A system and method for delivering sensory stimuli during sleep based on demographic information.

Abstract

The present disclosure relates to delivering sensory stimuli to a user during a sleep session. In some embodiments, a sensor is configured to generate an output signal conveying information about the user's brain activity during the sleep session. A sensory stimulator is configured to provide sensory stimuli to the user during the sleep session. One or more processors are configured to determine a demographic group for the user, select a stimulation parameter model associated with the user's demographic group from a set of stimulation parameter models associated with different demographic groups, and control the one or more sensory stimulators to deliver sensory stimuli to the user based on the output signal and the stimulation parameter model for the user's demographic group.

Description

Technical Field

[0001] The present disclosure relates to systems and methods for delivering sensory stimulation during sleep based on demographic information.

Background Art

[0002] Systems for monitoring sleep during sleep and delivering sensory stimulation to a user are known. Electroencephalogram (EEG) sensor-based sleep monitoring and sensory stimulation systems are known. These systems do not take into account changes in user characteristics such as age and demographic parameters. As a result, the user may receive less stimulation than otherwise, or the timing of the stimulation may not appropriately correspond to their individual sleep patterns. Therefore, there is a need for a system that can adjust the stimulation for a subject during sleep depending on the demographic characteristics of the subject (even if an explicit designation of a demographic group is not yet available to the user).

Summary of the Invention

[0003] Accordingly, one or more aspects of the present disclosure relate to a system configured to deliver sensory stimuli to a user during a sleep session. The system includes one or more sensors, one or more sensory stimulators, one or more processors, and / or other components. One or more sensors are configured to generate output signals that convey information about the user's brain activity during a sleep session. One or more sensory stimulators are configured to provide sensory stimuli to the user during a sleep session. One or more processors are coupled to one or more sensors and one or more sensory stimulators. One or more processors are configured to consist of machine-readable instructions. One or more processors are configured to determine a demographic group about the user based on the output signals generated during a first sleep session (or a portion thereof). One or more processors are configured to select a stimulus parameter model associated with the user's demographic group from a set of stimulus parameter models associated with different demographic groups during a sleep session. One or more processors are configured to control one or more sensory stimulators during a second sleep session (or a portion thereof) to deliver sensory stimuli to the user based on a stimulus parameter model for the user's demographic group and output signals generated during the second portion of the sleep session. The second sleep session follows the first sleep session in time. In some embodiments, one or more processors are configured to use output signals generated during the first sleep session to determine the demographic group of the user, based on the lack of explicit demographic group designation for the user.

[0004] Another aspect of this disclosure relates to a method for delivering sensory stimuli to a user during a sleep session using a delivery system. The delivery system includes one or more sensors, one or more sensory stimulators, one or more processors, and / or other components. The method includes using one or more sensors to generate output signals that convey information about the user's brain activity during a sleep session. The method includes using one or more sensory stimulators to deliver sensory stimuli to the user during a sleep session. The method includes using one or more processors to determine a demographic group for the user based on the output signals generated during a first sleep session. The method includes using one or more processors to select a stimulus parameter model associated with the user's demographic group from a set of stimulus parameter models associated with different demographic groups during a sleep session. The method includes using one or more processors to control one or more sensory stimulators to deliver sensory stimuli to the user during a second sleep session based on the stimulus parameter model for the user's demographic group and the output signals generated during the second part of the sleep session. The second part of the sleep session follows the first part of the sleep session in time. In some embodiments, the method includes determining a demographic group for a user based on the lack of explicit demographic group designation for the user, using output signals generated during a first portion of a sleep session.

[0005] A further aspect of this disclosure relates to a system for delivering sensory stimuli to a user during a sleep session. The system includes means for generating output signals that convey information about the user's brain activity during a sleep session. The system includes means for providing sensory stimuli to the user during a sleep session. The system includes means for determining a demographic group for the user based on output signals generated during a first part of a sleep session. The system includes means for selecting a stimulus parameter model associated with the user's demographic group from a set of stimulus parameter models associated with different demographic groups during a sleep session. The system includes means for controlling the means for providing sensory stimuli to deliver sensory stimuli to the user during a second part of a sleep session, based on the stimulus parameter model for the user's demographic group and output signals generated during the second part of the sleep session. The second part of the sleep session follows the first part of the sleep session in time. In some embodiments, the output signals generated during the first part of the sleep session are used to determine a demographic group for the user based on the lack of explicit demographic group designation for the user.

[0006] These and other purposes, configurations, and features of this disclosure, the methods and functions of the relevant elements of the structure, and the combinations and manufacturing economies of the parts will become clearer after considering the following description and the appended claims with reference to the appended drawings. All of the appended drawings constitute part of this specification, and herein, equivalent reference numbers point to the corresponding parts through the various drawings. However, it should be expressly understood that the drawings are for illustrative and descriptive purposes only and are not intended as definitions of limitations of this disclosure. [Brief explanation of the drawing]

[0007] [Figure 1] This is a schematic diagram of a system configured to deliver sensory stimuli to a user during a sleep session according to one or more embodiments.

