Presenting multi-modal, multi-stability stimulation to reduce conditions associated with attention disease

Abstract

Presenting multi-modal, multi-stable stimuli to reduce symptoms associated with attention deviations due to impaired cognitive function of a user is provided herein. Systems and methods for presenting multi-modal stimuli to address symptoms associated with a condition are provided. The server may identify a first visual stimulus and a second visual stimulus associated with the condition. The server may present the first visual stimulus that at least partially overlaps the second visual stimulus to guide the user to interact with the display. The service may detect a response identifying an interaction associated with one of the first or second visual stimuli. The server may generate an auditory stimulus to include one or more portions indicative of response-based feedback.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Non-Provisional Application No. 18 / 757,253, filed on June 27, 2024, which claims priority to U.S. Provisional Application No. 63 / 547,456, filed on November 6, 2023, and U.S. Provisional Application No. 63 / 530,640, filed on August 3, 2023, all of which are incorporated herein by reference in their entirety. Technical Field

[0003] The present disclosure relates to the medical field, and more particularly to a method and system for presenting multimodal, multistable stimulation to reduce symptoms associated with attention bias caused by impaired cognitive function of a user. Background Art

[0004] Certain conditions may cause the subject to focus on certain deviations, which may eventually exacerbate their symptoms. Subjects may suffer from chronic pain, fear and emotional symptoms at the same time, such as the case of patients with multiple sclerosis (MS) or cancer. The desire to pay attention to pain, fear or other deviations is innate, and the subject may also become highly sensitive to deviations corresponding to relevant stimuli. For example, subjects with MS may pay more attention to pain-related stimuli than patients without chronic pain. Similarly, oversensitivity to negative or threat-related stimuli can exacerbate the subject's fear. For example, unlike patients without such conditions, patients with oversensitivity may look for signs of threat in social interactions. This focus on negative stimuli may cause the patient's symptoms to worsen. For example, the deviation to pain may cause the patient to be oversensitive. In addition, these oversensitivities may worsen the disease through fear avoidance. In fear avoidance, individuals can avoid those stimuli or activities that may cause pain or threats, thereby further weakening physical or mental illnesses due to lack of activity.

[0005] Treating attention biases in people with chronic conditions can be difficult because these conditions often lead to a general decline in cognitive function. Therapeutic exercises that mitigate the effects of these biases can reduce the severity of symptoms. Certain behavioral therapies can help individuals reduce or eliminate the biases that direct attention toward or away from certain stimuli. However, access to these behavioral therapies can be difficult, especially for people with chronic conditions such as MS or cancer. Additionally, the therapy may not be useful to an individual without consistent compliance, which can be difficult to ensure due to the nature of pain and fear. Finally, it can be difficult to determine which therapy will be most beneficial for an individual, or whether a combination of therapies would be most beneficial.

[0006] Addressing such attentional biases associated with chronic conditions in subjects by digitally presenting these therapeutic exercises through a device may present a number of problems. First, it may be impossible or extremely difficult for the user to refrain from focusing on negative stimuli and thus ignore any intervention attempts by the clinician or through the device. Therefore, due to the nature of the chronic condition, it may be difficult for the user to adhere to the digital treatment, resulting in ineffective clinical outcomes. On the other hand, it may be physically difficult for the subject to access the digital treatment through the device when the subject is experiencing pain, let alone contact the clinician to receive treatment. Summary of the invention

[0007] To address these and other technical challenges, a digital therapy using multimodal multistable bias modification (or multimodal, multistable bias modification or MMBM) can be provided to users with symptoms associated with attention bias caused by a condition that affects the user's cognitive function. By linking two different senses (e.g., multimodal perception using a set of visual stimuli and auditory multistable perception using auditory stimuli), the synergy generated by the multimodal multistable approach can provide enhanced training to the user to redirect attention to positive stimuli and address symptoms associated with the user's attention bias. In addition, the digital therapy described herein can provide auditory stimulation (e.g., binaural beats) to address auxiliary symptoms (e.g., fatigue) associated with the user's condition. In this way, the user can adjust the user to pay less attention to negative stimuli, such as stimuli associated with pain or stress, at a speed, frequency, and efficacy available through the digital therapy application.

[0008] The ability of a user to shift attention away from negative stimuli can be improved through a multimodal multistable perception modification method that includes visual and auditory stimulation. Controlling the bias towards negative stimuli may be an aspect of treating or addressing the symptoms of conditions such as MS or cancer. Multimodal methods may refer to therapies that are applicable to two or more senses of a user, such as hearing and vision. Multistable perception may refer to superimposing two media together so that they are detected by the same sense of the user. For example, multistable perception may include two images presented to the user, each of which attracts the user's attention or stands out to the user separately at different times when the user views the image.

[0009] Visual multistable perception can include monocular rivalry and binocular rivalry. During monocular rivalry, different images (or words) can be presented to each eye of the subject. Then, the subject changes her field of view between the image presented to the left eye and the image presented to the right eye. In binocular rivalry, two or more images can be superimposed on each other so that the subject can use both eyes to distinguish any image at different times. As a treatment method, two stimuli presented in images or words can be presented to the subject. The first stimulus can be a negative stimulus, or a stimulus associated with a disease. For example, the first stimulus can include the word "pain", "disease" or "tiredness". The second stimulus can be a positive or neutral stimulus that is not associated with the disease. For example, the second stimulus can include the word "love", "good" or "happy". These two stimuli can be presented to the subject as superimposed images. Through cognitive bias training, subjects can be trained to see more clearly, pay more attention, and are more inclined to pay attention to positive or neutral stimuli rather than negative stimuli.

[0010] In addition, binaural beats are a unique type of auditory multistable perception in this method. The system can present binaural beats as a combination of two or more sounds of different pitches or frequencies. Binaural beats can include a first sound presented to a subject's first ear and a second sound simultaneously presented to a subject's second ear. For example, presenting a frequency of 415 Hz to a patient's left ear while presenting a frequency of 400 Hz to the patient's right ear can cause the patient to hear a 15 Hz "beat". In some cases, this presentation of the beat can induce a beneficial therapeutic response.

[0011] By using a combination of binaural beats and binocular rivalry, the user's ability to resist bias against negative stimuli can be synergistically increased by multimodal multistable bias modification. Resisting bias against negative stimuli can be, for example, an aspect of treating or addressing the symptoms of chronic conditions (such as MS or tumor conditions). Multimodal multistable bias modification can include interventions such as binaural beats, in which the user receives two or more different but similar tones in each ear. Binaural beats can regulate brain activity based on the different frequency beats provided. For example, beats in the range of 14-30Hz have been shown to regulate brain activity associated with attention, alertness, and cognition. Therefore, providing a 415Hz tone in the patient's left ear and a 400Hz tone in the patient's right ear can produce a 15Hz beat, which can stimulate brain activity associated with attention, alertness, and cognition.

[0012] Users may adapt to pay less attention to negative biases associated with feelings such as pain, anxiety, or depression. Performing actions using binocular rivalry can accustom users to focusing on positive or neutral stimuli rather than negative stimuli. By presenting two superimposed images, users can perform tasks such as selecting an image associated with a positive or neutral stimulus. After selecting the correct (e.g., positive or neutral) stimulus, the user can receive positive feedback to bias the user toward positive or neutral stimuli and away from negative stimuli. Through this method, users can be trained to focus on images associated with positive or neutral stimuli.

[0013] The combination of these therapies can significantly reduce the bias towards negative stimuli. Due to the integration of multiple types of sensory information (such as vision and audio), combining these therapies can create a multimodal rich environment that is better close to the real world environment. As an illustrative example, the combination can include a service that provides games to users through the user's mobile device. The service can also be coupled with a set of speakers (e.g., headphones or earplugs) to play tones for each ear. The service can present two superimposed words to the user on the screen of the mobile device. The user can choose words that describe positive or neutral stimuli. The illustrative example shows binocular rivalry to encourage users to focus on positive or neutral stimuli rather than negative stimuli.

[0014] In addition to presenting visual stimulation, the service may also provide one or more different tones to each ear. Each tone in one ear may have a corresponding tone presented in the other ear. The tone and the corresponding tone may each have different frequencies, so that the frequency difference produces a beat. The beat can modulate brain activity to treat a variety of impairments caused by chronic diseases, such as fatigue, low cognitive acuity, anxiety, or pain perception. This multimodal approach can result in cross-modal interactions between the relevant brain regions for each stimulation. In this way, each brain region can be cross-activated during subsequent monosensory stimulation. In addition, the method can increase the functional connectivity of specific sensory regions. This combination of therapies provided by the service can alleviate the symptoms of chronic diseases.

[0015] To provide these therapies, the service may select two or more visual stimuli for the user, including at least two words or images and associated actions, to be transmitted to the end-user device. The service may select stimuli, including at least two tones, to be played to the user via two or more speakers. The service may also deliver or present stimuli to the user on a regular basis to avoid the user having to actively access the digital therapy application on their device when suffering from a chronic disease. The service may deliver or present stimuli to the user on a regular basis after completing a previous action associated with the stimulus. In addition, when the service obtains additional data about the user, the service may be able to select stimuli that are more targeted to a specific user and his or her condition, and store the data in the user's personal profile. The service may receive preferences from the user, such as a preferred word list or a preferred tones. The service may select subsequent stimuli based at least on previous stimuli, completion of previous actions, the user's personal profile, or an evaluation of the user's performance on previous stimuli.

[0016] In this way, users can easily receive stimuli related to chronic diseases to help retrain their bias against negative stimuli related to the conditions described herein. This can reduce or eliminate the obstacles for users to physically access their devices while fighting chronic diseases. By selecting stimuli sent to users to address the subject's bias against negative stimuli, the quality of human-computer interaction (HCI) between users and devices can be improved. In addition, because the stimuli are more relevant to the user's condition, unnecessary consumption of computing resources (e.g., processing and memory) and network bandwidth of services and user devices can be reduced relative to sending invalid messages. In addition, in the context of digital therapeutic applications, personalized selection of such stimuli can result in providing user-specific interventions to improve the subject's compliance with treatment. This can not only lead to higher compliance with therapeutic interventions, but also may improve the subject's bias against negative stimuli.

[0017] Because the digital therapeutic application operates on the subject's device, or at least on a device that the user can easily and reliably access (e.g., according to a predetermined frequency, such as once a day), the application can provide real-time support to the subject. For example, upon receiving a request from the user to initiate a treatment session, the application would initiate the treatment session in near real time. Such timely guidance cannot be achieved via an in-person visit, phone call, video conference, or even text message between the user and the healthcare provider who is examining the user for multiple sclerosis or cancer. Because of this accessibility, the application is able to provide and customize tasks for the user based on the user's performance. This can create an iteratively improving service for the user, where overall bandwidth and data communications are minimized due to the increased utility of each treatment session.

[0018] Aspects of the present disclosure relate to systems and methods for presenting multimodal stimulation to address symptoms associated with a disease. The system may include a computing system having one or more processors coupled to a memory. In order to address a user's disease, the computing system may identify (i) a first visual stimulus associated with the disease and (ii) a second visual stimulus. The computing system may present a first visual stimulus that at least partially overlaps the second visual stimulus via a display to guide the user to interact with the display. The system may detect a response that identifies the interaction. The interaction may be associated with one of the first visual stimulus or the second visual stimulus. The computing system may generate an auditory stimulus to include one or more parts. The one or more parts may indicate feedback based on a response. The computing system may play the auditory stimulus via a transducer to provide feedback to the user about the response.

[0019] In some embodiments, the computing system may determine that the response is correct based on an interaction associated with the second visual stimulus. The second visual stimulus may disassociate the user from the disease. In response to determining that the response is correct, the computing system may add at least a portion to the auditory stimulus to provide positive reinforcement. In some embodiments, the computing system may determine that the response is incorrect based on an interaction associated with the first visual stimulus associated with the disease. In response to determining that the response is incorrect, the computing system may remove at least a portion from the auditory stimulus to provide a negative penalty. In some embodiments, the computing system may assign (i) a first visual stimulus to a first type of interaction, and (ii) a second visual stimulus to a second type of interaction. The computing system may present (i) a first visual stimulus with a first indicator to identify a first type of interaction, and (ii) a second visual stimulus with a second indicator to identify a second type of interaction.

[0020] In some embodiments, the computing system can select a difficulty level from a set of difficulty levels based on a correct response rate from a previous presentation of a visual stimulus. Each difficulty level in the set of difficulty levels can define one or more visual features. The computing system can modify the presentation of the first visual stimulus and the second visual stimulus using the one or more visual features according to the difficulty level. In some embodiments, the computing system can generate an auditory stimulus to include (i) a first element to be played to a first ear of a user and (ii) a second element to be played to a second ear of the user. The computing system can provide the first element to the first ear of the user via a first speaker and provide the second element to the second ear via a second speaker. In some embodiments, the interaction can include an orientation of the display toward a side corresponding to one of the first side associated with the first visual stimulus or the second side associated with the second visual stimulus.

[0021] In some embodiments, the computing system may modify the visual features of one of the first visual stimulus or the second visual stimulus based on the response. In some embodiments, the computing system may play one of the one or more parts of the auditory stimulus. The computing system may play the one or more parts of the auditory stimulus at least partially simultaneously with the presentation of the first visual stimulus and the second visual stimulus. In some embodiments, the computing system may receive a user's selection of at least one characteristic from a set of auditory stimulus characteristics via an interface. The computing system may generate an auditory stimulus based on the at least one characteristic. In some embodiments, the computing system may receive a list identifying a plurality of words via an interface, the plurality of words including a first subset of words and a second subset of words associated with a disease. The computing system may select a first visual stimulus from the first subset of words and a second visual stimulus from the second subset of words. In some embodiments, at least partially simultaneously with the course of treatment, the user may be taking medication to treat a disease associated with at least one of cancer or multiple sclerosis.

[0022] Aspects of the present disclosure relate to systems and methods for alleviating symptoms associated with attention bias of a user suffering from a condition that affects cognitive functioning in need thereof. A computing system may obtain a first indicator associated with the user before a plurality of treatment sessions. The computing system may repeat during each treatment session of the plurality of treatment sessions: (i) presenting to the user via a display a corresponding set of visual stimuli, including (a) a first visual stimulus associated with the symptom and (b) a second visual stimulus at least partially overlapping the first visual stimulus to guide the user to perform an interaction, and (ii) playing a corresponding auditory stimulus to the user via a transducer to provide feedback based on an interaction with one of the corresponding set of visual stimuli via the display. The computing system may obtain a second indicator associated with the user after at least one of the plurality of treatment sessions. When the second indicator (i) decreases by a first predetermined margin from the first indicator or (ii) increases by a second predetermined margin from the first indicator, a symptom associated with the user's attention bias may be alleviated. In some embodiments, the attention bias may include one or more of the following: (i) avoiding stimuli or activities associated with the symptom; (ii) anxiety caused by stimuli associated with the symptom, multiple sclerosis, or cancer; or (iii) depressed mood.

[0023] In some embodiments, the user's condition may include multiple sclerosis (MS) with or without movement disorders. In some embodiments, a reduction in symptoms may occur when the second indicator increases from the first indicator by a second predetermined margin, and the first indicator and the second indicator may be symbol digital modality test (SDMT) values. In some embodiments, the user may relapse at least within a predefined time period before multiple courses of treatment and not use steroids. In some embodiments, the user may take medication at least partially concurrently with multiple courses of treatment, and the medication may include at least one of beta interferon, glatiramer, cladribine, dimethyl fumarate, deloximetate fumarate, fingolimod, monomethyl fumarate, ofatumumab, ozanimod, ponamod, siponimod, teriflunomide, alemtuzumab, mitoxantrone, or natalizumab.

[0024] In some embodiments, the user's condition may include at least one of lung cancer, colorectal cancer, skin cancer, breast cancer, ovarian cancer, leukemia, pancreatic cancer, or gastric cancer. In some embodiments, symptom relief may occur when the second indicator increases from the first indicator by a second predetermined margin, and the first indicator and the second indicator may be a Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) value. In some embodiments, the user may complete cancer chemotherapy within a predefined time period prior to multiple courses of treatment.

[0025] In some embodiments, a reduction in symptoms may occur when the second indicator is reduced by a first predetermined margin from the first indicator, and the first indicator and the second indicator may be Patient Reported Outcome Measurement Information System (PROMIS) values. In some embodiments, a reduction in symptoms may occur when the second indicator is reduced by a first predetermined margin from the first indicator, and the first indicator and the second indicator may be Brief Pain Inventory (BPI) values. In some embodiments, a reduction in symptoms may occur when the second indicator is reduced by a first predetermined margin from the first indicator, and the first indicator and the second indicator may be Pain Catastrophizing Scale (PCS) scores. In some embodiments, the first indicator and the second indicator may be computerized cognitive assessment values.

[0026] In some embodiments, the user may experience an improvement in fatigue associated with the condition in response to the binaural beats of the corresponding auditory stimulation in at least one of the plurality of treatment sessions. In some embodiments, the corresponding set of visual stimuli for each of the plurality of treatment sessions may be selected from a plurality of visual stimuli including (i) pain-related visual stimuli, (ii) threat-related visual stimuli, (iii) condition-related visual stimuli, (iv) negative visual stimuli, or (v) neutral visual stimuli.

[0027] In some embodiments, in at least one of the plurality of sessions, when the interaction with the corresponding set of visual stimuli is correct, a corresponding auditory stimulus may be played to provide positive reinforcement. In some embodiments, in at least one of the plurality of sessions, when the interaction with the corresponding set of visual stimuli is incorrect, a corresponding auditory stimulus may be played to provide negative punishment. In some embodiments, in at least one of the plurality of sessions, presentation of the corresponding visual stimulus may occur at least partially concurrently with playing of a portion of the corresponding auditory stimulus.

[0028] In some embodiments, in at least one of the plurality of sessions, presentation of the corresponding set of visual stimuli may be modified according to a difficulty level selected based on responses in a previous session. In some embodiments, the interaction includes orientation of the display toward a side corresponding to one of a first side associated with the first visual stimulus or a second side associated with the second visual stimulus. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The foregoing and other objects, aspects, features and advantages of the present disclosure will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings, in which:

[0030] Figure 1 depicts a block diagram of a system for presenting multimodal stimulation to address symptoms associated with a condition in accordance with an illustrative embodiment;

[0031] Figure 2 A block diagram depicting a process for presenting stimuli and detecting responses identifying interactions associated with the stimuli in accordance with an illustrative embodiment;

[0032] Figure 3 A block diagram depicting a process for generating auditory stimuli and playing the auditory stimuli to provide feedback according to an illustrative embodiment;

[0033] Figure 4 A flow chart depicting a method for presenting multimodal stimulation to address symptoms associated with a disorder according to an illustrative embodiment;

[0034] Figure 5 A screenshot depicting an example user interface of a system for presenting multimodal stimulation to address symptoms associated with a condition in accordance with an illustrative embodiment;

[0035] Figure 6 A screenshot depicting an example user interface of a system for presenting multimodal stimulation to address symptoms associated with a condition in accordance with an illustrative embodiment;

[0036] Figure 7 A flow chart depicting a method of alleviating symptoms associated with attention bias in a user suffering from a condition that affects their required cognitive functions according to an illustrative embodiment;

[0037] Figure 8 Depicting a timeline of a randomized, controlled, exploratory basket study to evaluate multimodal multistable bias modification for normalization of attention bias and cognitive improvement in adults with multiple sclerosis, breast cancer, and lung cancer according to an illustrative embodiment;

[0038] Fig. 9 is a block diagram of a server system and a client computer system according to an illustrative embodiment;

[0039] Fig.10 Results from the PROMIS-Fatigue study are depicted. In PROMIS-Fatigue, lower scores are improvements (patients have less fatigue). Clinically important change: 2 to 6 points;

[0040] Fig.11 Describes the results of the PROMIS-Depression Study. In PROMIS-Depression, lower scores are improvements (patients have less severe depression). Clinically important change: 2 to 6 points;

[0041] Fig.12 Describes the results of the PROMIS-Anxiety Study. In PROMIS-Anxiety, lower scores are improvements (patients have less anxiety). Clinically important change: 2 to 6 points;

[0042] Fig.13 Describes the results of the PROMIS-Pain Interference Study. In PROMIS-Pain Interference, lower scores are improvements (patients have less pain interference). Clinically important change: 2 to 6 points;

[0043] Fig.14 Results of the PROMIS pain score study are described. In PROMIS-Pain Interference, lower scores are improvements (patients have less pain interference). Clinically important change: ≥2;

[0044] Fig.15 Describes the results of the PROMIS-Sleep Disorders Study. In PROMIS-Sleep Disorders, lower scores are improvements (patients have less sleep disturbance). Clinically important change: 2 to 6 points;

[0045] Fig.16 Describes the results of the PROMIS-Physical Functioning Study. In PROMIS-Physical Functioning, higher scores are improvements (patients experience better physical function). Clinically Important Change: 2 to 6 points;

[0046] Fig.17 Describes the results of the PROMIS-Cognitive Functioning study. In PROMIS-Cognitive Functioning, higher scores are improvements (patients experience better cognitive functioning). Clinically important change: 2 to 6 points;

[0047] Fig.18 Describes the results of the PROMIS-Social Functioning study. In PROMIS-Social Functioning, higher scores are improvements (patients experience better social functioning). Clinically important change: 2 to 6 points;

[0048] Fig.19 Depicts results of the Brief Pain Inventory Study for Interference. Lower scores indicate improvement (less pain interference). Clinically important change: ≥1 point;

[0049] Fig. 20 Describes the results of the Brief Pain Inventory Study for worst pain severity. Lower scores indicate improvement (less pain). Clinically important change: ≥1 point;

[0050] Fig.21 Describes the results of the Brief Pain Inventory Study for minimal pain severity. Lower scores indicate improvement (less pain). Clinically important change: ≥1 point;

[0051] Fig. 22 Results of the Brief Pain Inventory Study for mean pain severity are depicted. Lower scores indicate improvement (less pain). Clinically important change: ≥1 point;

[0052] Fig.23 Describes the results of the Brief Pain Inventory Study for current pain severity. Lower scores indicate improvement (less pain). Clinically important change: ≥1 point;

[0053] Fig.24 Depicting the results of a study on the Pain Catastrophizing Scale. Lower numbers = lower pain catastrophizing (better symptoms). Minimum detectable change: 9.1 points;

[0054] Fig.25 Results depicting patient-reported outcomes for MS cognition. Higher scores indicate better cognitive functioning. Clinically important change: 4 points;

[0055] Fig.26 Results depicting the global score of change (GRC) between DiNaMo and control;

[0056] Fig. 27 Depicts the results of a study of the Attention Bias Index for depression. Attention Bias Index: The goal is to be close to 0 (no bias) or lower (deviation from the triggering stimulus);

[0057] Fig.28 Depicts the results of a study of the Attention Bias Index for anxiety. Attention Bias Index: The goal is to be close to 0 (no bias) or lower (biased towards the triggering stimulus); and

[0058] Fig.29Depicts the results of an Attention Bias Index study for indications. Attention Bias Index: The goal is to be close to 0 (no bias) or lower (deviation from the triggering stimulus). DETAILED DESCRIPTION

[0059] In order to read the description of the following embodiments, the following enumeration of the various parts of the specification and their corresponding contents may be useful:

[0060] Section A describes systems and methods for presenting multimodal stimulation to address symptoms associated with a condition;

[0061] Section B describes a method of alleviating symptoms associated with attention bias in a user with a condition that affects their desired cognitive function; and

[0062] Section C describes networking and computing environments that may be useful for practicing the embodiments described herein.