[0008] [Figure 2] The effects of sensory stimulation using prior art systems on younger and older demographic groups are illustrated.

[0009] [Figure 3] This diagram illustrates the results of an analysis of the number of tones delivered by conventional systems for various demographic characteristics.

[0010] [Figure 4] The diagram illustrates the actions performed by the demographic component, model component, and system control component according to one or more embodiments.

[0011] [Figure 5] The process for determining and / or adjusting a stimulus parameter model is illustrated by performing a simulation of sensory stimuli for users in a specific demographic group, according to one or more embodiments.

[0012] [Figure 6] This diagram illustrates exemplary optimization of stimulus control parameter values ​​for a demographic stimulus parameter model according to one or more embodiments.

[0013] [Figure 7] The diagram illustrates a method for delivering sensory stimuli to a user during a sleep session, according to one or more embodiments. [Modes for carrying out the invention]

[0014] As used herein, singular expressions include plural references unless the context explicitly indicates otherwise. As used herein, the term “or” means “and / or” unless the context explicitly indicates otherwise. As used herein, the expression “coupled” means that two or more parts or components are joined or acted upon by one or more intermediate parts or components, directly or indirectly, i.e., insofar as a link is created. As used herein, “directly coupled” means that two elements are in direct contact with each other. As used herein, “fixedly coupled” or “fixed” means that two components are coupled so as to move as one while maintaining a constant orientation relative to each other.

[0015] As used herein, the term “unitary” means that it is produced as a single molded article or unit. That is, a component that includes parts that are produced separately and then joined together as a unit is not a “unitary” component or body. As used herein, the expression “engage” between two or more parts or components means that the parts exert force against each other directly or through one or more intermediate parts or components. As used herein, the term “number” means one or more integers (i.e., plural).

[0016] For example, the directional terms used herein, such as top, bottom, left, right, up, down, front, back, and their derivatives, relate to the orientation of elements shown in the drawings and do not limit the claims unless expressly referenced in the claims.

[0017] Figure 1 is a schematic diagram of a system 10 configured to deliver sensory stimulation to user 12 during a sleep session. Changes in sleep architecture, electroencephalogram (EEG) spectral characteristics, slow wave activity, and NREM (non-rapid eye movement) sleep fragmentation can be attributable to demographic characteristics such as age and sex. These changes are substantial. System 10 is configured to take these changes into account when automatically analyzing sleep data and / or when delivering sensory (e.g., auditory) stimulation to enhance slow wave sleep (e.g., as described below). The accumulation of slow wave activity during NREM sleep (cumulative SWA or CSWA) is associated with the restorative value of sleep.

[0018] In brief (details provided below), deep NREM sleep may be detected to increase slow-wave activity (SWA, i.e., EEG power in the 0.5–4 Hz band) and to deliver sensory (e.g., auditory) stimuli. The EEG signal may be filtered through three frequency bands, namely alpha (8–12 Hz), beta (15–30 Hz), and delta (0.5–40 Hz), to obtain mean square (RMS) power values ​​in each of these bands. Detection of sleep micro-arousals and "wake" states is achieved by detecting periods during which the alpha or beta RMS value exceeds a predetermined threshold. If the alpha or beta RMS exceeds the threshold for a period lasting at least (e.g.) 10 seconds, a "wake" state may be detected; otherwise, sleep micro-arousals are detected. The presence of micro-arousals delays the onset of the next auditory stimulus or, in the case of an ongoing stimulus, causes it to be stopped. Deep sleep (e.g., N3 sleep, described below) is detected in response to a delta-RMS exceeding a predetermined threshold for at least a certain threshold duration (e.g., 25 seconds) and in response to the number of slow waves detected within a sliding window of threshold length (e.g., 20 seconds) being higher than a predetermined number of slow waves detected (e.g., 6). Periods not detected as wakefulness or deep sleep are often flagged as light sleep. Auditory and / or other sensory stimuli may be delivered in response to deep sleep continuously detected for at least a threshold duration (e.g., 90 seconds), where the sleep depth (e.g., indicated by the logarithmic ratio between delta and beta power) exceeds a predetermined threshold. Auditory stimuli (e.g.) often include tones separated from each other by constant intervals (e.g., 1 second) (e.g., 50 milliseconds). The volume of each tone is linearly modulated with respect to sleep depth, such that louder (softer) tones are played during deeper (lighter) sleep. Other stimulation modalities include synchronizing with the slow wave phase and delivering stimuli in the block.

[0019] In conventional systems, the effect of stimulation (tone) on slow-wave activity enhancement decreases with age. For example, Figure 2 illustrates the effect of sensory stimulation from conventional systems on a younger demographic group 200 and an older demographic group 202. A simulated sleep session 204 (without stimulation) is compared to a stimulated session 206 for each group. The effects of stimulation from these systems on SWA208 and CSWA210 are shown. The average number of tones per unit time 212 and the average volume in dB 214 are also shown. As shown in Figure 2, SWA208, CSWA210, average number of tones per unit time 212, and average volume 214 all decrease for the older demographic group 202.