[0063] A. Systems and methods for presenting multimodal stimulation to address symptoms associated with a condition

[0064] Reference now Figure 1 , depicting a block diagram of a system 100 for presenting multimodal stimulation to address symptoms associated with a condition. In general, the system 100 may include at least one therapy session management service 105 and a set of user devices 110A-N (hereinafter generally referred to as user devices 110 or client devices), which are communicatively coupled to each other via at least one network 115. At least one user device 110 (e.g., the first user device 110A as shown) may include at least one transducer 120 and at least one application 125. The application 125 may include or provide at least one user interface 130 having one or more user interface (UI) elements 135A-N (hereinafter generally referred to as UI elements 135). The therapy session management service 105 may include at least one therapy session manager 140, a stimulation selector 145, a response handler 150, a performance evaluator 155, or at least one feedback provider 160, etc. The therapy session management service 105 may include or have access to at least one database 165. The database 165 may store, maintain or otherwise include one or more user profiles 170A-N (hereinafter generally referred to as user profiles 170), one or more visual stimuli 175A-N (hereinafter collectively referred to as visual stimuli 175), or one or more auditory stimuli 180A-N (hereinafter generally referred to as auditory stimuli 180), etc. The functionality of the application 125 may be partially performed on the treatment management service 105. The functionality of the application 125 may also be combined with operations performed on the treatment management service 105.

[0065] In more detail, the course management service 105 can be (sometimes generally referred to herein as a computing system or service) any computing device including one or more processors that are coupled to memory and software and are capable of performing the various processes and tasks described herein. The course management service 105 can communicate with one or more user devices 110 and a database 165 via a network 115. The course management service 105 can be located, located, or otherwise associated with at least one server group. The server group can correspond to a data center, a branch office, or a site where one or more servers corresponding to the course management service 105 are located. The course management service 105 can be located, located, or otherwise associated with one or more user devices 110. Some components of the course management service 105 can be located within the server group, while some components can be located within the client device. For example, the course manager 140 can operate or be located on the user device 110A, and the stimulus selector 145 can operate or be located on the server group.

[0066] In the treatment management service 105, the treatment manager 140 may identify a treatment that includes a set of visual stimuli 175, which are presented to the user by the application 125 on the corresponding user device 110. The treatment manager 140 may identify a first visual stimulus and a second visual stimulus for addressing the user's condition. The stimulus selector 145 may present the first visual stimulus at least partially overlapping the second visual stimulus to guide the user to interact via a display (such as the user interface 130). The response handler 150 may detect a response that identifies an interaction associated with the first visual stimulus or the second visual stimulus. The performance evaluator 155 may determine a score based on the response. The feedback provider 160 may generate an auditory stimulus including one or more parts to indicate feedback to the user via the transducer 120 based on the response. The feedback provider 160 may generate an auditory stimulus that plays the one or more parts at least partially while the stimulus selector 145 presents the visual stimulus.

[0067] The user device 110 (sometimes referred to herein as an end-user computing device or client device) can be any computing device including one or more processors coupled with memory and software and capable of performing the various processes and tasks described herein. The user device 110 can communicate with the treatment management service 105 and the database 165 via the network 115. The user device 110 can be a smartphone, other mobile phone, tablet computer, wearable computing device (e.g., smart watch, glasses), or laptop computer. The user device 110 can be used to access the application 125. In some embodiments, the application 125 can be downloaded and installed on the user device 110 (e.g., via a digital distribution platform). In some embodiments, the application 125 can be a web application with resources accessible via the network 115.

[0068] In some embodiments, the user device 110 may be coupled to at least one transducer 120. The transducer 120 may convert an electrical signal provided by the treatment management service 105 into an audio signal. The transducer 120 may generate one or more audio signals for output by one or more speakers coupled to the transducer 120. The transducer 120 may generate an audio signal, such as a tone, a beep, a note, a voice, or other sound, for playback by the speaker. The transducer 120 may generate instructions for the speaker to play one or more sounds. For example, the transducer 120 may generate an audio signal in a musical instrument digital interface (MIDI) format for output by the speaker. The transducer may generate instructions including pre-recorded sounds for playback by the speaker. For example, the transducer may generate an audio signal according to a recorded audio format, such as a moving picture experts group (MPEG), audio layer 3 (MP3), or a waveform audio file (WAV). The audio signal may include instructions for playback of the sound, such as volume, pitch, speed, rhythm, compression, panning, bit rate, distortion, or timbre.

[0069] Continuing, the transducer 120 can transmit the audio signal or instruction to one or more speakers. The speaker can be any device designed or configured to emit audio. The speaker can include a magnet, a cone, an audio amplifier or other such device to generate mechanical vibrations to output sound from the signal. In some embodiments, the speaker can be coupled to the transducer 120 or included in the transducer 120. For example, the speaker and the transducer 120 can be part of the same speaker, earphone, earplug or other device to convert the electrical signal into audio and generate output audio. In some embodiments, the transducer 120 can be configured to generate two or more audio signals for two or more speakers. For example, the first transducer 120 can generate a first audio signal for a first speaker to play in the left ear of the subject, and the second transducer 120 can simultaneously generate a second audio signal for a second speaker to play in the right ear of the subject. The transducer 120 can play multiple tones or sounds through each speaker. For example, the transducer 120 may superimpose a 500 Hz signal on a 300 Hz signal, or the transducer may alternately play the two signals, as well as other combinations of two or more signals played through one speaker.

[0070] The application 125 executed on the user device 110 may be a digital therapeutic application and may provide a treatment session (sometimes referred to herein as a therapy session) to address symptoms associated with a condition. The user of the application 125 may suffer from or be at risk for the condition. The condition may include, for example, cancer (e.g., lung cancer, colorectal cancer, skin cancer, breast cancer, ovarian cancer, leukemia, pancreatic cancer, or gastric cancer) or multiple sclerosis (e.g., with or without a mobility impairment). The condition may have symptoms such as pain, fear, or fatigue due to attention biases associated with cancer or multiple sclerosis.

[0071] Attention bias may include, for example, avoidance of stimuli or activities associated with a symptom; anxiety caused by stimuli associated with a symptom or condition; or depression (or depressed mood), etc. The user may pay attention to stimuli associated with symptoms of the condition, such as pain, fatigue, or actions that cause symptoms, such as certain actions or behaviors. For example, the user may increase sensitivity to pain by avoiding movements that may cause pain, thereby further limiting the user and causing anxiety about movements that are believed to cause pain. Other behaviors may cause the user's condition or be related to the user's condition. Application 125 can be used to present stimuli, prompting the user to perform actions to reduce the bias against negative stimuli associated with the user's condition. The action can be presented to the user as a result of sending a request to start a treatment, a detection measurement of the user received from a client device, or a predetermined time or period, etc.

[0072] The user may be taking an effective amount of medication to treat the condition at least in part concurrently, at least in part concurrently with the course of treatment performed through the application 125. The medication may be at least orally, intravenously, or topically applied. For example, for multiple sclerosis, the user may be taking beta interferon, glatiramer, cladribine, dimethyl fumarate, deloximetate fumarate, fingolimod, monomethyl fumarate, ofatumumab, ozanimod, ponesimod, sipomod, teriflunomide, alemtuzumab, mitoxantrone, or natalizumab, etc. For cancer, the user may have received chemotherapy, radiotherapy, or immunotherapy, etc. A user with cancer may also be taking painkillers, such as acetaminophen, aspirin, ibuprofen, naproxen, and nonsteroidal anti-inflammatory drugs, etc. The application 125 can improve the efficacy of the medication the user is taking to address the condition.

[0073] Application 125 may include, present, or otherwise provide a user interface 130 including one or more UI elements 135 to a user of user device 110, depending on the configuration on application 125. UI elements 135 may correspond to visual components of user interface 130, such as command buttons, text boxes, check boxes, radio buttons, menu items, sliders, etc. In some embodiments, application 125 may be a digital therapeutic application and may provide a therapy session (sometimes referred to herein as a therapy session) via user interface 130 to address the deviation from negative stimuli associated with the condition.

[0074] Application 125 may receive instructions to present visual stimulation 175 or auditory stimulation 180 to the user. Visual stimulation 175 may be or include stimulation or actions presented to the user in the form of text, images, videos, or other visual presentations, and may include instructions for the user to perform actions to address symptoms associated with the condition. Auditory stimulation 180 may be or include stimulation or actions presented audibly via transducer 120 coupled to a speaker.

[0075] The action associated with the visual stimulus 175 may include interacting or not interacting with the user device 110. For example, the action may include tilting the user interface 130 or clicking on the visual stimulus 175 presented by the user device 110. In some embodiments, tilting the user device may change the presentation of the visual stimulus 175. For example, tilting the mobile device to the left may cause the first visual stimulus to become clearer or more prominent than the second visual stimulus. In a similar manner, tilting the mobile device to the right may cause the second visual stimulus to become clearer or more prominent than the first visual stimulus. The action may include instructions for the user to address the condition. For example, the action may include a message with instructions describing the attention bias to negative stimuli to be reduced. The action may include an interactive interface through the user interface 130 to engage the user in one or more therapies intended to reduce or mitigate the bias to negative stimuli associated with the condition. For example, a user may play a game presented by the application 125 on the user device 110 that contains one or more therapies to address the bias.

[0076] The database 165 may store and maintain various resources and data associated with the treatment management service 105 and the application 125. The database 165 may include a database management system (DBMS) to arrange and organize the data maintained thereon. The database 165 may communicate with the treatment management service 105 and one or more user devices 110 via the network 115. When running various operations, the treatment management service 105 and the application 125 may access the database 165 to retrieve identified data therefrom. The treatment management service 105 and the application 125 may also write data to the database 165 when running such operations.

[0077] Such operations may include maintaining a user profile 170 (sometimes referred to herein as a subject profile). User profile 170 may include information related to the user's condition, as described herein. For example, user profile 170 may include information related to the severity of the condition, the occurrence of the condition (such as the occurrence of symptoms associated with attention bias due to the condition's impact on the user's cognitive function), medications or treatments taken by the user for the condition, and / or the duration of the condition, etc. User profile 170 may be updated in response to a schedule, periodically (e.g., daily, weekly), in response to changes in user information (e.g., input by the user via user interface 130 or learned from user device 110), or in response to a clinician (e.g., a doctor or nurse) addressing the user's condition, etc.

[0078] The user profile 170 may store and maintain information related to the user of the application 125 via the user device 110. Each user profile 170 may be associated or correspond to a respective subject or user of the application 125. The user profile 170 may contain or store information for each treatment session performed by the user. The information for the treatment session may include various parameters, actions, visual stimuli 175, auditory stimuli 180, or tasks of previous treatment sessions performed by the user, and may initially be empty. The user profile 170 may enable simplified communication with the user by presenting the user with tasks that are most likely to help the user resolve their condition symptoms or reduce bias to negative stimuli based at least on the user profile 170. This targeted approach may reduce the need to communicate with the user multiple times, thereby reducing bandwidth and increasing the benefits of user-computer interaction.

[0079] In some embodiments, the user profile 170 may identify or include information about the treatment regimen taken by the user, such as the type of treatment (e.g., therapy, medication, or psychotherapy), duration (e.g., day, week, or year), and frequency (e.g., daily, weekly, quarterly, annually), etc. The user profile 170 may be stored and maintained in the database 165 using one or more files (e.g., Extensible Markup Language (XML), Comma Separated Values ​​(CSV) delimited text files, or Structured Query Language (SQL) files). The user profile 170 may be iteratively updated as the user provides responses and performs actions associated with the visual stimulus 175, auditory stimulus 180, or treatment session.

[0080] Visual stimulation 175 may be or include stimulation or action presented to the user in the form of text, image, video or other visual presentation. For example, visual stimulation 175 may include animation presented via user interface 130 of user device 110. Visual stimulation 175 may include images, such as photos, digital images, art, charts, shapes or other images. Visual stimulation 175 may include live, pre-recorded or generated videos or animations, such as video recordings, animated shorts or animated images (e.g., graphics interchange format (GIF)). Visual stimulation 175 may include 3-dimensional (3D) visual presentations, such as holograms, projections or other 3D visual media. Visual stimulation 175 may have any size or orientation that user interface 130 can perform. Visual stimulation 175 may include text, such as words or sentences to be presented to the user via user interface 130. Visual stimulation 175 may include instructions for users to perform actions to solve symptoms associated with illness. For example, visual stimulation 175 may include text or graphics that depict actions taken or performed by users for visual stimulation 175.

[0081] The visual stimulus 175 may include two or more text-based or image-based stimuli. In some embodiments, two or more stimuli may be superimposed on each other so that the user can focus on and understand one stimulus at a time. For example, two visual stimuli including text may be presented via the user interface 130. The two visual stimuli may overlap so that the user can read the two visual stimuli. The user may be able to focus on one of the two visual stimuli to make the one visual stimulus more focused. In some embodiments, one or more visual stimuli 175 may have a positive or neutral meaning, while one or more other visual stimuli 175 may have a negative meaning. For example, the first visual stimulus may be a word or image with a positive association, such as an image of "love" or a smiling baby. The second visual stimulus may be a word or image with a negative association, such as an image of "pain" or a crying baby. In some cases, the second visual stimulus may be associated with the user's illness. For example, the second visual stimulus may include a word associated with the illness, such as "pain" or an image or video associated with the illness, such as an image of someone suffering.

[0082] Auditory stimulation 180 may be or include stimulation presented to the user in an auditory manner via a transducer 120 coupled to user device 110. Auditory stimulation 180 may include pre-recorded sounds, such as recordings of speech, musical instruments, natural sounds (e.g., rain or whale songs), or other such recordings. Auditory stimulation 180 may include computer-generated sounds, such as MIDI tones, white noise, brown noise, or computer-generated speech, as well as other computer-generated sounds. Auditory stimulation 180 may include live sounds, such as sounds from a radio station. Auditory stimulation 180 may be divided into multiple parts. Auditory stimulation 180 may include or be divided into multiple parts, each of which is a subset of the auditory stimulation. For example, a part may be a tone over a period of time, multiple tones over a period of time, or a tone frequency of a first auditory stimulation, etc. Auditory stimulation 180 may be each part played together, or different parts at different times, such as a music pattern. In some embodiments, stimulation may include music, words including different color and font options, word selections, binaural beats including alpha or beta wavelengths (e.g., wavelengths associated with a relaxed or restful state of mind), and vibrations of various frequencies in addition to music.

[0083] In addition, the identification of the visual stimulus 175 and the auditory stimulus 180 may be stored and maintained on the database 165. For example, the database 165 may maintain the visual stimulus 175 using one or more data structures or files (e.g., extensible markup language (XML), comma separated value (CSV) delimited text files, joint photo experts group (JPEG), or structured query language (SQL) files). Each of the visual stimulus 175 may prompt the user to perform an action via the application 125 via the application 125. For example, the application 125 may receive instructions to present an activity to be performed as part of the visual stimulus 175. The visual stimulus 175 may be used to provide therapy to reduce bias against negative stimuli associated with a condition, a symptom of a condition, or other cognitive or behavioral effects of a condition. The visual stimulus 175 may be presented as a game, activity, or action that the user performs via the user interface 130. For example, one or more visual stimuli 175 may be presented as overlay text, prompting the user to select a visual stimulus 175 that does not have a negative association.

[0084] Reference now Figure 2, depicting a block diagram of a process 200 for presenting a stimulus and detecting a response identifying an interaction associated with the stimulus. The process 200 may include or correspond to operations performed in the system 100 to present a multimodal stimulus to address symptoms associated with a condition. Under the process 200, the treatment manager 140 executing on the treatment management service 105 may access the database 165 to retrieve, obtain, or otherwise identify a user profile 170 of a user 210 (sometimes referred to herein as a subject, patient, or person) of the application 125 on the user device 110. The user profile 170 may identify or define information associated with the user 210, the instance of the application 125 on the user device 110, and the user device 110, etc. For example, the user profile 170 may identify that the user 210 has a certain bias against negative stimuli, symptoms associated with the condition, or other cognitive or behavioral consequences of the condition. The user profile 170 may identify that the user 210 takes medication to address the condition in the user 210 or symptoms associated with the condition, etc.

[0085] The treatment manager 140 can determine or identify a treatment for the user 210 that is used to address the symptoms associated with the condition. The treatment can correspond to, include, or define a set of stimuli, such as visual stimuli 175 or auditory stimuli 180, presented to the user 210 via the application 125. Each stimulus can be an audio, visual, or tactile stimulus to address the user's condition. The treatment manager 140 can identify a treatment for addressing the condition of the user 210 associated with the user profile 170.

[0086] The user profile 170 may include information about the visual stimulus 175, the auditory stimulus 180, previous treatment sessions (such as previous visual stimulus 175 identified for the user 210), performance associated with the visual stimulus 175 identified for the user 210, or medication taken by the user 210 to address the user's condition, etc. The user profile 170 may also identify or include information about recorded deviation performance, such as the number of negative deviation occurrences, symptoms associated with the condition, the number of occurrences of deviations that engage in negative, positive, or neutral stimuli associated with the condition, the duration of previous occurrences, and medication taken, etc. The user profile 170 may initially lack information about previous treatment sessions, but may build information as the user 210 participates in a treatment session via the application 125. The user profile 170 may be used to select one or more stimuli 175 to be provided to the user 210 via the application 125 during a treatment session.

[0087] The treatment manager 140 may initiate the treatment session in response to receiving a request from the user 210 via the application 125. The user 210 may provide a request to initiate the treatment session via the user interface 130 for execution through the application 125. The request may include information related to the onset of the user's condition. The request may include attributes associated with the condition, such as an identification of the user 210 or the user profile 170, symptoms associated with the condition of the user 210, the time of the request or the severity of the condition, etc. The application 125 operating on the user device 110 may generate a request to initiate the treatment session to send to the treatment management service 105 in response to the user 210 interacting with the application 125. In some embodiments, the treatment manager 140 may initiate the treatment session in response to a scheduled treatment session time, in response to receiving a setting 205, or based on the user 210 taking a prescribed medication to address the condition, etc.

[0088] The treatment session manager 140 may initiate the treatment session in response to receiving the treatment session operation preference. The treatment session manager 140 may identify one or more stimuli to present to the user 210 to address the condition based on input including settings 205 (also referred to herein as user settings 205) from the user 210. The user 210 may provide the settings 205 before, during, or after the treatment session provided by the treatment session manager 140. In some embodiments, the user 210 may provide the settings 205 along with the request to initiate the treatment session. The user 210 may provide the settings 205 via the user interface 130. The user 210 may interact with the user interface 130 via the UI elements 135 to provide input for the settings 205 for the execution of the treatment session, the identification of the visual stimuli 175, the duration of time that the treatment session is available, or the symptoms or conditions to be addressed during the treatment session, etc.

[0089] The stimulus selector 145 executing on the treatment session management service 105 may select or identify a set of visual stimuli 175 to present to the user 210 in the treatment session. The stimulus selector 145 may select the visual stimuli 175 from the stimuli identified by the treatment session manager 140. The stimulus selector 145 may select the visual stimuli 175 as part of the treatment session to perform attention bias modification training (ABMT) on the user 210 suffering from the condition. The set of visual stimuli 175 may include at least one visual stimulus 175A associated with the condition. As part of the ABMT treatment session, the stimulus selector 145 may select a first visual stimulus 175A and a second visual stimulus 175B for the user 210. Each visual stimulus 175 may correspond to or be associated with an action to be performed by the user 210 via the application 125 or the user device 110 itself. For example, the first visual stimulus 175A may be associated with a leftward tilt of the user device 110, while the second visual stimulus 175B may be associated with a rightward tilt of the user device 110.

[0090] The first visual stimulus 175A may be a visual stimulus associated with a disease (e.g., threat-related, disease-related, pain-related or other negative associations). In contrast, the second visual stimulus 175B may be a visual stimulus not associated with a disease (e.g., neutral or positive associations). In some cases, the first visual stimulus 175A may be a negative stimulus associated with a disease. For example, the first visual stimulus 175A may include text containing negative words associated with the disease, such as "pain", "soreness", "fear" or "tiredness". The first visual stimulus 175A may include an image associated with the disease. For example, the first visual stimulus 175A may include an image of a sad or frowning face, an image of a stormy rain cloud or an image of a barking dog, etc. In some cases, the second visual stimulus 175B may be a positive or neutral stimulus. The second visual stimulus 175B may not be associated with a disease. For example, the second visual stimulus 175B may include a positive text containing one or more words, such as "happy", "good", "smile" or "love". The second visual stimulus 175B may include a neutral text containing one or more words, such as "beach", "puppy" or "dinner". The second visual stimulus 175B may include a positive or neutral image. For example, the second visual stimulus 175B may be a picture of a tree, a baby, or a bicycle.

[0091] In some embodiments, the stimulus selector 145 may select the visual stimulus 175 based on the user profile 170. The user profile 170 may include historical information related to the user's condition, such as the occurrence or type of symptoms, the time when the symptoms occurred, the intensity of the bias to negative stimuli associated with the condition, demographic information, prescription information, location information, etc. For example, the treatment manager 140 may identify a visual stimulus 175 that was historically positively associated by the user 210 to improve the user's bias to negative stimuli.

[0092] In some embodiments, the stimulus selector 145 may identify the set of visual stimuli 175 based on the user settings 205. The user settings 205 may indicate the user's preferred stimuli, such as preferred colors, font types, or types of visual stimuli 175 (e.g., images or videos). The user settings 205 may identify images, text, or other visual stimuli 175 that the user 210 associates with a condition. The user settings 205 may identify visual stimuli 175 that the user 210 positively associates or disassociates with a condition. For example, the user 210 may select the type of visual stimuli 175, or provide guidance or criteria for the visual stimuli 175. The user settings 205 may indicate preferred auditory stimuli 180. For example, the user settings 205 may identify sounds that the user 210 positively associates and sounds that the user 210 negatively associates. In this way, the stimulus selector 145 may select auditory stimuli 180 that may serve as positive reinforcement or negative punishment for the user 210.

[0093] The user may provide user settings 205 to the session manager 140, or the session manager 140 may retrieve the user settings 205. The user 210 may provide the user settings 205, or the session manager 140 may retrieve the settings 205 from an external computing system, a clinician, or a pre-generated visual or auditory stimulus library. The user settings 205 may include the settings 205 as a file, such as a comma separated file (CSV), a word document (DOC), a standard MIDI file (SMF), or an MP3, etc. The user settings 205 may be provided via input into an application 125 operating on the user device 110.

[0094] The user settings 205 may include a list identifying a set of visual stimuli. For example, the user settings 205 may include a list of words selected from an interface provided before any treatment session begins, or as part of the startup process of the login application 125. The visual stimulus 175 may be selected from the set or list of words provided in the settings 205. The user 210 may provide a first set of words related to the condition (or symptom) and a second set of words unrelated to the condition (or symptom) via the interface 130. The user 210 may provide a first set of words with negative associations and a second set of words with positive or neutral associations via the interface 130. The stimulus selector 145 may select a first visual stimulus 175A from the first set of words and a second visual stimulus 175B from the second set of words.

[0095] The user settings 205 may include characteristics of the auditory stimulation. The characteristics may include attributes associated with the auditory stimulation, such as volume, pitch, speed, rhythm, compression, sound image, bit rate, distortion, or timbre. For example, the user settings 205 may include the maximum or minimum volume required for the playback of the auditory stimulation 180. The user settings 205 may include preferred or unpreferred instruments, rhythms, or pitches. The characteristics may include desired sounds selected by the user 210. For example, the user 210 may select preferred songs or preferred song types to be played as part of the auditory stimulation 180. The user 210 may select disliked sounds or songs as part of the auditory stimulation 180.

[0096] In some embodiments, the stimulus selector 145 may identify the visual stimulus 175 or the auditory stimulus 180 based on a predefined stimulus schedule. For example, the stimulus selector 145 may identify the first visual stimulus 175A as a visual stimulus associated with a condition according to a predefined task schedule. In this illustrative example, the stimulus selector 145 may identify the second visual stimulus 175B based on a subsequent stimulus of the predefined schedule. For example, the predefined stimulus schedule may include a first and a second stimulus corresponding to a visual stimulus, a third stimulus corresponding to an auditory stimulus, or a fourth stimulus corresponding to a tactile stimulus. The treatment manager 140 may define a schedule or time at which the stimulus selector 145 may identify a stimulus or mark a stimulus to be presented. In some embodiments, the stimulus selector 145 may identify the visual stimulus 175 or the auditory stimulus 180 based on a set of rules. The rules may be configured to provide a visual stimulus 175 or a set of visual stimuli 175 to target the root cause or alleviate the symptoms of the condition of the user 210 in a systematic, objective, and therapeutically effective manner. The rule may be based on a completion time of an action associated with the playing of the visual stimulus 175 , the user profile 170 , the auditory stimulus 180 , or other attributes of the system 100 .

[0097] In some embodiments, the stimulus selector 145 may assign an interaction type to each of the visual stimuli 175. The stimulus selector 145 may assign a first type of interaction to the first visual stimulus 175A and a second type of interaction to the second visual stimulus 175B. The interaction type may be or include manipulation of the user device 110, touching or pressing the user interface 130, or speaking to the user device 110, etc. For example, the interaction may include the user 210 tilting the user device 110. For example, the interaction may include the user 210 pressing a button (a button of the UI element 135) presented by the application 125. In some embodiments, the first type of interaction associated with the first visual stimulus 175A may be related to a condition of the user 210. For example, when the user interface 130 presents the word "pain", the first type of interaction may include selecting a button of the UI element 135 corresponding to the first visual stimulus 175A. In some embodiments, the second type of interaction associated with the second visual stimulus 175B may include disassociating the user from the condition. For example, the second type of interaction may include not pressing a button associated with the word "pain," or pressing a button associated with a positive second visual stimulus 175B, such as the word "pleasure."

[0098] Upon identification, the session manager 140 may provide, send, or otherwise communicate a set of visual stimuli 175 to the user device 110. In some embodiments, the session manager 140 may send instructions for presenting the visual stimuli 175 via the user interface 130 for the application 125 on the user device 110. The instructions may include, for example, specifications regarding which UI elements 135 are to be used, and may identify content to be displayed on the UI elements 135 of the user interface 130. The instructions may further identify or include the visual stimuli 175. The instructions may be code, a data packet, or a control to present the visual stimuli 175 to the user 210 via the application 125 running on the user device 110.

[0099] Continuing, the instructions may include processing instructions for displaying visual stimulation 175 on application 125. The instructions may include processing instructions for playing audio associated with auditory stimulation 180, or instructions for actuating a haptic system of user device 110. The instructions may also include instructions for user 210 to perform for their treatment regimen. For example, the instructions may display a message instructing user 210 to take medication associated with their treatment regimen. Visual stimulation 175 may include text, images, or videos presented by user device 110 via application 125. For example, visual stimulation 175 may include an image presentation instructing user 210 to interact with application 125 via user interface 130.

[0100] The application 125 on the user device 110 may render, display, or otherwise present a set of visual stimuli 175. The visual stimuli 175 may be presented via one or more UI elements 135 of the user interface 130 of the application 125 on the user device 110. The presentation of the UI elements 135 may be performed in accordance with instructions provided by the treatment manager 140 to present the visual stimuli 175 to the user 210 via the application 125. In some embodiments, the application 125 may render, display, or otherwise present the visual stimuli 175 independently of the treatment management service 105. The application 125 may share or have the same functionality as the treatment manager 140, the stimulus selector 145, or other components of the treatment management service 105, as described above. For example, the application 125 may maintain a timer to track the time that has passed since the presentation of the previous visual stimulus 175. The application 125 may compare the elapsed time to the time limit of the visual stimulus 175. When the elapsed time exceeds the time limit, the application 125 may determine to present the visual stimulus 175. The application 125 may also use a schedule to determine when to present one or more visual stimuli 175. Application 125 may present visual stimulus 175 for display via user interface 130 on user device 110 .

[0101] Application 125 may display, render, or otherwise present visual stimuli 175A and 175B at at least partially concurrent locations of user interface 130 of user device 110. A concurrent location may refer to a location on a display (e.g., user interface 130) where at least a portion of visual stimulus 175A is presented and overlaps at least a portion of visual stimulus 175B. For example, visual stimuli 175A and 175B may overlap in whole or in part. Visual stimuli 175A and 175B may overlap at different opacities. Opacity may refer to the transparency of visual stimulus 175A. In some cases, the opacity of first visual stimulus 175A may be greater than that of second visual stimulus 175B, such that for each overlapping portion of visual stimuli 175A and 175B, first visual stimulus 175A completely covers second visual stimulus 175B. In some cases, the opacity of first visual stimulus 175A may be equal to or sufficiently similar to the opacity of second visual stimulus 175B such that both first visual stimulus 175A and second visual stimulus 175B are visible or legible when presented on user interface 130 via application 125. The presentation of overlapping visual stimuli 175A and 175B may vary in opacity. For example, during a first time period, first visual stimulus 175A may have a greater opacity than second visual stimulus 175B, and during a second time period, first visual stimulus 175A may have a lower opacity than second visual stimulus 175B.

[0102] In some embodiments, the application 125 may display, render or otherwise present visual stimuli 175A and 175B for different time periods. The application 125 may present the first visual stimulus 175A in a first time period and the second visual stimulus 175B in a second time period. For example, the application 125 may present the first visual stimulus 175A during the first time period and then present the second visual stimulus 175B during the second time period. In some cases, the application 125 may present the second visual stimulus 175B after displaying the first visual stimulus 175A with a delay. The application may present the visual stimuli 175A and 175B simultaneously. Presenting the visual stimuli 175A and 175B simultaneously may refer to displaying the visual stimuli 175 during the same time period or at a concurrent display position on the user interface 130. The same time period may refer to the first time period and the second time period overlapping in whole or in part. For example, the presentation of the first stimulus 175A may overlap the presentation of the second stimulus 175B in duration. The application 125 may present the visual stimuli 175A and 175B in the same time period or in different time periods. For example, a first time period associated with first visual stimulus 175A may be the same or equal to a second time period associated with second visual stimulus 175B.

[0103] In some embodiments, the application 125 may present the visual stimulus 175 simultaneously with another type of stimulus. For example, the application 125 may display the visual stimulus 175A and 175B simultaneously with the auditory stimulus 180. The application 125 may display one or more visual stimuli 175 without the auditory stimulus 180 during a first time period. The application 125 may display one or more visual stimuli 175 simultaneously with one or more auditory stimuli 180 during a second time period. The application 125 may present the auditory stimuli 180 in whole or in part, such as the application 125 presenting a portion of the auditory stimuli 180 as described herein. In other cases, the application 125 may present the visual stimulus 175 simultaneously with another type of stimulus, such as a tactile stimulus. For example, the application 125 may present the first visual stimulus 175A while actuating the user device 110 to produce a vibration, buzzing, or other tactile stimulus for the user 210.

[0104] Application 125 can display visual stimuli 175A and 175B to guide user 210 to interact with the display. Visual stimuli 175A and 175B can include prompting user 210 to perform actions associated with stimuli 175A and 175B. The action can be or include an interaction 220 from user 210 related to the presentation of visual stimuli 175. Interaction 220 can include actions such as physical manipulation of user device 110, actuation of UI element 135, or viewing a video or image of visual stimuli 175. Interaction 220 can include an action of moving, tapping, sliding, nodding, shaking, tilting, or orienting user device 110 toward one side of user device 110. A side of user device 110 can refer to a boundary created by user interface 130 associated with user device 110, such as a side of a rectangular screen. One or more sides of the client can be associated with first visual stimulus 175A. In some embodiments, user 210 may perform interaction 220 to tilt user device 110 toward a side of user device 110 that corresponds to first visual stimulus 175A.

[0105] The interaction 220 may include an action such as touching, pressing, or otherwise actuating a UI element 135 of the user interface 130 associated with at least one of the first stimulus 175A or the second stimulus 175B. For example, the user 210 may provide one or more interactions 220 through the application 125 running on the user device 110 by actuating one or more UI elements 135 described herein. The user 210 may provide the interaction 220 by pressing a button associated with the application 125 and displayed via the user interface 130. In some embodiments, one or more first UI elements 135A may be associated with the first visual stimulus 175A, and one or more second UI elements 135B may be associated with the second visual stimulus 175B. In this illustrative example, the user 210 may provide the interaction 220 associated with the first visual stimulus 175A by touching, tilting, nodding, sliding, clicking, or otherwise engaging with the first UI element 135A. Similarly, the user 210 may provide the interaction 220 associated with the second visual stimulus 175B by engaging with the second UI element 135B.

[0106] Interaction 220 may include a series of actions performed sequentially or simultaneously. For example, interaction 220 may include manipulation of user device 110 and pressing of UI element 135. Manipulation of user device 110 and pressing of UI element 135 may be performed simultaneously as part of the same interaction 220, or performed sequentially as part of the same interaction 220. For example, user 210 may tilt user device 110 and press UI element 135 simultaneously, or user 210 may tilt user device 110 and then press UI element 135. Application 125 may present one or more visual stimuli 175 via user interface 130 to guide user 210 to perform interaction 220.

[0107] Presenting the stimulus via the user interface 130 may include presenting a first visual stimulus 175A with a first indicator to identify a first type of interaction 220 and presenting a second visual stimulus 175B with a second indicator to identify a second type of interaction 220. The indicator may include a visual presentation, such as text or a color. For example, the indicator may include a green highlight above the first visual stimulus 175A and a red highlight above the second visual stimulus 175B to indicate that the user 210 selected the first visual stimulus 175A. As another example, the indicator may include text that instructs the user 210 to perform the type of interaction 220, such as text that indicates "lean toward a positive stimulus" or "do not press a negative stimulus". Each visual stimulus presented by the application 125 may include an indicator. For example, the first visual stimulus 175A may include an indicator indicating "select me!" and the second visual stimulus 175B may include an indicator indicating "do not select me!"

[0108] In some embodiments, the indicator may include a timer. For example, the application 125 may use a timer as an indicator for presenting the visual stimulus 175 or a countdown to perform the interaction 220. In some embodiments, the indicator may generate an audio tone to prompt the user 210 to perform a specified interaction with the visual stimulus 175. For example, a first indicator may include a beep sound emitted from the user device 110 via the speaker and transducer 120 to indicate to the user 210 that they should interact with the first visual stimulus 175A. A second indicator may include a different (e.g., tone, duration, pitch, volume) beep sound emitted from the user device 110 via the speaker and transducer 120 to indicate to the user 210 that they should interact with the second visual stimulus 175B.

[0109] The application 125 may monitor at least one interaction 220 with the visual stimulus 175. The application 125 may monitor during the session in response to the presentation of the visual stimulus 175 or in response to receiving the interaction 220. The application 125 may monitor the receipt of the interaction 220. The application 125 may monitor the interaction 220 through the user interface 130 or through a sensor associated with the user device 110, etc. The application 125 may receive multiple interactions 220 during the session. For example, the application 125 may monitor a series of interactions 220 provided by the user 210 during the session. The application 125 may monitor and record information related to the received interactions 220. For example, the application 125 may monitor and record the time of the interaction 220, the duration of the interaction 220, the sequence of the interaction 220, the visual stimulus 175 associated with the interaction 220, and / or the delay time between the presentation of the visual stimulus 175 and the interaction 220, etc.

[0110] After the user 210 provides the interaction 220, the application 125 may generate at least one response 215. The response 215 may identify the interaction 220. The response 215 may include information about the interaction 220, such as the duration of the interaction 220, the time of the interaction 220, the visual stimulus 175 associated with the interaction 220, and / or the delay time between the presentation of the visual stimulus 175 and the interaction 220. The application 125 may generate the response 215 for transmission to the treatment management service 105. The response 215 may be in a format readable by the treatment management service, such as an electronic file readable by the treatment management service or a data packet readable by the treatment management service 105.

[0111] The response handler 150 may receive, identify, or otherwise detect a response 215 identifying an interaction 220. The response handler 150 may receive the response 215 from the application 125. The response handler 150 may receive the response 215 at predetermined time intervals or when an interaction 220 occurs during a treatment session. The response handler 150 may query or ping the application 125 for a response 215. The response handler 150 may receive multiple responses 215 during a time period. For example, the response handler 150 may receive a first response 215 indicating a first interaction 220 and a second response 215 indicating a second interaction 220.

[0112] Response handler 150 may store response 215 including interaction 220 in database 165. Response handler 150 may store information related to response 215, including the time of response 215, the action associated with interaction 220, the user profile 170 associated with response 215, and the visual stimulus 175 associated with response 215, etc. Response 215 may include or identify interaction 220 of user 210 with visual stimulus 175A or 175B. Response 215 may include task completion time. For example, response 215 may include that the user took 4 minutes to perform the action associated with the presentation of visual stimulus 175. Response 215 may include the total time for the treatment course to be completed, and may also include the start time of the treatment course and the completion time of the treatment course. Response 215 may include UI elements 135 that were interacted with during the presentation of visual stimulus 175. For example, response 215 may include a list of buttons, toggles, or other UI elements 135 that were selected by user 210 at a specified time during the presentation of visual stimulus 175. Response 215 may include other information, such as the location of user 210 when the treatment session was performed, such as geographic location, IP address, GPS location, or triangulation of cellular towers, etc. Response 215 may include measurements, such as measurements of time, location, or user data, etc.

[0113] Reference now Figure 3 , depicts a block diagram of a process 300 for generating auditory stimuli and playing the auditory stimuli to provide feedback. The process 300 may include or correspond to operations performed in the system 100 or the process 200. Under the process 300, the performance evaluator 155 may evaluate the response 215 to generate a response score 305. The feedback provider 160 may generate or select stimuli to provide feedback based on the response score 305. The treatment manager 140 may transmit the feedback to the application 125 for presentation to the user 210. The presentation of the visual stimulus 175 or the auditory stimulus 180 may be based on a previous visual stimulus 175, the user profile 170, the response 215, or a determination by the performance evaluator 155.

[0114] The performance evaluator 155 can calculate, generate or otherwise determine a response score 305 associated with the response 215 based on the interaction 220 with the visual stimulus 175. The response score 305 can indicate a level of correctness or conversely an error level associated with the response 215. A high response score 305 can be associated with a high level of correctness of selecting a visual stimulus 175 that is not related to a bias toward a disease. A low response score 305 can be associated with a low level of correctness (e.g., a high level of error) of selecting a visual stimulus 175 that is not related to a bias toward a disease. For example, a low response score 305 can indicate that the user 210 is more likely to select a first visual stimulus 175A that is associated with a negative stimulus or associated with the user's disease.

[0115] In determining the response score 305, the performance evaluator 155 can evaluate the response 215 based on the interaction 220. The response 215 may be correct, incorrect, or indeterminate. In some embodiments, the second visual stimulus 175B can be or include a stimulus that disassociates the user 210 from the condition. The user 210 can provide an interaction 220 related to disassociating the user 210 from the condition. For example, the user 210 can select the second visual stimulus 175B by the application 125 using the UI element 135. The user 210 can click, select, touch, or otherwise indicate a preference or selection for the second stimulus 175B through the interaction 220. The interaction 220 can indicate a selection or preference for the second visual stimulus 175B.

[0116] The performance evaluator 155 may identify or determine whether the user's response 215 is correct or incorrect based on the selected visual stimulus 175. If the interaction 220 corresponding to the response 215 is associated with the second visual stimulus 175B, the response 215 may be correct. If the response 215 is associated with the interaction 220 corresponding to the visual stimulus 175 disassociated from the condition, the performance evaluator 155 may determine that the response 215 is correct. The performance evaluator 155 may identify the response 215 including the interaction 220 as correct.

[0117] If the interaction 220 indicates a bias towards a positive or neutral stimulus, the performance evaluator 155 can identify the response 215 as correct. In some embodiments, the interaction 220 can be associated with a positive or neutral visual stimulus 175B. For example, the interaction 220 can include selecting a positive or neutral visual stimulus 175B. The positive or neutral stimulus 175B can include a positive or neutral image, text, or video, etc., which is not related to the user 210's condition or negative stimulus.

[0118] In contrast, if the interaction 220 associated with the response 215 is related to the first stimulus 175A associated with the condition, the performance evaluator 155 can identify the response 215 as incorrect. In some embodiments, the interaction 220 can be associated with a negative stimulus or a stimulus associated with the user's condition. For example, the interaction 220 can include selecting, directing, sliding, or tilting the user device 110 toward the negative visual stimulus 175A. The negative visual stimulus 175A can include a negative image, text, or video, etc. The negative visual stimulus 175A can be related to the condition of the user 210. For example, the negative visual stimulus 175A can include symptoms or emotions associated with the condition presented in text form, such as "pain" or "sadness."

[0119] Based on whether the response 215 is correct or incorrect, the performance evaluator 155 can calculate, generate, or otherwise evaluate the response score 305 of the user 210 based on the interaction 220 associated with the response 215. For example, the performance evaluator 155 can set the response score 305 of a given response 215 to "1" (when correct) and "-1" (when incorrect). In some embodiments, the performance evaluator 155 can identify the reaction time or correctness of the user 210 when selecting the visual stimulus 175. For example, the performance evaluator 155 can determine from the response 215 that the user 210 did not perform one or more actions indicated by the visual stimulus 175, or that the user 210 did not perform the action within a threshold time. The threshold time can correspond to or define the amount of time that the user 210 is expected to interact with one of the visual stimuli 175, and can range from 5 seconds to 10 minutes. Through this determination, the performance evaluator 155 can modify or adjust the response score 305 using the response time compared to the threshold time.

[0120] In some embodiments, the performance evaluator 155 may determine a degree of compliance of the user 210. The degree of compliance of the user 210 to the treatment session may be based on whether the response time of the user 210 to the presentation of the visual stimulus 175 is above or below a threshold time. For example, if the user 210 takes too long to provide the interaction 220, the user 210 may not be fully engaged or compliant with the treatment session. The degree of compliance of the user 210 may be based on the responses 215 provided by the user via the UI element 135 while participating in the treatment session. For example, if the user 210 presses a button presented by the application 125 at the wrong time during the treatment session or at a time when the button is not indicated to be pressed, the user 210 may have a low degree of compliance. Conversely, if the user 210 provides the correct interaction 220 within a threshold time period and performs a threshold number of actions based on the presented visual stimulus 175, the user 210 may have a high degree of compliance.

[0121] In some embodiments, the performance evaluator 155 may calculate, generate, or otherwise determine a response score 305 associated with the likelihood of overcoming the bias against negative stimuli. The likelihood of overcoming the bias against negative stimuli may refer to, include, or be associated with the probability that the user 210 will no longer pay attention to the stimulus associated with the condition. For example, if each time a negative stimulus is presented to the user 210 via the application 125, the user 210 successfully ignores the negative stimulus associated with the condition, then it can be said that the rate at which the user 210 overcomes the bias against negative stimuli is 100%. The likelihood of overcoming the bias against negative stimuli may include a threshold number of occurrences of the bias. For example, the performance evaluator 155 may not determine the likelihood until a threshold number of occurrences of negative stimuli have occurred, or until the user 210 has provided a threshold number of interactions 220. The performance evaluator 155 may determine the likelihood of overcoming the bias against negative stimuli based at least on the selection of UI elements 135 during the treatment session, the user profile 170, or the time of the treatment session, etc.

[0122] In some embodiments, the performance evaluator 155 may calculate, generate, or otherwise determine a response score 305 associated with an increase in mental acuity or a decrease in fatigue of the user 210. The performance evaluator 155 may determine the response score 305 based on a delay time between the presentation of the visual stimulus 175 and the receipt of the interaction 220. For example, the delay time between subsequent presentations of the visual stimulus 175 and the receipt of the interaction 220 may decrease. The decrease in the delay time may indicate an increase in mental acuity or a decrease in fatigue. The performance evaluator 155 may query the user 210 via the application 125 for an indication of the user's mental state. For example, the performance evaluator 155 may ask the user 210 via the user interface 130 a question asking the user 210 about his perceived level of mental acuity or fatigue. The performance evaluator 155 may generate a response score 305 associated with mental acuity or fatigue based on a response provided by the user 210 to the query.

[0123] At the same time, the feedback provider 160 can generate, output or otherwise generate feedback that the user 210 receives via the application 125 operating on the user interface 130. The feedback provider 160 can generate feedback based on at least the response score 305, the user profile 170, the response 215, or the historical stimulus presentation. The feedback can include text, video, or audio to be presented to the user 210 via the application 125 displayed by the user interface 130. The feedback can include one or more visual stimuli 175 or one or more auditory stimuli 180. The feedback can include the presentation of the response score 305. The feedback can display messages such as motivational messages, suggestions for improving performance, congratulatory messages, comforting messages, etc. In some embodiments, the feedback provider can generate feedback during a treatment session that the user 210 is performing.

[0124] Based on the response 215, the feedback provider 160 may generate an auditory stimulus 180A to include one or more parts 310A-N (hereinafter generally referred to as parts 310) for indicating feedback based on the response 215. The feedback provider 160 may generate the auditory stimulus 180 including the part 310 based on the response score 305 or the setting 205, etc. During the generation process, the feedback provider may generate an audio part 310 for the auditory stimulus 180. The part 310 may be a segment, a partition, a tone, or other such subset of the auditory stimulus 180. In some embodiments, the first part 310A of the auditory stimulus 180 may be audio within a first time period. For example, the first part 310A may be or include the first 2 seconds of the auditory stimulus 180. In some embodiments, the first part 310A of the auditory stimulus 180 may be the tone of the auditory stimulus 180. For example, the first part 310A may be or include a B flat pitch. In some embodiments, the first part 310A of the auditory stimulus 180 may be or include a music part, such as represented by a musical score. For example, the first portion 310A may be or include a violin sheet music or a soprano sheet music, while the entirety of the auditory stimulation 180 includes a complete sheet music, such as a violin sheet music, a soprano sheet music, and a piano sheet music.

[0125] In generating part 310 of the auditory stimulation 180, the feedback provider 160 may identify or access recorded sounds or music. The feedback provider 160 may extract, retrieve, or access from a library of pre-recorded sounds or music. The feedback provider 160 may generate recorded sounds through a microphone of the user device 110. The feedback provider 160 may generate the auditory stimulation 180 from pre-recorded or recorded sounds or music. The feedback provider 160 may generate tones through the user device 110 to generate the auditory stimulation 180, such as through a MIDI file associated with the auditory stimulation 180. The feedback provider 160 may generate an electronic sound file or electronic file for generating the sound, such as MIDI, MP3, or WAV, etc.

[0126] Based on whether the response 215 is correct, the feedback provider 160 may generate an auditory stimulus 180 to indicate feedback. The feedback may provide positive reinforcement or negative punishment to the user 210 depending on the response 215 from the user 210. When it is determined that the response 215 is correct, the feedback provider 160 may generate an auditory stimulus 180 to provide positive reinforcement. In order to provide positive reinforcement, the feedback provider 160 may insert, supplement or otherwise add at least one part 310 to the auditory stimulus 180. In some embodiments, the feedback provider 160 may generate or select a first part 310A indicating positive feedback to provide to the user 210 based on the response score 305 being equal to or higher than a threshold score. For example, if the treatment course response score 305 associated with the user 210 is higher than the threshold score, the feedback provider 160 may generate the first part 310A to play to the user to encourage the user or provide positive reinforcement. In some embodiments, the feedback provider 160 may change, adjust or otherwise modify (e.g., increase) the volume of the auditory stimulus 180 to provide positive reinforcement.

[0127] In contrast, when the response 215 is determined to be incorrect, the feedback provider 160 may generate the auditory stimulation 180 to provide a negative penalty. To provide the negative penalty, the feedback provider 160 may delete, subtract, or otherwise remove at least one portion 310 from the auditory stimulation 180. In some embodiments, if the response score 305 is below the threshold score, the feedback provider 160 may generate or select a second portion 310B indicating negative feedback to provide to the user 210. In some embodiments, the feedback provider 160 may change, adjust, or otherwise modify (e.g., reduce) the volume of the auditory stimulation 180 to provide the negative penalty. The generation of positive reinforcement or negative punishment may be used in conjunction with the ABMT session to reduce the user's bias toward negative stimuli associated with their condition.

[0128] In some embodiments, if the response 215 is correct or associated with a correct interaction 220, the feedback provider 160 may provide a preferred portion or additional portions to provide positive reinforcement to the user 210 when correcting the deviation of the negative stimulus associated with the condition. The user 210 may select or indicate the preferred portion 310 or the auditory stimulus 180 as one or more of the settings 205. The feedback provider 160 may provide the preferred portion 310A in response to receiving the response 215 indicating that the user 210 performed a correct interaction 220 (e.g., an interaction 220 associated with a positive visual stimulus 175B or not associated with the condition). The feedback provider 160 may provide the preferred portion 310A in response to the response score 305 being equal to or above a threshold score.

[0129] In some embodiments, if the response 215 is incorrect or associated with an incorrect interaction 220, the feedback provider 160 may provide a non-preferred portion to be included in the auditory stimulation 180. The feedback provider 160 may provide a non-preferred portion to provide a negative penalty to the user 210 to correct the deviation of the negative stimulation associated with the condition. The user 210 may select or indicate the non-preferred portion 310 or the auditory stimulation 180 as one or more of the settings 205. The feedback provider 160 may provide a non-preferred portion 310B in response to receiving a response 215 indicating that the user 210 has performed an incorrect interaction 220 (e.g., an interaction 220 associated with a negative visual stimulus 175A or a condition). In this manner, the feedback provider 160 may provide a negative penalty to the user 210 when the user 210 provides an incorrect response or the response score 305 is below a score threshold.

[0130] By continuously responding, the feedback provider 160 can send, communicate, or otherwise provide feedback to the user 210 by adding or removing different portions 310 of the auditory stimulus 180. After receiving an incorrect response, the feedback provider 160 can remove the preferred portion 310A from the playback to the user 210. Similarly, in response to a correct response 215 or a response score 305 equal to or above a score threshold, the feedback provider 160 can provide the preferred portion 310A, remove the non-preferred portion 310B, or a combination of both. When the user 210 provides more correct responses 215, or when the response score 305 increases, the feedback provider 160 can provide additional preferred portions 310 to play to the user 210. The additional preferred portions 310 can be played simultaneously. Playing the preferred portions 310 simultaneously can create a song, such as the preferred song indicated by the user 210 in the settings 205. In this way, the feedback provider 160 can provide the auditory stimulus 180A including the preferred portion for positive reinforcement. Similarly, the feedback provider 160 can add the non-preferred portion 310 to the auditory stimulation 180A to provide a negative penalty in response to an incorrect response 215 or a response score 305 below a threshold score. In this way, a non-preferred song can be presented to the user 210 based on the response 215 to provide a negative penalty.

[0131] In some embodiments, the feedback provider 160 may generate an auditory stimulus 180 to be played to the left and right ears of the user 210. The auditory stimulus 180 may include stereo audio, with different parts 310 provided to the left and right ears. The feedback provider 160 may identify or select different parts 310 to be played to each ear of the user 210. In some embodiments, the feedback provider 160 may select parts 310 to provide binaural perception to the user 210. For example, the feedback provider 160 may generate a first part 310A including a tone with a frequency of 415 Hz and a second part 310B including a tone with a frequency of 400 Hz to provide binaural beats. Binaural beats may be provided by the auditory stimulus 180 to address fatigue associated with a condition in the user 210 (e.g., multiple sclerosis or cancer). The feedback provider 160 may provide the first part 310A to the left ear of the user 210 using a first speaker, and provide the second part 310B to the right ear of the user 210 using a second speaker.

[0132] In some embodiments, the feedback provider 160 may generate the auditory stimulus 180 based on the user profile 170. The user profile 170 may include a historical association between previously presented auditory stimulus 180 and previous responses 215. For example, the user profile 170 may indicate that the auditory stimulus 180A has ever produced an increased response score 305 for the user 210 during the session. For example, the user profile 170 may indicate that the auditory stimulus 180A has ever been associated with an incorrect response 215.

[0133] In some embodiments, the feedback provider 160 may generate the auditory stimulus 180 based on the user settings 205. The user settings 205 may include characteristics of the auditory stimulus 180. The user 210 may provide preferred or non-preferred auditory stimulus 180 via the application 125. For example, the user 210 may indicate a preferred song or a non-preferred instrument. The feedback provider 160 may generate the auditory stimulus 180 for positive reinforcement feedback from the preferred auditory stimulus 180 provided by the user 210 in the settings 205. Similarly, the feedback provider 160 may generate the auditory stimulus 180 for negative punishment feedback from the non-preferred auditory stimulus 180 provided by the user 210 in the settings 205.

[0134] In some embodiments, feedback provider 160 may provide one or more of portions 310 at least partially concurrently with presentation of visual stimulus 175 by stimulus selector 145. Feedback provider 160 may provide one or more of portions 310 at least partially concurrently with presentation of visual stimulus 175. For example, feedback provider 160 may provide first portion 310A via a speaker coupled to user device 110 while application 125 presents visual stimulus 175. Feedback provider 160 may provide one or more portions 310 in association with visual stimulus 175. For example, first visual stimulus 175A may correspond to first auditory stimulus 180.

[0135] After generation, the feedback provider 160 may send, transmit, or otherwise provide the auditory stimulus 180 to the application 125. The auditory stimulus 180 may be provided to the application 125 on the user device 110 in the form of an audio file (e.g., MPEG, FLAC, WAV, or WMA format) or as part of an audio stream (e.g., MP3, AAC, or OGG format). In some embodiments, the feedback provider 160 may send, transmit, or otherwise present visual feedback for presentation via the application 125 during the performance of the treatment session or after receiving the response 215. For example, the response score 305 may indicate that the performance of the user 210 in the treatment session is below a threshold correctness. The feedback provider 160 may generate feedback associated with the low response score 305, such as an incentive message including the response score 305. The feedback provider 160 may transmit the auditory stimulus 180 as part of the feedback. The feedback provider 160 may present the feedback including the auditory stimulus 180 via the application 125 operating on the user device 110.

[0136] The application 125 may present, generate, or otherwise play the auditory stimulus 180 via one or more transducers 120 on the user device 110. The application 125 may generate a signal, a data packet, an electronic file, etc., to be played via one or more speakers coupled to the user device 110. The application 125 may transmit a signal including instructions for playing the auditory stimulus 180 to the transducer 120. The application 125 may play the auditory stimulus 180 via the transducer 120. The transducer 120 may include or be coupled with one or more speakers. In some embodiments, the application 125 may provide the auditory stimulus 180 to the transducer 120 for playback via one or more speakers by generating a signal including the auditory stimulus 180 for reception by the transducer 120. The transducer 120 may convert the signal into mechanical vibrations via the speaker to generate the sound of the auditory stimulus 180 for playback to the user 210.

[0137] Application 125 can provide stereo audio of auditory stimulation 180 to different ears of user 210. For example, transducer 120 can provide a first portion 310A of auditory stimulation 180 to a first ear and a second portion 310B of auditory stimulation 180 to a second ear via two speakers. Transducer 120 can be coupled to one or more speakers or configured to actuate one or more speakers. The signal including auditory stimulation 180 can instruct transducer 120 to play first portion 310A to a first speaker and second portion 310B to a second speaker.

[0138] For the next stimulation delivery (e.g., in a subsequent round or session), the session manager 140 may identify or select a difficulty level associated with the visual stimulations 175'A and 175'B (referred to herein as visual stimulations 175'). The level may be an assigned level, score, or descriptor to determine the presentation of the visual stimulations 175' by the stimulation selector 145. For example, the level may correspond to "easy," "medium," or "difficult," or the level may correspond to a numerical value, a title, or a time period, etc. The level may correspond to a time period. For example, a first level may include a first time period, and a second level may include a second time period. The level may define one or more features of the presentation of the visual stimulations 175'. The feature may guide the presentation of the stimulations 175'. For example, the feature may be a visual feature defined by a level that affects the display of the visual stimulations or affects the selection of the visual stimulations. For example, the first visual stimulation 175'A may correspond to an "easy" level and thereby have a different presentation than the first visual stimulation 175'A corresponding to a "difficult" level. The presentation of the visual stimulation 175' may change depending on the assigned level. Figure 5 A set of visual stimuli in the interface shown in may correspond to an easier level, while Figure 6 A set of visual stimuli in the interface shown in may correspond to a more difficult level.

[0139] The session manager 140 may use reaction time, response score 305, or correctness of response 215, etc. to identify or select a level of visual stimulation 175'. Reaction time may correspond to a delay between presentation of visual stimulation 175' and receipt of response 215 or performance of interaction 220. For example, the session manager 140 may select a higher or more difficult level corresponding to a reaction time below a threshold level. If the correctness of a previous response 215 is below a threshold or specified correctness, the session manager 140 may select a level to include more or fewer stimulation 175'.

[0140] In some embodiments, the session manager 140 may select a level associated with the visual stimulus 175' based on the response score 305. For example, if the response score 305 is above a threshold, the session manager 140 may select a more difficult level associated with the visual stimulus 175'. For example, if the response score 305 is below a threshold, the session manager 140 may select an easier level associated with the visual stimulus 175'. In some embodiments, the performance evaluator 155 may select a level based on reaction time and the correctness of any previous responses 215. In this way, more difficult visual stimuli 175' may be presented to the user 210 to further facilitate the user's progress in the ABMT session.

[0141] In some embodiments, the treatment manager 140 may select a level based on the level of compliance of the user 210. If the user 210 has a high level of compliance with the treatment, the treatment manager 140 may select a level for the subsequent visual stimulation that is higher than the level associated with the previously presented visual stimulation. Conversely, if the user 210 exhibited a low level of compliance with that level in the previously presented visual stimulation 175' during the treatment, the treatment manager 140 may select the same level for the subsequent visual stimulation. The treatment manager 140 may use any combination of the visual stimulation 175', the user profile 170, the response 215, the response score 305, or the interaction 220 to determine the level to select or modify the stimulation 175'.

[0142] In some embodiments, the session manager 140 may select a level based on a previous presentation of the visual stimulus 175'. The session manager 140 may select a level based on a previous presentation of a visual, auditory, or tactile stimulus, etc. For example, the session manager 140 may select a level based on a user's failure to provide a correct interaction 220 for a previously presented visual stimulus 175'. The session manager 140 may select a level based on a response score 305. For example, if the response score 305 associated with the session is below a threshold score, the session manager 140 may assign an easier level to a subsequent presentation of the visual stimulus 175'.

[0143] By determining the level, the stimulus selector 145 can modify the presentation of the visual stimulus 175' based on the level of the visual stimulus 175'. The stimulus selector 145 can modify the presentation of the first stimulus 175'A, the second stimulus 175'B, the subsequent visual stimulus, or a combination thereof. The stimulus selector 145 can provide instructions to the application 125 to display the visual stimulus 175'. The stimulus selector 145 or the application 125 can modify the presentation of the visual stimulus 175' during the presentation of the visual stimulus 175' or after the presentation of the visual stimulus 175'. For example, the stimulus selector 145 can modify the first visual stimulus 175'A when it is presented on the user interface 130 by the application 125. For example, the stimulus selector 145 can modify the presentation of the subsequent visual stimulus 175' during the same treatment session or a subsequent treatment session.

[0144] The stimulus selector 145 may modify the visual stimulus 175' using one or more visual features associated with the assigned level. For example, the first level "easy" may include a first feature indicating the opacity of the first visual stimulus 175'A. The second level "difficult" may include a second feature indicating the opacity of the second visual stimulus 175'B. In some embodiments, the opacity associated with the second level may be more difficult for the user 210 to recognize or distinguish than the opacity associated with the first level. That is, the first stimulus 175'A with the "easy" level may be more recognizable, easier to read, or easier to distinguish than the second stimulus 175'B with the "difficult" level. In this way, one or more overlapping visual stimuli associated with the "easy" level may be easier to distinguish by the user 210 than one or more overlapping visual stimuli associated with the "difficult" level.

[0145] The interaction 220 with the visual stimulus 175' can iteratively cause the stimulus selector 145 to modify the presentation of the visual stimulus 175' based on the response score 305 and the level determined by the treatment manager 140. As an illustrative example, the user 210 can provide an interaction 220 of tilting the user device 110 in response to the visual stimulus 175'. When the user 210 tilts the user device 110 toward the words associated with the first visual stimulus 175'A and away from the words associated with the second visual stimulus 175'B, the words associated with the first visual stimulus 175'A can become more prominent or opaque, while the words associated with the second visual stimulus 175'B can become less prominent or visible. The visual stimulus 175' can change in other ways. For example, in response to the treatment manager 140 changing the level feature, the image or word associated with the visual stimulus 175' can change color, size, font, opacity, position or alignment, etc. In this manner, depending on the responses 215 provided by the user 210 , the presentation of the visual stimuli 175 ′ may be iteratively changed.

[0146] The treatment course management service 105 may repeat the above functions (e.g., processes 200 and 300) over multiple treatment courses. The number of treatment courses may be a set number of days, weeks, or even years, or may have no clear endpoint. By iteratively providing visual and auditory stimulation based at least on the response score 305, the user profile 170, the response 215, or the settings 205, the user 210 may be able to receive content to help alleviate the bias to the stimulation associated with the condition. This may alleviate the symptoms faced by the user 210, even with a condition that may prevent the user from seeking treatment or even physically visiting the user device 110. In addition, by participating in the treatment course when presented through the user interface 130 of the application 125, the quality of the human-computer interaction (HCI) between the user 210 and the user device 110 may be improved.

[0147] Because the visual stimuli 175' are more relevant to the user's condition (e.g., cancer, MS, other chronic conditions) and are associated with symptoms of attention bias caused by the condition, the user 210 may be more likely to engage in a treatment session when presented via the user device 110. Compared to sending invalid or irrelevant visual stimuli 175', this can reduce unnecessary consumption of computing resources (e.g., processing and memory) of the service and user device 110, and reduce network bandwidth usage. In addition, in the context of digital therapeutic applications, personalized selection of visual stimuli 175' can result in the provision of user-specific interventions to improve the subject's compliance with treatment. This can not only improve compliance with therapeutic interventions, but also potentially improve the user's condition.

[0148] Reference now Figure 4 , depicting a flow chart of a method 400 for presenting multimodal stimulation to address symptoms associated with a condition. The method 400 may be implemented or performed using any of the components detailed herein, such as the therapy management service 105 and the user device 110, or any combination thereof. Under the method 400, a service (e.g., therapy management service 105) may identify a set of visual stimulations (405). The service may provide the set of visual stimulations to a client (e.g., user device 110) (410). The client may present the set of visual stimulations using a display device of the client (415). After the stimulations are presented, an application operating on the client may detect a response to one or more sets of visual stimulations (425). The service may receive a response (420). After receiving the response, the service may determine whether the response is correct (430). If the response is incorrect, the service may remove a portion from the auditory stimulation (435). If the response is correct, the service may add a portion to the auditory stimulation (440). The service may provide the auditory stimulation (445). The client may play the auditory stimulation to provide feedback to the user (450).

[0149] Reference now Figure 5 , depicting a screenshot of an example set 500 of interfaces for presenting multimodal stimulation to address symptoms associated with a condition. The set 500 may include example user interfaces 505, 510, or 515 and a set of instructions 520. The set 500 may include an application 125 installed thereon. The application 125 may be presented on a user interface or display, such as a user interface 130 of a user device 110. In some embodiments, the application 125 may be presented as a game, image, video, or interactive application 125 on the user device 110. A user (e.g., user 210) may interact with the user interfaces 505-515. The user interfaces 505-515 may include one or more user elements, such as UI elements 135, to accept input from the user 210 using at least one hand 525. The user 210 may press the screen of the user device 110 to enter input, may manipulate or rotate the user device 110 to record (via detection of an accelerometer, gyroscope, or other sensor associated with the user device 110) the movement of the user device 110.

[0150] The user 210 may manipulate the user device 110 in accordance with the instructions 520. The instructions 520 may be presented on the user device 110 as part of the application 125 running thereon. By the user 210 manipulating the user device 110 in accordance with the instructions 520, each user interface 505-515 may be displayed to the user 210 via the user device 110. For example, by tilting the user device 110 to the left of the user, the user interface 505 may be displayed in which the word "love" is more prominent than the word "pain". Conversely, the user 210 tilting the user device 110 to the right of the user may cause the application 125 to more prominently display the word "pain" rather than "love". By keeping the user device 110 in a neutral position, the client device 110 may display the user interface 510 in which the words "love" and "pain" are equally opaque. In this way, by the user 210 providing the interaction 220 of tilting the phone, different stimuli "love" and "pain" may present different visual features.

[0151] Reference now Figure 6, depicts a screenshot of an example group 600 of user interfaces for presenting multimodal stimulation to address symptoms associated with a condition. The group 600 may include example user interfaces 605, 610, or 615. The group 600 may include an application 125 installed thereon. The application 125 may be presented on a user interface or display, such as the user interface 130 of the user device 110. In some embodiments, the application 125 may be presented as a game, image, video, or interactive application 125 on the user device 110. A user (e.g., user 210) may interact with the user interfaces 605-615. The user interfaces 605-615 may include one or more user elements, such as UI elements 135, to accept input from the user 210. The user 210 may press the screen of the user device 110 to input, may manipulate or rotate the user device 110 to record (via detection of an accelerometer, gyroscope, or other sensor associated with the user device 110) the movement of the user device 110.

[0152] The user interfaces 605-615 may correspond to difficulty levels. The user interface 605 may correspond to an "easy" difficulty level. The user interface 610 may correspond to a "medium" difficulty level. The user interface 615 may correspond to a "hard" difficulty level. The treatment manager 140 may determine different difficulty levels associated with the user interfaces 605-615 according to the systems and methods described herein. In this illustrative example, increasing difficulty levels are associated with visual stimuli that may be more difficult for the user 210 to interpret. For example, the user interface 615 depicts two stimuli ("love" and "pain") with similar fonts, colors, and sizes, making it harder or more difficult for the user 210 to distinguish between the two visual stimuli. Similarly, the user interface 605 depicts the same two visual stimuli, but in different fonts, sizes, and colors, making it easier for the user 210 to distinguish between the stimuli.

[0153] Because the application operates on the subject's mobile device, or at least on a mobile device that the subject can easily and reliably access, such as according to a predetermined frequency (e.g., once a day), the application provides real-time support to the subject. For example, upon receiving a request from the user to initiate a treatment course, the application starts the treatment course in real time (i.e., at least within a few milliseconds after receiving the request). Such timely guidance cannot be achieved via an in-person visit, phone call, video conference, or even text message between the user and the healthcare provider who is performing a multiple sclerosis or cancer examination for the user. In this way, the application is able to provide and customize tasks for the user based on the user's performance. This can create an iteratively improved service for the user, where the overall bandwidth and data communication are minimized due to the increasing utility of each task.

[0154] B. Methods of Alleviating Symptoms Associated with Attention Bias in Users Suffering from Conditions Affecting Cognitive Function

[0155] Reference now Figure 7 , depicts a flow chart of a method 700 for reducing symptoms associated with attention bias of a user having a condition that affects cognitive functioning that is desired. The method 700 may be performed by any component or participant described herein, such as the therapy management service 105 and the user device 110, among others. The method 700 may be used in conjunction with any of the functions or actions described herein in Section A, Example 1 of Section B, or Appendix A. Briefly summarized, the method 700 may include obtaining a baseline metric (705). The method 700 may include selecting a visual stimulus for a therapy session (710). The method 700 may include presenting the set of visual stimuli (715). The method 700 may include playing an auditory stimulus (720). The method 700 may include obtaining a therapy session metric (725). The method 700 may include determining whether to continue (730). The method 700 may include determining whether the therapy session metric is improved over the baseline metric (735). The method 700 may include determining that symptom reduction has occurred when it is determined that the therapy session metric is improved over the baseline metric (740). Method 700 may include determining that symptom reduction has not occurred when it is determined that the treatment course indicator has not improved over the baseline indicator (745).

[0156] In more detail, method 700 may include determining, identifying, or otherwise obtaining baseline indicators (705) prior to any treatment course. The baseline indicators may be associated with a user (e.g., user 210) who is at risk for, diagnosed with, or otherwise has a condition. In some cases, the user's condition may include multiple sclerosis (MS), with or without mobility impairment due to muscle weakness or cramps, fatigue, or loss of balance. A user with multiple sclerosis may be in a relapsing state and not use steroids for at least a period of time (e.g., ranging between 3 days and 3 weeks) prior to the treatment course. In other cases, the user's condition may include cancer, such as lung cancer, colorectal cancer, skin cancer, breast cancer, ovarian cancer, leukemia, pancreatic cancer, or gastric cancer, etc. In other cases, the disease may include a psychogenic chronic pain disease, including but not limited to fibromyalgia, rheumatoid arthritis, and IBS.

[0157] "Cancer", also referred to herein as "tumor", is a medical term for the uncontrolled division of abnormal cells in a part of the body, benign or malignant. In one embodiment, cancer refers to a malignant tumor, which is a large class of diseases involving uncontrolled cell division and growth and invasion of nearby parts of the body. Non-limiting examples of cancer include carcinomas, sarcomas, leukemias, and lymphomas, such as colon cancer, colorectal cancer, rectal cancer, gastric cancer, esophageal cancer, head and neck cancer, breast cancer, brain cancer, lung cancer, gastric cancer, liver cancer, gallbladder cancer, or pancreatic cancer. In one embodiment, the term "cancer" refers to a solid tumor, which is an abnormal tissue mass that does not usually contain a cyst or liquid area, including but not limited to sarcomas, carcinomas, and certain lymphomas (such as non-Hodgkin's lymphoma). In another embodiment, the term "cancer" refers to liquid cancer, i.e., cancer present in body fluids (e.g., blood and bone marrow), such as leukemia (blood cancer) and certain lymphomas.

[0158] Additionally or alternatively, cancer can refer to localized cancer (which is an aggressive malignant cancer that is completely confined to the organ or tissue where the cancer started), metastatic cancer (referring to a cancer that spreads from its site of origin to another part of the body), non-metastatic cancer, primary cancer (a term used to describe the initial cancer experienced by a subject), secondary cancer (referring to the metastasis of a second cancer that is unrelated to the primary cancer or the original cancer), advanced cancer, unresectable cancer, or recurrent cancer. As used herein, advanced cancer refers to a cancer that progresses after receiving one or more of the following treatments: first-line therapy, second-line therapy, or third-line therapy.

[0159] The user may be taking medication to address the condition, at least partially in sync with the course of treatment. For multiple sclerosis, the drug may include beta interferon, glatiramer, cladribine, dimethyl fumarate, deloximetate fumarate, fingolimod, monomethyl fumarate, ofatumumab, ozanimod, ponamod, sipomod, teriflunomide, alemtuzumab, mitoxantrone or natalizumab, etc. For cancer, the user may complete chemotherapy, radiotherapy or immunotherapy (for example, ranging from 3 days to 18 months) at least for a period of time before the course of treatment. The user can have any demographics or characteristics, such as age (for example, adults (over 18 years old), late adolescents (between 18-24 years old)) or gender (for example, male, female or non-binary gender), etc.

[0160] Because the condition affects the user's cognitive function, the user may have one or more symptoms associated with attention bias. Symptoms associated with the condition may include chronic pain, fatigue, and mood (e.g., depression), etc. Cognitive functions affected by the condition may include cognitive impairment of chronic neurological diseases and multiple sclerosis, as well as cognitive impairment caused by cancer or cancer treatment, etc. Attention bias may include, for example, avoiding stimuli or activities associated with the symptom; anxiety caused by stimuli associated with the symptom, multiple sclerosis, or cancer; or depression, etc.

[0161] Before any course of treatment is provided to a user via a digital therapy application (e.g., application 125 or study application (StudyApp) described herein), a baseline measurement can be obtained (e.g., by a computing system, such as a user device 110 or course management service 105 or a clinician separate from the computing system). The baseline measurement can identify or indicate the severity of symptoms associated with attention bias due to a condition that affects the user's cognitive function. Certain types of indicators can be used for both multiple sclerosis and cancer. For both conditions, baseline indicators can include, for example, Patient Reported Outcome Measurement Information System (PROMIS) values ​​(e.g., PROMIS-29), Brief Pain Inventory (BPI) values, Pain Catastrophizing Scale (PCS) values, Global Change Rating (GRC) values, User Experience Questionnaire values, and computerized assessment values, etc. Certain types of indicators can be used for one of multiple sclerosis or cancer. Baseline indicators for multiple sclerosis may include symbolic digital modality testing (SDMT) values, while baseline indicators for cancer may include functional assessment of cancer therapy-cognitive function (FACT-Cog) values.

[0162] Method 700 may include identifying or selecting a set of visual stimuli (e.g., visual stimuli 175) for a treatment session (710). The computing system may select the set of visual stimuli based on settings (e.g., settings 205, which identifies a word list from which visual stimuli are identified) of a user profile of the user (e.g., user profile 170) and previous treatment sessions (if any treatment sessions have been previously provided to the user). The visual stimuli may include text, images, or videos, and may be selected based on attention bias modification training (ABMT). The set of visual stimuli may include at least one visual stimulus associated with a condition (or a symptom associated with a condition) and at least one other visual stimulus. The first visual stimulus (e.g., first visual stimulus 175A) may be, for example, a visual stimulus associated with pain, a visual stimulus associated with a threat, a visual stimulus associated with a condition, or other negatively associated visual stimuli, etc. The second visual stimulus (e.g., second visual stimulus 175B) may be a neutral visual stimulus or a positive visual stimulus, etc.

[0163] Method 700 may include displaying, rendering, or otherwise presenting the set of visual stimuli (715). By selecting the set of visual stimuli, the computing system may present a first visual stimulus that at least partially overlaps the second visual stimulus on the display. The user may be prompted or instructed (e.g., via a display) to perform at least one interaction (e.g., interaction 220) with one of the first visual stimulus or the second visual stimulus presented to the user. For example, the computing system may display an indicator that identifies which side of the display to turn the device toward to select the visual stimulus. The computing system may monitor the interaction with one of the visual stimuli. The interaction may include an orientation (e.g., tilt or movement) of the device display toward a side corresponding to one of the visual stimuli or a touch (e.g., a touch or click event) with one of the visual stimuli, etc. After detection, the computing system may identify (e.g., from response 215) the visual stimulus of the set with which the user performs the interaction.

[0164] Method 700 may include presenting, outputting, or otherwise playing an auditory stimulus (e.g., auditory stimulus 180) (720). The computing system may generate the auditory stimulus to provide feedback to the user based on the response. The computing system may determine whether the response is correct based on the visual stimulus that the user performs the interaction. When the response identifies that the interaction is with a first visual stimulus associated with the disease, the computing system may determine that the response is incorrect. When the response is incorrect, the computing system may generate the auditory stimulus to provide a negative penalty (e.g., by removing one or more portions 310). When the response identifies that the interaction is with a second visual stimulus, the computing system may determine that the response is correct. When the response is correct, the computing system may generate the auditory stimulus to provide positive reinforcement (e.g., by adding one or more portions 310). In some embodiments, the computing system may provide the auditory stimulus at least partially simultaneously with the presentation of the set of visual stimuli. The auditory stimulus may include stereo audio, and the audio played to one ear of the user is different from the audio played to the other ear of the same user to achieve binaural perception. In response to the binaural beats in the auditory stimulus, the user may experience an improvement in the fatigue symptoms associated with the disease.

[0165] Method 700 may include determining, identifying, or otherwise obtaining a course of treatment indicator (725). After providing at least one course of treatment to a user via a digital therapeutic application, the course of treatment indicator may be obtained (e.g., by a computing system (such as user device 110 or course of treatment management service 105) or a clinician separate from the computing system). The course of treatment indicator may identify or indicate the severity of symptoms associated with attention bias due to a condition that affects the user's cognitive function. The course of treatment indicator may be of the same type of measurement as the baseline indicator. Certain types of indicators may be used for multiple sclerosis and cancer. For both conditions, baseline indicators may include, for example, Patient Reported Outcomes Measurement Information System (PROMIS) values ​​(e.g., PROMIS-29), Brief Pain Inventory (BPI) values, Pain Catastrophizing Scale (PCS) values, Global Rating of Change (GRC) values, User Experience Questionnaire values, and computerized assessment values, among others. Certain types of indicators may be used for one of multiple sclerosis or cancer. Baseline measures for multiple sclerosis may include symbol digit modalities test (SDMT) values, while baseline measures for cancer may include Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) values.

[0166] Method 700 may include determining whether to continue (730). The determination may be based on a set length of the trial (e.g., days, weeks, or years) or a set number of sessions to be provided to the user. For example, the set number of time instances may range between 2 and 8 weeks relative to obtaining the baseline metric. When the amount of time from obtaining the baseline metric exceeds the set length, the determination may be to stop providing additional sessions. Method 700 may repeat from step 710, selecting a set of visual stimuli for the next session. The presentation of visual stimuli for subsequent sessions may be changed, altered, or otherwise modified based on responses in the current session. In some embodiments, the computing system may determine, identify, or otherwise select a difficulty level based on responses from the user in the current or previous session. By selection, the computing system may modify the visual features (e.g., opacity or degree of overlap) of the set of visual stimuli based on the difficulty level of the next session.

[0167] Method 700 may include identifying or determining whether a treatment course indicator is improved over a baseline indicator (735). The improvement may correspond to an improvement or reduction in a symptom associated with an attention bias due to a condition that affects the user's cognitive function. When the treatment course indicator increases by a first predetermined margin compared to the baseline indicator, or when the treatment course indicator decreases by a second predetermined margin compared to the baseline indicator, it can be determined that an improvement has occurred (e.g., determined by a computing system or a clinician examining the user). The margin may identify or define a difference in value between the baseline indicator and the treatment course indicator to determine that the user exhibits a symptom or a reduction in its severity. Whether the improvement is shown by an increase or a decrease may depend on the type of indicator used to measure the user relative to the condition or symptom. The margin may also depend on the type of indicator used, and may generally correspond to a difference in value that shows a clinician or user a significant difference in the symptom, or a statistically significant result of a difference in value between the baseline and treatment course indicators.

[0168] Method 700 may include determining that symptom relief has occurred (740) when it is determined that the treatment course indicator has improved by a first or second predetermined margin over the baseline indicator. In some embodiments, symptom relief may occur when the treatment course PROMIS value increases by a first predetermined margin from the baseline PROMIS value. In some embodiments, symptom relief may occur when the treatment course BPI value decreases by a first predetermined margin from the baseline BPI. In some embodiments, symptom relief may occur when the treatment course PCS value decreases by a first predetermined margin from the baseline PCS. In some embodiments, symptom relief may occur for a computerized cognitive assessment value when the treatment course indicator value increases by a second predetermined margin from the baseline indicator value. In some embodiments, symptom relief may occur for a user with multiple sclerosis when the treatment course SDMT value increases by a second predetermined margin from the baseline SDMT value. In some embodiments, symptom relief may occur for a user with cancer when the treatment course FACT-Cog value increases by a second predetermined margin from the baseline FACT-Cog value. In some embodiments, symptom relief may occur after a FACIT-Fatigue, FACT-G, and / or HADS treatment course.

[0169] Method 700 may include determining that symptom relief has not occurred (745) when it is determined that the treatment course indicator has not improved by a first or second predetermined margin over the baseline indicator. In some embodiments, symptom relief may not have occurred when the treatment course PROMIS value has not increased by a first predetermined margin from the baseline PROMIS value. In some embodiments, symptom relief may not have occurred when the treatment course BPI value has not decreased by a first predetermined margin from the baseline BPI. In some embodiments, symptom relief may not have occurred when the treatment course PCS value has not decreased by a first predetermined margin from the baseline PCS. In some embodiments, for a computerized cognitive assessment value, symptom relief may not have occurred when the treatment course indicator value has not increased by a second predetermined margin from the baseline indicator value. In some embodiments, for a user with multiple sclerosis, symptom relief may not have occurred when the treatment course SDMT value has not increased by a second predetermined margin from the baseline SDMT value. In some embodiments, for a user with cancer, symptom relief may not have occurred when the treatment course FACT-Cog value has not increased by a second predetermined margin from the baseline FACT-Cog value.

[0170] Example 1: A randomized, controlled, exploratory basket study to evaluate multimodal multistable bias modification for normalization of attentional bias and cognitive improvement in adults with multiple sclerosis, breast cancer, and lung cancer 1. Summary

[0171] Indications: Multiple sclerosis (MS); breast cancer and lung cancer

[0172] Introduction and Research Rationale: CT-100 (e.g., Application 125) is a platform that provides interactive software-based therapeutic components that can be used as part of multimodal treatments in future software-based prescription digital therapeutics. One class of CT-100 components is Digital Neural Activation and Modulation (DiNaMo TM ) components. DiNaMo components target key neural systems (including but not limited to systems related to sensation, perception, emotion, pain, attention, cognitive control, social interaction, and self-processing) to optimally improve participant health.

[0173] Multimodal multistable bias modification (or multimodal, multistable bias modification or MMBM) is a targeted cognitive training that uses the principles of multimodal neural enriched tasks (M-NET) in order to reduce symptoms associated with multiple sclerosis (MS) and cancer. Biasing attention toward or away from certain stimuli can exacerbate a variety of symptoms across many different indications. For example, in chronic pain conditions, patients pay increased attention to pain-related stimuli, which can lead to hypersensitization. Similarly, hypersensitization to threat-related stimuli can exacerbate anxiety.

[0174] In multimodal multistable bias modification, users are trained to redirect their attention to positive stimuli, rather than stimuli that may cause them distress, such as pain or threat-related stimuli. This is done in a novel format, utilizing multistable perception. Visual multistable perception in the form of monocular rivalry is used to implicitly retrain the attention bias. Meanwhile, auditory multistable perception in the form of binaural beats is used both to target fatigue symptoms and to work synergistically to enhance the attention bias component.

[0175] Objectives: To assess trends in effects on pain interference, cognition, and related outcomes (attention bias and global quality of life [QoL]) compared with a digital control group.

[0176] Evaluation Criteria

[0177] Exploratory End Points

[0178] ●Change from baseline to week 4 in quality of life as measured by PROMIS-29+2 (Patient-Reported Outcomes Measurement Information System)

[0179] Change from baseline to week 3 in pain severity and pain interference as measured by the Brief Pain Inventory (BPI)

[0180] Change from baseline to week 4 in the Pain Catastrophizing Scale (PCS)

[0181] ● Change from baseline to Week 4 in indication-specific measures: Symbol Digit Modalities Test (SDMT) for MS; Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) for cancer

[0182] ●Change from baseline to week 4 on computerized cognitive assessment

[0183] ●Proportion of participants with improvement at Week 4 as measured by the Global Rating of Change (GRC) score

[0184] ● Engagement with the research app as measured by metrics such as daily app usage and daily time spent in the research app

[0185] ● Experience with the research application as assessed through a user experience survey and optional qualitative interviews that may be conducted after the treatment period

[0186] Study Design

[0187] Reference now Figure 8 , depicts the timeline of a randomized, controlled, exploratory basket study to evaluate multimodal multistable bias modification for normalization of attentional biases and cognitive improvement in adults with multiple sclerosis, breast cancer, and lung cancer.

[0188] Screening period (Day -14 to Day -1)

[0189] ● Participant screening for up to 14 days, including electronic informed consent. During this screening period, assessments are performed remotely according to the Schedule of Activities and Assessments (SoA).

[0190] ●Based on the investigator's assessment, participants were considered eligible if they met all inclusion criteria and none of the exclusion criteria.

[0191] ●Screening and baseline visits may occur on the same day.

[0192] Baseline (Day 1)

[0193] ●Contact participants for a baseline visit to review and confirm eligibility and perform identity verification. Perform assessment based on SoA.

[0194] Eligible participants will be randomized during a virtual study visit on Day 1. Participants will be randomized 1:1 (study app: control) to one of the following 4 cohorts: MS patients without mobility impairment; MS patients with mobility impairment; breast cancer patients; lung cancer patients. Participants randomized to the study app treatment group will download and activate the app on their personal primary smartphone.

[0195] Intervention period (Day 1 to Day 28)

[0196] Participants in the study app group used app-based brain exercises for seven minutes per day for four weeks.

[0197] ●Control group participants received a digital control and did not receive any study intervention.

[0198] ● According to the SoA, both groups were assessed weekly throughout the intervention period.

[0199] ● Participants assigned to the study app group completed a user experience questionnaire at the end of the intervention period.

[0200] Follow-up period (up to 1 week)

[0201] ● Participants completed follow-up assessments based on SoA.

[0202] ● Participants did not perform any activities within the study app.

[0203] ●A subset of participants completed an optional qualitative interview between Days 29 and 35.

[0204] Planned Number of Participants: A total of 189 participants will be enrolled in this study:

[0205] ●A total of 107 MS patients, of whom at least 53 belonged to the DiNaMo 4 group and at least 54 belonged to the control group,

[0206] 82 BC participants, of whom at least 41 were in the DiNaMo 4 group and at least 41 were in the control group.

[0207] Study Entry Criteria

[0208] Inclusion Criteria: Participants were eligible for entry into the study if they met all of the following criteria:

[0209] 1. Be fluent in written and spoken English and be able to read, understand and sign the informed consent form

[0210] 2. Live in the United States

[0211] 3. Adults aged 22 to 65

[0212] 4. Meet the criteria for the specific indication, including as reported by the study participant and with adequate clinical documentation (provided to the study team upon request)

[0213] 5. Have a valid email address and be willing and able to receive and respond to emails

[0214] 6. Access to the Internet for the duration of the study

[0215] 7. Have an active bank account to receive research compensation, or be willing to create one

[0216] 8. Willing and able to comply with the study protocol and assessments

[0217] 9. Was the only user of a smartphone during the study duration

[0218] 10. Willing and able to receive Short Message Service (SMS) text messages and notifications on their smartphone

[0219] 11. Can use operating headphones

[0220] Exclusion Criteria: Participants were ineligible for the study if they met any of the following criteria:

[0221] 1. Vision, dexterity, or cognitive deficits so severe that, in the judgment of the researcher, the use of app-based reaction time activities is impractical

[0222] 2. Severe mental illness involving a history of psychosis (e.g., schizophrenia, bipolar disorder, severe personality disorder)

[0223] 3. Hospitalization for mental illness in the past 6 months

[0224] 4. Participation in any research in the past 3 months (including research on psychotherapy, mindfulness, cognitive training, or drug therapy)

[0225] 5. Start or change specific drug treatment for primary disease within 30 days before entering the study

[0226] 6. Plan to introduce new treatments during the study duration (6 weeks) (including studies on psychotherapy, mindfulness, cognitive training, or medication)

[0227] 7. It is expected that the current medication or psychotherapy regimen will change during the study period (6 weeks)

[0228] 8. Self-reported substance use disorder in the past year

[0229] 9. Severe neurological disease impairing brain function (e.g., previous stroke, dementia, primary brain dysfunction, brain metastasis, Alzheimer's disease, Parkinson's disease, history of severe head trauma followed by persistent neurological dysfunction or known brain structural abnormalities)

[0230] 10. Mild, moderate, severe or profound unilateral or bilateral hearing loss

[0231] Test product and management model DiNaMo 004

[0232] Eligible participants will download and install the study app on their smartphones at the baseline visit (Day 1).

[0233] Treatment regimen: Study app: Daily use for 3 weeks (7 minutes per day)

[0234] Study Duration: Participation in the study will last up to 6 weeks:

[0235] Screening period: up to 2 weeks

[0236] Intervention period: 3 weeks

[0237] Follow-up: up to 1 week

[0238] Sample size: 107 patients with MS, at least 53 in the DiNaMo 4 group and at least 54 in the control group; and at least 80 patients with BC, at least 41 in the DiNaMo 4 group and at least 41 in the control group. These sample sizes were sufficient to measure changes with relative precision.

[0239] Statistical Analysis: Changes from baseline to week 3 for all PROMIS-29+2 domains, BPI pain severity and BPI pain interference, PCS subcategory and total scores, and computerized cognitive assessment were summarized using descriptive statistics. An analysis of covariance (ANCOVA) model was implemented to assess differences between the two treatment groups. The model included change from baseline as the dependent variable and included treatment group, indication, and baseline value as covariates in the model. 95% confidence intervals (CIs) and two-sided p-values ​​for the null hypothesis of no difference between the two groups are provided. Least squares (LS) means of treatment effects are provided. In addition, LS means, 95% CIs, and p-values ​​for the null hypothesis of no change from baseline for each treatment group are provided.

[0240] For the SDMT and FACT-Cog for the specific indication, changes from baseline were summarized using descriptive statistics. In addition, for the change from baseline to Week 3 within each treatment group, the 95% CI and two-sided p-value for the null hypothesis of no difference between treatment groups were provided. The CI and p-value were based on a 2-sample t distribution.

[0241] The 95% CI for the change from baseline to Week 3 within each group is provided, along with a two-sided p-value for the null hypothesis of no change from baseline for one sample (pre-post) using a t-distribution.

[0242] The number and percentage of improvement as measured by GRC (improvement as a score greater than 1) were summarized by treatment group. Comparisons between treatment groups were performed using the Cochran-Mantel-Haenszel stratified by indication.

[0243] For the remaining exploratory end points and safety parameters, only descriptive statistics were used.

[0244] 2. Individual indications

[0245] A. Multiple sclerosis without movement impairment

[0246] Indications: Multiple sclerosis (MS)

[0247] Evaluation Criteria

[0248] Additional disease-specific scales:

[0249] ●Symbolic Digital Modal Testing (SDMT)

[0250] Study Entry Criteria

[0251] Inclusion criteria:

[0252] 1. Self-report clinical diagnosis of multiple sclerosis and provide sufficient clinical documentation (provided upon request by the research team)

[0253] 2. Relapse within 30 days before screening and no steroid use

[0254] 3. Self-reported pain for at least the past 3 months, with the pain starting after the diagnosis of MS.

[0255] Exclusion criteria:

[0256] 1. Self-reported history of cancer diagnosis

[0257] 2. Unable to walk 300 meters (328 yards) without assistance

[0258] B. Multiple sclerosis with mobility impairment

[0259] Indications: Multiple sclerosis (MS)

[0260] Evaluation Criteria

[0261] Additional disease-specific scales:

[0262] ●Symbolic Digital Modal Testing (SDMT)

[0263] Study Entry Criteria

[0264] Inclusion criteria:

[0265] 1. Self-report clinical diagnosis of multiple sclerosis and provide sufficient clinical documentation (provided upon request by the research team)

[0266] 2. Relapse within 30 days before screening and no steroid use

[0267] 3. Unable to walk 300 meters (328 yards) without assistance

[0268] 4. Self-reported pain for at least the past 3 months, and the pain started after the diagnosis of MS

[0269] Exclusion criteria

[0270] 1. Self-reported history of cancer diagnosis

[0271] C.Breast cancer

[0272] Indications: Breast cancer

[0273] Evaluation criteria:

[0274] Additional disease-specific scales:

[0275] Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog)

[0276] Study Entry Criteria Inclusion Criteria

[0277] 1. The study participant reports a history of breast cancer (at any stage) and provides adequate clinical documentation (upon request from the research team)

[0278] 2. Completed at least 3 months of cancer chemotherapy within 9 months to 5 years before screening

[0279] 3. Self-reported pain for at least the past 3 months, and the pain began after cancer treatment

[0280] Exclusion criteria

[0281] 1. Self-reported clinical diagnosis of multiple sclerosis

[0282] D. Lung cancer

[0283] Indications: Lung cancer

[0284] Evaluation Criteria

[0285] Additional disease-specific scales:

[0286] Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog)

[0287] Study Entry Criteria Inclusion Criteria

[0288] 1. Study participants report a history of lung cancer (any stage) and provide adequate clinical documentation (upon request from the research team)

[0289] 2. Completed at least 3 months of cancer chemotherapy within 9 months to 5 years before screening

[0290] 3. Self-reported pain for at least the past 3 months, and the pain began after cancer treatment

[0291] Exclusion criteria

[0292] 1. Self-reported clinical diagnosis of multiple sclerosis

[0293] 3. Activities and Assessment Schedule

[0294]

[0295]

[0296] Abbreviations: AE = adverse event; app = application program; BPI = Brief Pain Inventory; EOS = end of study; ET = early termination; GRC = Global Change Rating; PCS = Pain Catastrophizing Scale, PROMIS-29+2 = Patient-Reported Outcomes Measurement Information System

[0297] a. Applicable only to participants in the treatment group

[0298] b. Based on the application evaluation

[0299] c. All drugs related to the primary indication or acting on the mind

[0300] 4. Introduction

[0301] A. Multimodal Multistable Bias Modification

[0302] Multimodal Multistable Bias Modification (Multimodal, Multistable Bias Modification or MMBM) is a targeted cognitive training that uses the principles of Multimodal Neurally Rich Tasks (M-NET) to reduce symptoms associated with multiple sclerosis (MS) and cancer, including fatigue, pain, and mood-related symptoms. In Multimodal Multistable Bias Modification, users are trained to redirect their attention to positive stimuli rather than things that may cause them distress, such as pain or threat-related stimuli, through a multistable perceptual phenomenon called monocular rivalry. At the same time, binaural beats are used to target fatigue symptoms and work synergistically by providing a second multistable perceptual modality.

[0303] B. Attention bias

[0304] Individuals with multiple indications (such as multiple sclerosis or various cancers) often show problems with both pain and emotions. These problems may be exacerbated by attention biases related to pain or threat-related stimuli. Individuals with chronic pain may pay more attention to pain-related stimuli, which may worsen the condition via fear avoidance. Individuals may avoid stimuli or activities that are thought to cause pain, which may cause the body to lose its ability to adapt and lead to further disability, thereby exacerbating the condition. For stimuli related to threats, individuals with anxiety usually automatically look for any signs of threat. The threat causes a feedback loop that keeps the anxiety going. This may include stimuli related to indications: for example, cancer survivors who are worried about cancer recurrence may have a bias against cancer-related stimuli. Similarly, since pain and anxiety are highly comorbid and share similar neural circuit changes, a synergistic effect may be produced for the biases related to both. Finally, individuals with depression usually show attention biases to negative emotional information, which can lead to rumination and thereby exacerbate symptoms. These different attention biases add up and can make people very weak.

[0305] Common symptoms of MS include pain and mood disturbances, both of which are targets for this therapy. There is also a significant relationship between high-grade pain and anxiety, where multimodal multistable bias modification may be particularly beneficial.

[0306] Both individuals with cancer and cancer survivors show an attentional bias toward cancer-related words. Studies have also found evidence of a bias toward threat and negative emotions. Attempts to alter these automatic associations have shown some success. Since cancer patients also experience pain and emotional symptoms, multimodal multistable bias modification is expected to be highly relevant to this patient population.

[0307] C. Cognitive impairment

[0308] Cognitive impairment is a common symptom of a variety of physical and mental disorders, because its main symptoms are associated with the disease / disorder, or associated with the treatment of a specific disease (e.g., cancer chemotherapy), or both. Cognitive impairment is also often associated with emotional regulation problems and emotional problems. The combination of cognitive deficits and emotional symptoms can cause pain and disability to patients, can negatively affect their quality of life, and can lead to increased health care utilization.

[0309] For example, for multiple sclerosis (MS), a chronic central nervous system disease, cognitive impairment is very common, with up to 70% of MS patients suffering from cognitive deficits. Deficits can affect multiple cognitive areas, and attention and processing speed are usually affected. Patients with MS suffer from these cognitive deficits, such as loss of ability and stress, and there is currently a lack of treatment options to improve these challenges. Computerized cognitive training has been repeatedly shown to be effective in correcting cognitive impairment in MS. The training can produce a wide range of benefits outside its cognitive domain. For example, cognitive training has been shown to have beneficial effects on memory, semantic fluency, processing speed, and executive function. Its benefits can also be extended beyond cognitive improvement. For example, other studies have found beneficial effects on depression, daily living activities, expanded disability status scale scores, and fatigue.

[0310] For cancer patients, tumor activity and associated inflammatory processes and / or cancer-related treatments can affect cognitive function. Up to 75% of cancer patients experience cancer-related cognitive impairment, and for up to 35% of those with impairment, the impairment may persist for months or years after treatment. As the number of cancer survivors increases, the incidence of persistent cognitive impairment due to cancer and cancer treatment will increase further. Similar to MS, computerized cognitive training has shown efficacy in general cancer patients, breast cancer patients, and cancer survivors.

[0311] Fatigue is also a debilitating symptom in both indications and can contribute significantly to cognitive problems. Up to 97% of people with MS experience significant fatigue symptoms, and up to 40% describe it as the most disabling symptom of their disease; in fact, fatigue is the primary symptom in one-third of diagnosed patients. Fatigue is one of the most common cancer symptoms and is often the primary symptom, and this can be caused by treatments such as chemotherapy (which has a 75-100% prevalence) or the disease itself (especially in advanced stages). One study even found that 37% of cancer survivors had not regained their energy to a satisfactory level even years later.

[0312] D. Binaural beats

[0313] In binaural beats, a single tone frequency is played to each ear, and the difference in frequency between the two can be detected as a "beat." The theory behind binaural beats is that rhythmic sensory stimulation can induce neural oscillations, similar to non-invasive techniques such as transcranial magnetic stimulation and transcranial direct current stimulation. Studies have found beneficial effects of binaural beats on symptoms of depression and anxiety, memory, attention and cognition, fatigue, and pain perception.

[0314] E. Research Applications (Apps)

[0315] The Multimodal Multistable Bias Modification CT-100 Digital Neural Activation and Modulation (DiNaMo) component (e.g., App 125) uses implicit training to redirect and strengthen attentional processes. The intervention can help improve cognitive abilities and redirect attentional biases to make participants less sensitive to painful stimuli. Preliminary studies have shown success with computerized cognitive training for MS and cancer and have successfully retrained attentional biases for pain, threat, and emotion. It is likely that Multimodal Multistable Bias Modification can improve cognitive abilities and attentional biases present in MS and cancer.

[0316] F. Digital comparison

[0317] The digital control group downloaded the digital control app and completed a version of the task designed to be ineffective in the study app. This included choosing among a set of neutral words based solely on personal preference and did not include any attentional bias-capturing stimuli. Additionally, all instances of multistable perception were removed, including the removal of all auditory elements.

[0318] G. Research reasons

[0319] Multimodal multistable bias modification is a novel intervention that uses the principles of a multimodal neural enrichment task (M-NET) in order to reduce symptoms associated with MS and cancer. Attentional biases to various attention-capturing stimuli can exacerbate a variety of symptoms in many different indications. For example, in some conditions, patients pay increased attention to pain-related stimuli, which can lead to hypersensitization. Similarly, hypersensitization to threat-related stimuli can exacerbate anxiety.

[0320] In multimodal multistable bias modification, users are trained to redirect their attention to positive stimuli rather than stimuli that may cause them distress, such as pain or threat-related stimuli. This is done in a novel format, utilizing multistable perception. Visual multistable perception in the form of monocular rivalry is used to implicitly retrain the attention bias. Simultaneously, auditory multistable perception in the form of binaural beats will be used to target fatigue symptoms and work in tandem to enhance the attention bias component.

[0321] The purpose of the proposed study is to evaluate the preliminary effects of the DiNaMo component (the research app) on measures of attention bias, attention impairment, and related outcomes (overall quality of life [QoL]) in multiple conditions such as MS, breast cancer, and lung cancer. Results from this study could be used as components of future digital therapeutics.

[0322] H.CT-100 Platform

[0323] The CT-100 platform provides interactive software-based therapeutic components that can be used as part of multimodal treatments in future software-based prescription digital therapeutics. One category of CT-100 components is the DiNaMo component. The DiNaMo component targets key neural systems (including but not limited to systems related to sensation, perception, emotion, pain, attention, cognitive control, social interaction, and self-processing) to optimally improve the health of participants.

[0324] 3. Goals and End Points

[0325] The research objectives are:

[0326] ●Assess trends in effects on pain interference, cognition, and related outcomes (attention bias and global QoL) compared with a digital control group

[0327] ● Explore the feasibility of conducting a digital multimodal multistable bias-modified visual search task (research app) at home, including participants’ engagement and experience with the research app

[0328] ●Evaluate the safety of research applications

[0329] Study endpoints supporting these objectives are listed in Table 1 .

[0330] Table 1: Study endpoints

[0331]

[0332]

[0333] 4. Study Design

[0334] A. Scientific Principles of Research Design

[0335] This study aimed to evaluate the preliminary effects of the multimodal multistable bias modification CT-100 component (research application) on attentional bias and attentional cognitive deficits compared with a digital control.

[0336] Participants were assessed based on validated standard participant rating outcomes. Participant engagement with the study app was assessed based on participant usage data captured in the study app. Participant safety was assessed throughout the study. The scales and assessments are described herein.

[0337] B. Study End Definition

[0338] The study end date was defined as the last contact date or last contact attempt date for the last participant who completed or withdrew from the study. For the purposes of this study, participants who completed the trial assessment on Day 21 (+3) (Week 3) were defined as trial completers.

[0339] 6. Study interventions and concomitant treatments

[0340] A. Research Intervention Implemented

[0341] The CT-100-D-004 research application (e.g., Application 125) will administer the research intervention to participants.

[0342] B.CT-100

[0343] The study intervention being evaluated was the Multimodal Multistable Bias Modification CT-100 component, which is a digital mobile application. Participants randomized to this group downloaded and installed the study application onto their smartphones at the baseline visit (Day 1) and performed Multimodal Multistable Bias Modification training daily using the study application during the 3-week intervention period.

[0344] C. Control

[0345] The digital control group downloaded the digital control app and completed a version of the task designed to be inactive in the study app. This consisted of choosing among a set of neutral words based solely on personal preference and did not include any attentional bias-capturing stimuli. Additionally, all instances of multistable perception were removed, including the removal of all auditory elements.

[0346] D. Preparation / Handling / Storage / Responsibility

[0347] Detailed instructions for downloading, installing, activating, using, and disposing of Research Applications are described in the CT-100-D-004 Research Applications Field Guide.

[0348] In general:

[0349] 1. Only participants enrolled in the study will receive the research intervention.

[0350] 2. On-site personnel must confirm download and activation of the study app.

[0351] 3. After the third week, the study application will be automatically invalidated. Participants who have completed the study or terminated the study early will be notified by the site staff to uninstall the study application.

[0352] E. Concomitant treatment

[0353] Participants continued to use prescribed therapy during their participation in the study. Participants self-reported any changes in all concomitant medications related to the primary indication or that were psychoactive at the end of the follow-up period.

[0354] 7. Research Evaluation and Procedures

[0355] Study assessments and procedures, including their timing, are summarized in the SoA. Adherence to study design requirements, including those specified in the SoA, is critical and essential to the conduct of the study. No waivers or exemptions from the protocol will be permitted. Every effort should be made to ensure that assessments and procedures are completed in accordance with protocol requirements. All clinician-administered scales, if applicable, are administered by appropriately trained personnel. Study assessments are described below.

[0356] The following efficacy assessment scales were used in this trial according to the timing provided in the SoA. A description of the scales and the corresponding scoring algorithms for all endpoints will be provided in the Statistical Analysis Plan (SAP).

[0357] A. Patient Reported Outcomes Measurement Information System-29+2 (PROMIS-29+2) Profile v2.1

[0358] PROMIS-29 is part of the Patient-Reported Outcomes Measurement Information System (PROMIS). PROMIS-29 is a brief assessment form containing 4 items from each of the 7 PROMIS domains (anxiety, physical function, pain interference, fatigue, sleep disturbance, depression, and ability to participate in social roles and activities), plus one pain intensity question (0-10 numeric rating scale) and 2 cognitive function questions. PROMIS-29 is generic and not disease-specific (i.e., it can assess a patient's health regardless of disease or condition) and is intended for use in adults (ages 18+). Scores are generated for all 7 domains. The domains are assessed within the past 7 days. PROMIS-29 has been widely implemented and validated in a variety of populations and settings. This electronic questionnaire is completed by the participant. It takes approximately 7 minutes to complete.

[0359] PROMIS29+2 also allows for the calculation of a PROMIS Preference (PROPr) score. This allows for the calculation of a single quality of life summary score using the PROMIS subscales. The calculation ranges from 0 (death) to 1 (perfect health).

[0360] B. Brief Pain Inventory (BPI)

[0361] The BPI is a self-report measure used in clinical trials. The BPI has 32 items that assess pain severity and interference using a numeric rating scale (NRS 0-10), pain location, pain medication, and amount of pain relief in the past 24 hours. This measure has excellent test-retest reliability and internal consistency in chronic pain research. The questionnaire is completed electronically by the participant. It takes approximately 5 minutes to complete.

[0362] The BPI interference subscale has 7 items, each of which is scored using a numeric rating scale (NRS 0-10). The BPI interference subscale is designed to assess the extent to which pain affects daily functioning. This measurement is used for both acute and chronic pain. Participants complete the questionnaire electronically using a standard 24-hour questionnaire. It takes about one minute to complete.

[0363] C. Pain Catastrophizing Scale (PCS)

[0364] The PCS is a reliable and valid 13-item self-report measure for assessing pain-related catastrophic thinking and is intended for use in adults (18-64 years). The PCS consists of a 5-point Likert scale across 3 subscales: rumination (4 items), magnification (3 items), and helplessness (6 items). The subscales can be scored individually or can be summed to provide a total score. The questionnaire is a survey that participants complete electronically. It takes approximately 5 minutes to complete.

[0365] D. Grading of Change (GRC)

[0366] The GRC is a self-report, single-item, 10-point Likert scale that assesses participants' rating of their overall improvement in their indication following the study intervention. This item is completed electronically by the participant.

[0367] E. User Experience Questionnaire and Optional Qualitative Interviews

[0368] The User Experience Questionnaire was a questionnaire used to understand participants' experience using the study app during the intervention phase. The questionnaire asked questions related to perceived enjoyment, challenges, and related user experience, and did not contain questions related to clinical outcomes. The questionnaire was completed electronically by the participants. It took approximately 7 minutes to complete.

[0369] Additionally, some participants may have participated in qualitative user interviews based on phone or video conferencing. These interviews collected more information about the users’ experience with the app, such as favorite app features, usability of features, challenges associated with the intervention, or any other feedback about regular interactions with the app.

[0370] 8. Statistical considerations

[0371] A. Statistical Assumptions

[0372] The study was exploratory in nature, and no formal statistical hypotheses were specified.

[0373] B. Sample size determination

[0374] Among them, at least 100 participants had MS, at least 50 participants had no mobility impairment, and at least 50 participants had mobility impairment, and at least 80 participants had a tumor, at least 40 participants had breast cancer, and at least 40 participants had lung cancer.

[0375] C. Analysis Set

[0376] For the purpose of analysis, the following analysis sets were defined:

[0377]

[0378]

[0379] D. Statistical analysis

[0380] The SAP was completed prior to database lock and it contains a more technical and detailed description of the statistical analyses described in this section. This section summarizes the planned statistical analyses for the most important endpoints.

[0381] E. General Considerations

[0382] Descriptive statistics included means and standard deviations, medians, and minimum and maximum values ​​for continuous variables. For categorical variables, Ns and percentages were reported for all applicable variables. Descriptive statistics were tabulated by combined treatment group and by treatment group within each indication.

[0383] All analyses were exploratory in nature. 95% confidence intervals and statistical tests were performed for some efficacy end points and are described in detail as part of the description of the planned analyses for each end point in the end points.

[0384] Data collection methods were programmed to minimize missing data (e.g., an answer had to be given in order to proceed to the next assessment question). SAP addressed the issue of handling incomplete questionnaires, where fields or total scores were missing. In the case of missing complete questionnaires or interviews, no imputation was performed, and only observed data were included in the analysis. No adjustment for multiplicity was planned.

[0385] F. Treatment of Participants

[0386] The analysis was performed on the enrolled group. The numbers of participants who enrolled, failed screening, were randomized, and completed the study are presented. The number of subjects in each analysis set is presented by treatment group in each indication cohort.

[0387] G. Demographics and Baseline Characteristics

[0388] To assess the comparability of the two groups at baseline, demographic and baseline characteristics data were summarized by treatment group. These summaries are presented for the mITT set. If the total number of participants between the mITT and safety, ITT, and PP analysis sets differed by more than 5 participants, summaries were presented for these sets.

[0389] H. Exploratory Endpoints

[0390] This is an exploratory study. Certain endpoints were available for all participants: PROMIS-29+2, BPI, PCS, and GRC. Analyses of these endpoints were performed by treatment group using the mITT set. The analysis was repeated for the PP set.

[0391] For PROMIS, the absolute values ​​and changes from baseline to Week 3 for the 7 core domains, pain intensity questions, cognitive functioning domain, and PROPr summary scores were summarized descriptively. In addition, the changes from baseline to Week 3 were analyzed using an analysis of covariance (ANCOVA) model to estimate the differences between the two treatment groups. The model included the change from baseline as the dependent variable and included treatment group, indication, and baseline value as covariates in the model. The 95% confidence interval (CI) and two-sided p-value for the null hypothesis of no difference between the two groups are provided. The least squares (LS) means of the treatment effects are provided. In addition, the LS means, 95% CI, and p-value for the null hypothesis of no change from baseline for each treatment group are also provided.

[0392] For the BPI, the absolute values ​​and changes from baseline to week 3 for the 4 questions on pain severity and the 7 questions on pain interference were summarized descriptively across all visits. In addition, CIs and tests were performed within and between treatment groups using the same methods as for PROMIS. For the PCS, the absolute values ​​and changes from baseline to week 3 for the 3 domains (helplessness, magnification, rumination) and their totals were summarized descriptively across all visits. CIs and tests were performed within and between treatment groups using the same methods as for PROMIS.

[0393] Plots of mean (standard error [SE]) changes over time relative to baseline within treatment groups and indications were generated for the above endpoints using the mITT set. For the GRC, the number and proportion of subjects with improvement (score greater than 1) were summarized by treatment group. Treatment groups were compared using Cochran-Mantel-Haenszel stratified by indication.

[0394] I. Other exploratory endpoints

[0395] Endpoints considered in this section are either indication-specific or completed only by participants in the study application group. For the former (SDMT and FACT-Cog), changes from baseline are summarized using descriptive statistics. 95% CIs and two-sided p-values ​​for the change from baseline to Week 3 within each treatment group and for the null hypothesis of no difference between treatment groups are provided. CIs and p-values ​​are based on a 2-sample t-distribution. 95% CIs for the change from baseline to Week 3 within each group and two-sided p-values ​​for the null hypothesis of no change from baseline using a one-sample (pre- and post-) t-distribution are provided.

[0396] For endpoints completed only by the study application group, analyses were stratified by indication and overall (for patients with MS and cancer). Analyses for these endpoints were performed using the mITT set and included only descriptive statistics.

[0397] 9. Results

[0398] The applicants conducted a remote, randomized, single-blind exploratory basket study to evaluate the feasibility and acceptability of a smartphone application-based multimodal multistable bias modification (MMBM) intervention in multiple sclerosis (MS) and breast cancer (BC). The results showed strong evidence supporting progressive MMBM in BC, particularly for fatigue and mood, and progressive MMBM in MS, particularly for anxiety and pain catastrophizing.

[0399] I. Patient-Reported Outcomes: PROMIS

[0400] Patients were assessed via the Patient-Reported Outcomes Measurement Information System (PROMIS). Improvements in anxiety, depression, fatigue, sleep disturbance, and pain interference were indicated by lower scores. Improvements in cognitive functioning, physical functioning, and social interaction were indicated by higher scores. Results for patient-reported outcomes recorded by PROMIS are described below and are available at Figure 10-18 Displayed in.

[0401] A. Fatigue

[0402] like Fig.10 As shown in Figure 2, breast cancer showed an advantage of DiNaMo over controls. Although both DiNaMo and controls for BC improved significantly over time, only DiNaMo exceeded the minimum clinically important change threshold. Only DiNaMo in the BC group also met the more stringent criteria, i.e., half a standard deviation (5 points) indicates a clinically important change. Both DiNaMo and controls for MS improved significantly over time and exceeded the minimum clinically important change threshold.

[0403] B. Depression

[0404] like Fig.11 As shown in Figure 2, BC showed an advantage of DiNaMo over control. The difference was above the minimum clinically important change threshold. Both DiNaMo and control for MS improved significantly over time and exceeded the minimum clinically important change threshold.

[0405] C. Anxiety

[0406] like Fig.12 As shown in the , BC showed a significant advantage of DiNaMo over the control, while MS showed a trend advantage. The difference was above the minimum clinically important change threshold. Only DiNaMo for MS improved significantly over time and was above the minimum clinically important change threshold. Both DiNaMo for BC and the control improved significantly over time and exceeded the minimum clinically important change threshold. Only DiNaMo in the BC group met the more stringent criteria, i.e., half a standard deviation (5 points) indicating a clinically important change.

[0407] D. Pain interference

[0408] like Fig.13 As shown in Figure 3, only DiNaMo for MS tended to improve over time. Only DiNaMo for BC improved significantly over time and exceeded the minimum clinically important change threshold.

[0409] E. Pain score

[0410] like Fig.14 As shown in , both DiNaMo and control for MS improved significantly over time. Only DiNaMo for BC improved significantly over time.

[0411] F. Sleep disorders

[0412] like Fig.15 As shown in Figure 3, only DiNaMo for MS and BC showed significant improvement over time and exceeded the minimal clinically important difference threshold.

[0413] G. Physical functions

[0414] like Fig.16 As shown in Figure 2, both DiNaMo and control for MS significantly improved over time. Only DiNaMo for BC significantly improved over time and exceeded the minimum clinically important change threshold.

[0415] H. Cognitive function

[0416] like Fig.17 As shown in , only DiNaMo for BC tends to improve over time.

[0417] I. Social Function

[0418] like Fig.18 As shown in Figure 3, only DiNaMo for MS showed significant improvement over time. Both DiNaMo for BC and control showed significant improvement over time and exceeded the minimal clinically important change threshold.

[0419] II. Patient-related outcomes: pain-related

[0420] Pain-related outcomes were assessed by patient-reported outcomes. Self-report assessments of pain interference and pain severity were used for patients with MS and BC as described below and are available at Figure 19-23 Lower scores indicate improvement.

[0421] A. Brief Pain Inventory-Interference

[0422] like Fig.19As shown in , DiNaMo for MS improved over time. Both DiNaMo and control for BC improved over time.

[0423] B. Brief Pain Inventory – Worst Pain Level

[0424] like Fig. 20 As shown in , both DiNaMo and control for MS improved over time. DiNaMo for BC tended to improve over time.

[0425] C. Brief Pain Checklist – Minimum Pain

[0426] like Fig.21 As shown in , DiNaMo for BC tends to improve over time.

[0427] D. Brief Pain Inventory – Average Pain Severity

[0428] like Fig. 22 As shown in Figure 3, DiNaMo for MS tended to show superiority over the control group. DiNaMo for MS and BC improved significantly over time.

[0429] E. Brief Pain Inventory – Current Pain Severity

[0430] like Fig.23 As shown in , DiNaMo for BC showed significant advantages over the control. DiNaMo for MS tended to improve over time. DiNaMo for BC improved significantly over time.

[0431] F. Pain Catastrophizing Scale

[0432] The self-report Pain Catastrophizing Scale showed significant improvement in MS patients compared with controls ( Fig.24 ). DiNaMo also showed significant improvement in BC patients.

[0433] III. Patient-Reported Outcomes – Miscellaneous

[0434] A. Cognition

[0435] like Fig.25 As demonstrated in , cognition in MS showed statistically and clinically meaningful improvements in both DiNaMo and controls.

[0436] IV. Overall change score

[0437] Patients were asked to describe how they felt at the end of the study compared to the beginning of the study. The DiNaMo group tended to have a greater percentage improvement ( Fig.26 ).

[0438] V. Target Results

[0439] Patients are assessed via a dot-probe assessment to measure attentional bias. The goal for the attentional bias index is to be close to 0 (no bias) or lower.

[0440] like Fig. 27 As shown in Figure 2, BC controls significantly worsened the attention bias depression index over time, while BCDiNaMo did not. Fig.28 As shown in the , the MSDiNaMo trended toward superiority on the Anxiety Attention Bias Index, which is well consistent with the superiority of MSDiNaMo over controls on the PROMIS-Anxiety domain (indication-specific words can induce anxiety about one's own condition).

[0441] VI. Conclusion

[0442] The data are from a remote, randomized, single-blind exploratory basket study to evaluate the feasibility and acceptability of a smartphone-based multimodal multistable bias modification (MMBM) intervention for multiple sclerosis (MS) and breast cancer (BC) to treat symptoms of fatigue, mood, and pain.

[0443] The results include strong evidence to support the advancement of MMBM in BC. Fatigue showed that DiNaMo had a statistically and clinically significant advantage over controls, as measured by PROMIS-29+2 (Patient Reported Outcomes Measurement Information System). The related PROMIS domain of cognitive function also showed a trend improvement over time only in DiNaMo. For mood, the PROMIS domains of depression and anxiety showed that DiNaMo had a statistically and clinically significant advantage over controls (PROMIS-29+2). For pain, only the PROMIS domains of pain interference and pain intensity of DiNaMo showed improvement over time. All pain severity scores in the Concise Pain Inventory also showed a trend or statistically significant improvement for DiNaMo, but not for controls. DiNaMo also had a significant advantage over controls in current pain severity scores. In the pain catastrophizing scale, only DiNaMo improved significantly over time. Finally, the PROMIS domains of related physical function also showed statistically and clinically significant improvement over time.

[0444] In addition, the results showed strong evidence to support the MMBM of progression in MS. In PROMIS-29+2, DiNaMo had a statistical trend and clinically significant advantage in anxiety compared to the control group. In the target attention bias assessment, MS showed a trending advantage of DiNaMo over the control in anxiety and indication-related words. For pain, DiNaMo had a statistically significant advantage over the control in the pain catastrophizing scale. Only PROMIS pain interference in DiNaMo also had a trend of improvement. In the Brief Pain Inventory, only the pain interference score in DiNaMo showed significant improvement over time. The average pain severity score showed a trend of advantage for DiNaMo over the control. The current pain severity score showed a trend of improvement only in DiNaMo.

[0445] The DiNaMo 004 intervention (MMBM) demonstrated statistically and clinically significant improvements in patients with breast cancer (BC). This suggests that treatment effects may vary by disease, a hypothesis that can be supported by direct EEG evidence. This would further strengthen an already compelling case.

[0446] The results described here indicate that BC (and possibly cancer in general) may be particularly responsive to MMBM interventions. This may be due to its direct effects on functional frontoparietal connectivity, which has been implicated in both chemotherapy-related cognitive impairment and the development of cancer itself, and it is noteworthy that studies have shown that functional brain changes prior to chemotherapy are more predictive of post-treatment fatigue than chemotherapy itself.

[0447] This hypothesis is further supported by the faster response observed in breast cancer compared to multiple sclerosis (MS), since in MS, cognitive impairment and fatigue are primarily caused by structural damage and inflammation, followed by maladaptive network recruitment leading to fatigue. In other words, MMBM in MS does not target the root cause but rather downstream events, which may explain the slower or less pronounced effects compared to breast cancer. This mechanism of action (MOA) of MMBM can be further investigated using EEG recordings to assess changes in functional connectivity and neural oscillations within the frontoparietal cortex and network communication during resting state.

[0448] Example 2: A randomized, controlled, exploratory basket study evaluating multimodal multistable bias modification for normalization of attentional bias and cognitive improvement in adults with cancer or psychogenic chronic pain.

[0449] summary

[0450] Indications: Cancer and psychogenic chronic pain conditions

[0451] Objectives: To assess trends in effects on pain interference, cognition, and related outcomes (attention bias and global quality of life [QoL]) compared with usual care (CAU) or a digital control group.

[0452] Evaluation Criteria

[0453] Exploratory End Points

[0454] ●Change in quality of life from baseline to weeks 2-8 as measured by PROMIS-29+2 (Patient-Reported Outcomes Measurement Information System)

[0455] Change from baseline to weeks 2-8 in pain severity and pain interference as measured by the Brief Pain Inventory (BPI)

[0456] Change from baseline to weeks 2-8 in the Pain Catastrophizing Scale (PCS)

[0457] ● Change from baseline to Weeks 2-8 for indication-specific measures: Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog)

[0458] ● Change from baseline to weeks 2-8 on computerized cognitive assessment

[0459] ●Proportion of participants with improvement as measured by Global Rating of Change (GRC) scores at Weeks 2-8

[0460] ● Engagement with the research app as measured by metrics such as daily app usage and daily time in the research app

[0461] ● Evaluate the experience of the research application, such as through user experience surveys and optional qualitative interviews that may be conducted after the treatment period

[0462] ●Other exploratory endpoints may include the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-Fatigue), the Functional Assessment of Cancer Therapy-Comprehensive (FACT-G), and / or the Hospital Anxiety and Depression Scale (HADS). FACIT-Fatigue is a 13-item scale with 5-point Likert-type scale questions. The scores are added together (two of the questions are reverse scored). To compensate for missing scores, the scores are multiplied by 13 and divided by the number of questions answered. Higher scores indicate better quality of life. FACT-G is a 27-item questionnaire with a 5-point Likert-type scale used to assess the health-related quality of life of cancer patients, including physical, social, emotional, and functional subscales. The values ​​are added together, some of which are reverse scored (all social and functional subscales, and one of the emotional subscale questions). All subscales are added together to obtain the FACT-G total score, and higher scores indicate better quality of life. HADS is a 14-item questionnaire used to assess depression and anxiety, and higher scores in each subdomain indicate higher symptom severity.

[0463] Study Design

[0464] Reference now Figure 8 , depicts the timeline of a randomized, controlled, exploratory basket study to evaluate multimodal multistable bias modification for normalization of attentional biases and cognitive improvement in adults with cancer or psychogenic chronic pain.

[0465] Screening period (Day -14 to Day -1)

[0466] ● Participant screening for up to 14 days, including electronic informed consent. During this screening period, assessments are performed remotely according to the Schedule of Activities and Assessments (SoA).

[0467] ●Based on the investigator's assessment, participants were considered eligible if they met all inclusion criteria and none of the exclusion criteria.

[0468] ●Screening and baseline visits may occur on the same day.

[0469] Baseline (Day 1)

[0470] ●Contact participants for a baseline visit to review and confirm eligibility and perform identity verification. Perform assessment based on SoA.

[0471] Eligible participants will be randomized during a virtual study visit on Day 1. Participants will be randomized 1:1 (study app: control) to the cancer and psychogenic chronic pain condition cohorts. Participants randomized to the study app treatment group will download and activate the app on their personal primary smartphone.

[0472] Intervention period

[0473] Participants in the study app group used app-based brain exercises for 1 minute to 30 minutes per day, at least 3 times per week, for 2-8 weeks.

[0474] ●Control group participants will receive usual care (CAU) or a digital control and will not receive any study intervention.

[0475] ● According to the SoA, both groups were assessed weekly throughout the intervention period.

[0476] ● Participants assigned to the study app group completed a user experience questionnaire at the end of the intervention period.

[0477] Follow-up period (up to 1-8 weeks)

[0478] ● Participants completed follow-up assessments based on SoA.

[0479] ● Participants did not perform any activities within the study app.

[0480] ●A subset of participants completed an optional qualitative interview between Days 22 and 28.

[0481] Planned Number of Participants: A total of at least 40 participants will be enrolled in this study:

[0482] Study Entry Criteria

[0483] Inclusion Criteria: Participants were eligible for entry into the study if they met all of the following criteria:

[0484] 1. Be fluent in written and spoken English and be able to read, understand and sign the informed consent form

[0485] 2. Live in the United States

[0486] 3. Adults aged 22 to 65

[0487] 4. Meet the criteria for the specific indication, including as reported by the study participant and with adequate clinical documentation (provided to the study team upon request)

[0488] 5. Have a valid email address and be willing and able to receive and respond to emails

[0489] 6. Access to the Internet for the duration of the study

[0490] 7. Have an active bank account to receive research compensation, or be willing to create one

[0491] 8. Willing and able to comply with the study protocol and assessments

[0492] 9. Was the only user of a smartphone during the study duration

[0493] 10. Willing and able to receive Short Message Service (SMS) text messages and notifications on their smartphone

[0494] 11. Can use operating headphones

[0495] Exclusion Criteria: Participants were ineligible for the study if they met any of the following criteria:

[0496] 1. Vision, dexterity, or cognitive deficits so severe that, in the judgment of the researcher, the use of app-based reaction time activities is impractical

[0497] 2. Severe mental illness involving a history of psychosis (e.g., schizophrenia, bipolar disorder, severe personality disorder)

[0498] 3. Hospitalization for mental illness in the past 6 months

[0499] 4. Participation in any research in the past 3 months (including research on psychotherapy, mindfulness, cognitive training, or drug therapy)

[0500] 5. Start or change specific drug treatment for primary disease within 30 days before entering the study

[0501] 6. Plan to introduce new treatments during the study duration (1-12 weeks) (including studies on psychotherapy, mindfulness, cognitive training, or medication)

[0502] 7. It is expected that the current medication or psychotherapy regimen will change during the study period (1-12 weeks)

[0503] 8. Self-reported substance use disorder in the past year

[0504] 9. Severe neurological disease impairing brain function (e.g., previous stroke, dementia, primary brain dysfunction, brain metastasis, Alzheimer's disease, Parkinson's disease, history of severe head trauma followed by persistent neurological dysfunction or known brain structural abnormalities)

[0505] 10. Mild, moderate, severe or profound unilateral or bilateral hearing loss

[0506] Test product and management model DiNaMo 004

[0507] Eligible participants will download and install the study app on their smartphones at the baseline visit (Day 1).

[0508] Treatment regimen: Study application: Use at least 3 times per week for at least 2 weeks (1 minute to 30 minutes per day)

[0509] Study Duration: Participation in the study will last up to 6 weeks:

[0510] Screening period: up to 2 weeks

[0511] Intervention period: 2-8 weeks

[0512] Follow-up: 1–3 weeks

[0513] Sample size: At least 40 participants with cancer and / or 40 participants with psychogenic chronic pain disorders. These sample sizes should be sufficient to measure changes with reasonable precision.

[0514] Statistical Analysis: Changes from baseline to week 3 for all PROMIS-29+2 domains, BPI pain severity and BPI pain interference, PCS subcategory and total scores, and computerized cognitive assessment were summarized using descriptive statistics. An analysis of covariance (ANCOVA) model was implemented to assess differences between the two treatment groups. The model included change from baseline as the dependent variable and included treatment group, indication, and baseline value as covariates in the model. 95% confidence intervals (CIs) and two-sided p-values ​​for the null hypothesis of no difference between the two groups are provided. Least squares (LS) means of treatment effects are provided. In addition, LS means, 95% CIs, and p-values ​​for the null hypothesis of no change from baseline for each treatment group are provided.

[0515] For the SDMT and FACT-Cog for the specific indication, changes from baseline were summarized using descriptive statistics. In addition, for the change from baseline to Week 3 within each treatment group, the 95% CI and two-sided p-value for the null hypothesis of no difference between treatment groups were provided. The CI and p-value were based on a 2-sample t distribution.

[0516] The 95% CI for the change from baseline to Week 3 within each group is provided, along with a two-sided p-value for the null hypothesis of no change from baseline for one sample (pre-post) using a t-distribution.

[0517] The number and percentage of improvement as measured by GRC (improvement as a score greater than 1) were summarized by treatment group. Comparisons between treatment groups were performed using the Cochran-Mantel-Haenszel stratified by indication.

[0518] For the remaining exploratory end points and safety parameters, only descriptive statistics were used.

[0519] 2. Individual Indications - Cancer and Psychogenic Chronic Pain Conditions

[0520] Evaluation Criteria

[0521] Additional disease-specific scales:

[0522] Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog)

[0523] Study Entry Criteria Inclusion criteria:

[0524] 1. Have a history of cancer (at any stage) as reported by the study participant, with adequate clinical documentation (upon request from the research team)

[0525] 2. Completed at least 3 months of cancer chemotherapy within 9 months to 5 years before screening

[0526] 3. Self-reported pain for at least the past 3 months, and the pain began after cancer treatment.

[0527] Exclusion criteria:

[0528] 1. Self-reported clinical diagnosis history of multiple sclerosis or breast cancer.

[0529] 3. Activities and Assessment Schedule

[0530] The activity schedule can be found in Example 1.

[0531] 4. Introduction

[0532] A. Multimodal Multistable Bias Modification

[0533] Multimodal Multistable Bias Modification (Multimodal, Multistable Bias Modification or MMBM) will be utilized as described in Example 1 above.

[0534] B. Attention bias

[0535] Individuals with various conditions (such as various types of cancer) tend to show problems with both pain and emotion. These problems may be exacerbated by attention biases related to pain or threat-related stimuli. Individuals with chronic pain may pay more attention to pain-related stimuli, which may worsen the condition via fear avoidance. Individuals may avoid stimuli or activities that are thought to cause pain, which may cause the body to lose its ability to adapt and lead to further disability, thereby exacerbating the condition. For stimuli related to threats, individuals with anxiety usually automatically look for any signs of threats. The threat causes a feedback loop that keeps the anxiety going. This may include stimuli related to the indications: for example, cancer survivors who are worried about the recurrence of cancer may have deviations from cancer-related stimuli. Similarly, since pain and anxiety are highly comorbid and share similar neural circuit changes, synergistic effects may be produced for the deviations related to both. Finally, individuals with depression usually show attention biases to negative emotional information, which can lead to rumination and thereby exacerbate symptoms. These different attention biases add up and can make people very weak.

[0536] Both individuals with cancer and cancer survivors show an attentional bias toward cancer-related words. Studies have also found evidence of a bias toward threat and negative emotions. Attempts to alter these automatic associations have shown some success. Since cancer patients also experience pain and emotional symptoms, multimodal multistable bias modification is expected to be highly relevant to this patient population.

[0537] C. Cognitive impairment

[0538] Cognitive impairment is a common symptom of a variety of physical and mental disorders, because its main symptoms are associated with the disease / disorder, or associated with the treatment of a specific disease (e.g., cancer chemotherapy), or both. Cognitive impairment is also often associated with emotional regulation problems and emotional problems. The combination of cognitive deficits and emotional symptoms can cause pain and disability to patients, can negatively affect their quality of life, and can lead to increased health care utilization.

[0539] For cancer patients, tumor activity and associated inflammatory processes and / or cancer-related treatments can affect cognitive function. Up to 75% of cancer patients experience cancer-related cognitive impairment, and for up to 35% of those with impairment, the impairment may persist for months or years after treatment. As the number of cancer survivors increases, the incidence of persistent cognitive impairment due to cancer and cancer treatment will increase further.

[0540] Fatigue is also a debilitating symptom in both indications and can significantly contribute to cognitive problems. Fatigue is one of the most common cancer symptoms and is often the primary symptom, and can be caused by treatments such as chemotherapy (which has a 75-100% prevalence) or the disease itself (especially in advanced stages). One study even found that 37% of cancer survivors had not regained their energy to a satisfactory level even years later.

[0541] D. Binaural beats

[0542] In binaural beats, a single tone frequency is played to each ear, and the difference in frequency between the two can be detected as a "beat." The theory behind binaural beats is that rhythmic sensory stimulation can induce neural oscillations, similar to non-invasive techniques such as transcranial magnetic stimulation and transcranial direct current stimulation. Studies have found beneficial effects of binaural beats on symptoms of depression and anxiety, memory, attention and cognition, fatigue, and pain perception.

[0543] E. Research Applications (Apps)

[0544] Multimodal Multistable Bias Modification The CT-100 Digital Neural Activation and Modulation (DiNaMo) component (e.g., App 125) uses implicit training to redirect and strengthen attentional processes. The intervention can help improve cognitive abilities and redirect attentional biases to make participants less sensitive to painful stimuli. Preliminary studies have shown success with computerized cancer cognitive training and have also been successful in retraining attentional biases in response to pain, threat, and emotion. Multimodal Multistable Bias Modification is likely to improve both cognitive abilities and attentional biases present in cancer.

[0545] F.CAU or digital control

[0546] The usual care (CAU) control group may complete only the assessment and will not use the study app. The digital control app group will download the digital control app. They will complete a version of the task designed to not work in the study app. This will include choosing between a set of neutral words based solely on personal preference and will not include any attentional bias capturing stimuli. Additionally, all instances of multistable perception will be removed, including removal of all auditory elements.

[0547] G. Research reasons

[0548] Multimodal multistable bias modification is a novel intervention that uses the principles of multimodal neural enrichment tasks (M-NET) to reduce cancer-related symptoms. Attentional biases to various attention-capturing stimuli can exacerbate a variety of symptoms in many different indications. For example, in some conditions, patients pay more attention to pain-related stimuli, which can lead to hypersensitization. Similarly, hypersensitization to threat-related stimuli can exacerbate anxiety.

[0549] In multimodal multistable bias modification, users are trained to redirect their attention to positive stimuli rather than stimuli that may cause them distress, such as pain or threat-related stimuli. This is done in a novel format, utilizing multistable perception. Visual multistable perception in the form of monocular rivalry is used to implicitly retrain the attention bias. Simultaneously, auditory multistable perception in the form of binaural beats will be used to target fatigue symptoms and work in tandem to enhance the attention bias component.

[0550] The purpose of the proposed study is to evaluate the preliminary effects of the DiNaMo component (the research app) on measures of attention bias, attention impairment, and related outcomes (overall quality of life [QoL]) in multiple conditions, such as cancer. Results from this study could be used as components of future digital therapeutics.

[0551] H.CT-100 Platform

[0552] The CT-100 platform provides interactive software-based therapeutic components that can be used as part of multimodal treatments in future software-based prescription digital therapeutics. One category of CT-100 components is the DiNaMo component. The DiNaMo component targets key neural systems (including but not limited to systems related to sensation, perception, emotion, pain, attention, cognitive control, social interaction, and self-processing) to optimally improve the health of participants.

[0553] 3. Goals and End Points

[0554] The research objectives are:

[0555] ●Evaluate trends in effects on pain interference, cognition, and related outcomes (attention bias and global QoL) compared with usual care (CAU) or a digital control group

[0556] ● Explore the feasibility of conducting a digital multimodal multistable bias-modified visual search task (research app) at home, including participants’ engagement and experience with the research app

[0557] ●Evaluate the safety of research applications

[0558] The study endpoints correspond to the endpoints provided in Example 1.

[0559] 4. Study Design

[0560] A. Scientific Principles of Research Design

[0561] This study aimed to evaluate the preliminary effects of the multimodal multistable bias modification CT-100 component (research application) on attentional bias and attentional cognitive deficits compared with CAU or digital controls.

[0562] Participants will be evaluated based on validated standard participant scoring outcomes. Participant engagement with the study app will be assessed based on participant usage data captured within the study app. Participant safety will also be assessed throughout the duration of the study. The scales and assessments are described herein.

[0563] B. Study End Definition

[0564] The study end date is defined as the last contact date or last contact attempt date for the last participant who completes or withdraws from the study. For the purposes of this study, participants who complete the trial assessment on Day 21 (+3) (Week 3) will be defined as trial completers.

[0565] 6. Study interventions and concomitant treatments

[0566] A. Research Intervention Implemented

[0567] The CT-100-D-004 research application (e.g., Application 125) will administer the research intervention to participants.

[0568] B.CT-100

[0569] The study intervention being evaluated is the Multimodal Multistable Bias Modification CT-100 component, a digital mobile application. Participants randomized to this group will download and install the study application onto their smartphone at the baseline visit (Day 1) and perform Multimodal Multistable Bias Modification training daily using the study application during the 2-8 week intervention period.

[0570] C. Control

[0571] Participants randomized to CAU or the digital control group will complete study assessments only during the 2-8 week intervention period. The digital control group will download the digital control app. They will complete a version of the task designed to not work in the study app. This will include choosing between a set of neutral words based solely on personal preference and will not include any attentional bias capturing stimuli. In addition, all instances of multistable perception will be removed, including removal of all auditory elements.

[0572] D. Preparation / Handling / Storage / Responsibility

[0573] Detailed instructions for downloading, installing, activating, using, and disposing of Research Applications are described in the CT-100-D-004 Research Applications Field Guide.

[0574] In general:

[0575] 1. Only participants enrolled in the study may receive the research intervention.

[0576] 2. On-site personnel must confirm download and activation of the study app.

[0577] 3. The study app will automatically become inactive after the end of Weeks 2-8. Participants who complete the study or terminate the study early will be notified by site personnel to uninstall the study app.

[0578] E. Concomitant treatment

[0579] Participants will continue to use prescribed therapy during their participation in this study. Participants will self-report any changes in all concomitant medications related to the primary indication or that are psychoactive at the end of the follow-up period.

[0580] 7. Research Evaluation and Procedures

[0581] The study assessment and procedures (including their timing) are summarised in the SoA and in Example 1 above.

[0582] 8. Statistical considerations

[0583] The statistical considerations correspond to those provided above with respect to Example 1.

[0584] 9. Conclusion

[0585] Based on the results of Example 1, it is expected that the treated individual will have an improvement in at least one indication-related symptom, as measured by the performance metrics provided herein. It is expected that the improvement in at least one indication-related symptom in the individual receiving the application is statistically significant relative to any improvement observed in the corresponding indication-related symptom in the individual receiving the digital control or CAU.

[0586] C. Network and computing environment

[0587] Various operations described herein can be implemented on a computer system. Fig. 9 A simplified block diagram of a representative server system 900, a client computer system 914, and a network 926 that can be used to implement certain embodiments of the present disclosure is shown. In various embodiments, the server system 900 or a similar system can implement the services or servers described herein or portions thereof. The client computer system 914 or a similar system can implement the clients described herein. The system 100 described herein can be similar to the server system 900. The server system 900 can have a modular design that combines multiple modules 902 (e.g., blades in a blade server embodiment); although two modules 902 are shown, any number of modules can be provided. Each module 902 can include a processing unit 904 and a local storage device 906.

[0588] The processing unit 904 may include a single processor, which may have one or more cores, or multiple processors. In some embodiments, the processing unit 904 may include a general-purpose main processor and one or more special-purpose coprocessors, such as a graphics processor, a digital signal processor, etc. In some embodiments, some or all of the processing units 904 may be implemented using custom circuits, such as application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). In some embodiments, such integrated circuits execute instructions stored on the circuit itself. In other embodiments, the processing unit 904 may execute instructions stored in a local storage device 906. Any type of processor may be included in the processing unit 904 in any combination.

[0589] The local storage device 906 may include volatile storage media (e.g., DRAM, SRAM, SDRAM, etc.) and / or non-volatile storage media (e.g., magnetic disks or optical disks, flash memory, etc.). The storage media incorporated in the local storage device 906 may be fixed, removable, or upgradeable as needed. The local storage device 906 may be physically or logically divided into various subunits, such as system memory, read-only memory (ROM), and permanent storage devices. The system memory may be a read-write memory device or a volatile read-write memory, such as a dynamic random access memory. The system memory may store some or all of the instructions and data required by the processing unit 904 at runtime. The ROM may store static data and instructions required by the processing unit 904. The permanent storage device may be a non-volatile read-write memory device that can store instructions and data even when the module 902 is powered off. The term "storage medium" as used herein includes any medium that can store data indefinitely (susceptible to coverage, electrical interference, power failure, etc.), but does not include carriers and transient electronic signals propagated through wireless or wired connections.

[0590] In some embodiments, the local storage device 906 may store one or more software programs executed by the processing unit 904, such as an operating system and / or programs that implement various server functions (such as the functions of system 100 or any other system described herein, or any other server associated with system 100 or any other system described herein).

[0591] "Software" generally refers to a sequence of instructions that, when executed by processing unit 904, causes server system 900 (or portions thereof) to perform various operations, thereby defining one or more specific machine embodiments that execute and implement the operations of the software program. Instructions may be stored as firmware residing in read-only memory and / or as program code stored in non-volatile storage media that may be read into volatile working memory for execution by processing unit 904. Software may be implemented as a single program or as a collection of separate programs or program modules that interact as desired. From local storage device 906 (or non-local storage device described below), processing unit 904 may retrieve program instructions to be executed and data to be processed in order to perform the various operations described above.

[0592] In some server systems 900, multiple modules 902 may be interconnected via a bus or other interconnect 908, thereby forming a local area network that supports communication between the modules 902 and other components of the server system 900. The interconnect 908 may be implemented using a variety of technologies, including server racks, hubs, routers, etc.

[0593] Wide area network (WAN) interface 910 can provide data communication capabilities between the local area network (e.g., via interconnect 908) and network 926 (e.g., the Internet). Other technologies can be used to communicatively couple the server system to network 926, including wired (e.g., Ethernet, IEEE 802.3 standards) and / or wireless technologies (e.g., Wi-Fi, IEEE 802.11 standards).

[0594] In some embodiments, the local storage device 906 is intended to provide working memory for the processing unit 904, providing fast access to programs and / or data to be processed while reducing traffic on the interconnect 908. Storage of large amounts of data can be provided on a local area network through one or more mass storage subsystems 912 that can be connected to the interconnect 908. The mass storage subsystem 912 can be based on magnetic, optical, semiconductor or other data storage media. Direct attached storage, storage area networks, network attached storage, etc. can be used. Any data storage or other data collection generated, used or maintained by a service or server described herein can be stored in the mass storage subsystem 912. In some embodiments, additional data storage resources can be accessed (possibly with increased latency) through the WAN interface 910.

[0595] The server system 900 can operate in response to requests received via the WAN interface 910. For example, one of the modules 902 can implement monitoring functions and assign discrete tasks to other modules 902 in response to received requests. Work distribution techniques can be used. When processing a request, the result can be returned to the requester via the WAN interface 910. Such operations can usually be automated. In addition, in some embodiments, the WAN interface 910 can connect multiple server systems 900 to each other, thereby providing an extensible system capable of managing a large number of activities. Other technologies for managing server systems and server farms (collaborative server system collections) can be used, including dynamic resource allocation and reallocation.

[0596] The server system 900 may interact with various user-owned or user-operated devices via a wide area network, such as the Internet. Fig. 9 9 shows an example of a user-operated device, namely a client computing system 914. The client computing system 914 can be implemented as, for example, a consumer device such as a smartphone, other mobile phones, a tablet computer, a wearable computing device (e.g., a smart watch, glasses), a desktop computer, a laptop computer, etc.

[0597] For example, client computing system 914 may communicate via WAN interface 910. Client computing system 914 may include computer components such as processing unit 916, storage device 918, network interface 920, user input device 922, and user output device 924. Client computing system 914 may be a computing device implemented in a variety of form factors, such as a desktop computer, a laptop computer, a tablet computer, a smartphone, other mobile computing devices, a wearable computing device, etc.

[0598] The processing unit 916 and the storage device 918 may be similar to the processing unit 904 and the local storage device 906 described above. Appropriate devices may be selected based on the requirements to be arranged on the client computing system 914. For example, the client computing system 914 may be implemented as a "thin" client or a high-performance computing device with limited processing capabilities. The client computing system 914 may be equipped with program code executable by the processing unit 916 to implement various interactions with the server system 900.

[0599] The network interface 920 may provide a connection to a network 926, such as a wide area network (e.g., the Internet), to which the WAN interface 910 of the server system 900 is also connected. In various embodiments, the network interface 920 may include a wired interface (e.g., Ethernet) and / or a wireless interface implementing various RF data communication standards, such as Wi-Fi, Bluetooth, or a cellular data network standard (e.g., 3G, 4G, LTE, etc.).

[0600] The user input device 922 may include any device (or devices) via which a user may provide signals to the client computing system 914, which the client computing system 914 may interpret as indicating a particular user request or information. In various embodiments, the user input device 922 may include any or all of a keyboard, a touch pad, a touch screen, a mouse or other pointing device, a scroll wheel, a click wheel, a dial, a button, a switch, a keypad, a microphone, and the like.

[0601] User output device 924 may include any device via which client computing system 914 can provide information to a user. For example, user output device 924 may include a display-to-display image generated by or transmitted to client computing system 914. Displays may incorporate various image generation technologies, such as liquid crystal displays (LCDs), light emitting diode (LED) displays (including organic light emitting diodes (OLEDs)), projection systems, cathode ray tubes (CRTs), etc.), as well as supporting electronic devices (e.g., digital-to-analog converters or analog-to-digital converters, signal processors, etc.). Some embodiments may include devices (such as touch screens) that function as both input and output devices. In some embodiments, other user output devices 924 may be provided in addition to or in place of a display. Examples include indicator lights, speakers, tactile "display" devices, printers, etc.

[0602] Some embodiments include electronic components, such as microprocessors, storage devices, and memories, which store computer program instructions in computer-readable storage media. Many of the features described in this specification can be implemented as processes, which are specified as a set of program instructions encoded on a computer-readable storage medium. When these program instructions are executed by one or more processing units, they cause the processing units to perform various operations indicated in the program instructions. Examples of program instructions or computer codes include machine codes, such as machine codes generated by a compiler, and files including higher-level codes executed by a computer, electronic component, or microprocessor using an interpreter. Through appropriate programming, processing units 904 and 916 can provide various functions for server system 900 and client computing system 914, including any functions or other functions performed by a server or client as described herein.

[0603] It should be understood that the server system 900 and the client computing system 914 are illustrative, and there may be changes and modifications. The computer system used in conjunction with the embodiments of the present disclosure may have other functions not specifically described herein. In addition, although the server system 900 and the client computing system 914 are described with reference to specific blocks, it should be understood that these blocks are defined for the convenience of description and are not intended to imply a specific physical arrangement of component parts. For example, different blocks may but need not be located in the same facility, the same server rack, or the same motherboard. In addition, blocks do not have to correspond to physically different components. Blocks can be configured to perform various operations, such as by programming a processor or providing appropriate control circuits, and various blocks may or may not be reconfigured, depending on how the initial configuration is obtained. The embodiments of the present disclosure can be implemented in various devices, including electronic devices implemented using any combination of circuits and software.

[0604] Although the present disclosure has been described with respect to specific embodiments, it will be appreciated by those skilled in the art that various modifications may be made. Embodiments of the present disclosure may be implemented using various computer systems and communication technologies, including but not limited to the specific examples described herein. Embodiments of the present disclosure may be implemented using any combination of dedicated components and / or programmable processors and / or other programmable devices. The various processes described herein may be implemented on the same processor or different processors in any combination. When a component is described as being configured to perform certain operations, such configurations may be implemented by, for example, designing an electronic circuit to perform the operation, by programming a programmable electronic circuit (e.g., a microprocessor) to perform the operation, or any combination thereof. In addition, although the above-described embodiments may refer to specific hardware and software components, it will be appreciated by those skilled in the art that different combinations of hardware and / or software components may also be used, and specific operations described as being implemented in hardware may also be implemented in software, and vice versa.

[0605] Computer programs incorporating various features of the present disclosure may be encoded and stored on a variety of computer-readable storage media; suitable media include disks or tapes, optical storage media (e.g., compact disks (CDs) or digital versatile disks (DVDs), flash memory, and other non-transitory media). Computer-readable media encoded with program code may be packaged with compatible electronic devices, or the program code may be provided separately from the electronic device (e.g., via Internet download or as a separately packaged computer-readable storage medium).

[0606] Therefore, although the disclosure has been described with respect to particular embodiments, it should be understood that the disclosure is intended to cover all modifications and equivalents within the scope of the following claims.

Claims

1. A method of presenting multimodal stimulation to address symptoms associated with a disorder, comprising: To address a condition of the user, identifying, by a computing system, (i) a first visual stimulus associated with the condition and (ii) a second visual stimulus; presenting, by the computing system, via a display, the first visual stimulus at least partially overlapping the second visual stimulus to induce the user to interact with the display; detecting, by the computing system, a response identifying an interaction associated with one of the first visual stimulus or the second visual stimulus; generating, by the computing system, auditory stimulation to include one or more portions indicative of feedback based on the response; as well as The auditory stimulus is played by the computing system via a transducer to provide the feedback to the user regarding the response.

2. The method of claim 1 , further comprising determining, by the computing system, that the response is correct to disassociate the user from the condition based on the interaction associated with the second visual stimulus, and in, Generating the auditory stimulation further includes adding at least a portion to the auditory stimulation to provide positive reinforcement in response to determining that the response is correct.

3. The method of claim 1 , further comprising determining, by the computing system, that the response is incorrect based on the interaction associated with the first visual stimulus associated with the condition, and in, Generating the auditory stimulus further includes removing at least a portion from the auditory stimulus to provide a negative penalty in response to determining that the response is incorrect.

4. The method of claim 1 , further comprising: assigning, by the computing system, (i) the first visual stimulus to a first type of interaction, and (ii) assigning the second visual stimulus to a second type of interaction, and in, Presenting via the display further includes presenting (i) the first visual stimulus having a first indicator to identify the first type of interaction, and (ii) the second visual stimulus having a second indicator to identify the second type of interaction.

5. The method according to claim 1, further comprising: selecting, by the computing system, a difficulty level from a plurality of difficulty levels based on a correct response rate from a previous presentation of the visual stimulus, each of the plurality of difficulty levels defining one or more visual features; as well as The one or more visual features are used to modify, by the computing system, presentation of the first visual stimulus and the second visual stimulus in accordance with the difficulty level.

6. The method according to claim 1, wherein: Generating the auditory stimulation further comprises generating the auditory stimulation to include (i) a first element to be played to a first ear of the user and (ii) a second element to be played to a second ear of the user, and Wherein playing via the transducer further comprises providing the first element to the first ear of the user via a first speaker and providing the second element to the second ear via a second speaker.

7. The method according to claim 1, wherein: The interaction includes: (i) orientation of the display toward a side corresponding to one of a first side associated with the first visual stimulus or a second side associated with the second visual stimulus.

8. The method of claim 1, further comprising modifying, by the computing system, a visual characteristic of one of the first visual stimulus or the second visual stimulus based on the response.

9. The method according to claim 1, wherein: Playing the auditory stimulus further includes playing one of the one or more portions of the auditory stimulus at least partially concurrently with the presentation of the first visual stimulus and the second visual stimulus.

10. The method of claim 1, further comprising receiving, by the computing system via an interface, a selection by the user of at least one characteristic from a plurality of characteristics for auditory stimulation, and in, Generating the auditory stimulation further comprises generating the auditory stimulation according to the at least one characteristic.

11. The method according to claim 1, further comprising: receiving, by the computing system via an interface, a list identifying a plurality of words, the plurality of words including a first subset of words and a second subset of words associated with the condition; as well as Wherein, to address the condition, identifying further comprises selecting the first visual stimulus from the first subset of words and selecting the second visual stimulus from the second subset of words.

12. The method according to claim 1, wherein: At least partially concurrently with the treatment session, the user is taking medication to address the disease associated with at least one of cancer or multiple sclerosis.

13. A system for presenting multimodal stimulation to alleviate symptoms associated with a disorder, comprising: A computing system having one or more processors coupled to a memory, the computing system being configured to: To address a condition of the user, identifying (i) a first visual stimulus associated with the condition and (ii) a second visual stimulus; presenting, via a display, the first visual stimulus at least partially overlapping the second visual stimulus to induce the user to interact with the display; detecting a response identifying an interaction associated with one of the first visual stimulus or the second visual stimulus; generating an auditory stimulus to include one or more portions indicative of feedback based on the response; as well as The auditory stimulus is played via a transducer to provide the feedback to the user regarding the response.

14. The system according to claim 13, wherein: The computing system is further configured to: determining that the response is correct to disassociate the user from the condition based on the interaction associated with the second visual stimulus, and In response to determining that the response is correct, at least a portion is added to the auditory stimulus to provide positive reinforcement.

15. The system of claim 13, wherein: The computing system is further configured to: determining that the response is incorrect based on the interaction associated with the first visual stimulus associated with the condition, and In response to determining that the response is incorrect, at least a portion is removed from the auditory stimulus to provide a negative penalty.

16. The system of claim 13, wherein: The computing system is further configured to: assigning (i) the first visual stimulus to a first type of interaction, and (ii) the second visual stimulus to a second type of interaction, and Presenting (i) the first visual stimulus having a first indicator to identify the first type of interaction, and (ii) the second visual stimulus having a second indicator to identify the second type of interaction.

17. The system of claim 13, wherein: The computing system is further configured to: selecting a difficulty level from a plurality of difficulty levels based on a correct response rate from a previous presentation of the visual stimulus, each of the plurality of difficulty levels defining one or more visual features; as well as The presentation of the first visual stimulus and the second visual stimulus is modified using the one or more visual features according to the difficulty level.

18. The system of claim 13, wherein: The computing system is further configured to: generating the auditory stimulation to include (i) a first element to be played to a first ear of the user and (ii) a second element to be played to a second ear of the user, and The first element is provided to the first ear of the user via a first speaker, and the second element is provided to the second ear via a second speaker.

19. The system of claim 13, wherein: The interaction includes: (i) orientation of the display toward a side corresponding to one of a first side associated with the first visual stimulus or a second side associated with the second visual stimulus.

20. The system of claim 13, wherein: The computing system is further configured to modify a visual characteristic of one of the first visual stimulus or the second visual stimulus based on the response.

21. The system of claim 13, wherein: The computing system is further configured to play one of the one or more portions of the auditory stimulus at least partially concurrently with the presentation of the first visual stimulus and the second visual stimulus.

22. The system of claim 13, wherein: The computing system is further configured to: receiving, via an interface, a selection by the user of at least one characteristic from a plurality of characteristics for auditory stimulation, and The auditory stimulus is generated according to the at least one characteristic.

23. The system of claim 13, wherein: The computing system is further configured to: receiving, via an interface, a list identifying a plurality of words, the plurality of words including a first subset of words and a second subset of words associated with the condition; as well as The first visual stimulus is selected from the first subset of words, and the second visual stimulus is selected from the second subset of words.

24. The system of claim 13, wherein: At least partially concurrently with the course of treatment, the user is taking medication to address the condition associated with at least one of cancer or multiple sclerosis.

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