[0020] Figure 3 illustrates the results of an analysis of the number of tones 300 delivered by a conventional system for various demographic characteristics. Specifically, Figure 3 illustrates the distribution of the number of tones 302, 304 for age groups 306, 308, 310, 312 (defined in this example as decades) and sexes 314, 316. As shown in Figure 3, the number of tones decreases with increasing age for both men and women. However, in the case of men, the decrease is more pronounced. For example, as shown in Figure 3, the median number of tones for men aged 50 and over is only 400, which is insufficient to produce CSWA augmentation. In some embodiments, the system 10 is configured to reduce or prevent this decrease in stimulation and the ineffectiveness of subsequent treatment by adjusting the sensory stimulation parameters depending on the user's demographic characteristics.

[0021] Returning to Figure 1, in some embodiments, the system 10 includes one or more of the following components: a sensor 14, a sensory stimulator 16, an external resource 18, a processor 20, an electronic storage device 22, a user interface 24, and / or other components. In some embodiments, the system 10 is configured so that a user 12 provides the system 10 with demographic information, for example, using the user interface 24. The demographic information includes age, age range, sex, ethnicity, marital status (e.g., which may guide volume levels to minimize partner disturbance), work shift (e.g., daytime or nighttime, which may be useful in guiding the timing and volume of stimulation in light of circadian factors affecting arousal), and / or other demographic information. The demographic information indicates the demographic group to which the user 12 belongs (e.g., age-based, sex-based, etc.). The demographic group may be determined by the system 10 based on age, sex, ethnicity, and / or other demographic characteristics. System 10 is configured to select a stimulus parameter model relevant to the user's demographic group from a set of stimulus parameter models related to different demographic groups. The stimulus parameter models may be stored, for example, in an electronic memory device 22, in an external resource 18, and / or elsewhere. If demographic information is not provided by the user 12, System 10 is configured to automatically determine which demographic group the user 12 belongs to. System 10 is configured to control the sensory stimulator 16 to deliver sensory stimuli to the user based on the stimulus parameter model for the user's demographic group and the output signals from the sensor 14 generated during the sleep session. This is further described below.

[0022] Sensor 14 is configured to generate an output signal that conveys information related to the brain activity and / or other activities of user 12. In some embodiments, sensor 14 is configured to generate an output signal that conveys information related to brain activity such as slow-wave activity in user 12. In some embodiments, the information related to the brain activity and / or other activities of user 12 is information related to slow-wave activity. In some embodiments, sensor 14 is configured to generate an output signal that conveys information related to the stimuli provided to user 12 during a sleep session. In some embodiments, the information in the output signal from sensor 14 is used to control the sensory stimulation device 16 to provide a sensory stimulus to user 12 (as described below).

[0023] Sensor 14 may include one or more sensors that generate an output signal that directly conveys information related to the brain activity of user 12. For example, sensor 14 may include an electroencephalogram (EEG) electrode configured to detect electrical activity along the scalp of user 12 resulting from the flow of current within the brain of user 12. Sensor 14 may include one or more sensors that generate an output signal that indirectly conveys information related to the brain activity of user 12. For example, one or more sensors 14 may be a heart rate sensor that generates an output based on the heart rate of user 12 (e.g., sensor 14 may be configured to be placed on the chest of user 12 and / or configured as a bracelet on the wrist of user 12 and / or placed on other limbs of user 12), the movement of user 12 (e.g., sensor 14 may include an accelerometer that can be supported by a wearable such as a bracelet around the wrist and / or ankle of user 12, where sleep may be analyzed using an actigraph signal), the respiration of user 12, and / or other characteristics of user 12.

[0024] In some embodiments, sensor 14 may include an electroencephalogram(EEG) electrode, an electrooculogram(EOG) electrode, an actigraphy sensor, an electrocardiogram(EKG) electrode, a respiration sensor, a pressure sensor, a vital signs camera, a photoplethysmogram(PPG) sensor, a functional near-infrared sensor(fNIR), a temperature sensor, a microphone, and / or other sensors configured to generate an output signal regarding the brain activity of user 12 and / or the stimuli provided to user 12 (e.g., the amount, frequency, intensity, and / or other characteristics of the stimuli), and / or one or more of the other sensors. Although sensor 14 is shown in a single location close to user 12, this is not intended to be limiting. Sensor 14 may be, for example, connected (in a removable manner) to the clothing of user 12, worn by user 12 (such as a headband, wristband, etc.), positioned to point to user 12 while user 12 is sleeping (such as a camera that transmits an output signal regarding the movement of user 12), connected to the bed and / or other furniture on which user 12 is sleeping, located in a plurality of locations such as within (or communicating with) the sensory stimulation device 16, and / or located in other locations.

[0025] In Figure 1, the sensor 14, sensory stimulator 16, processor 20, electronic memory 22, and user interface 24 are shown as separate entities. This is not intended to be limiting. Some and / or all of the components of system 10 and / or other components may be grouped into one or more single devices. For example, these and / or other components may be included in a headset and / or other clothing worn by user 12. Such a headset may include, for example, sensing electrodes, reference electrodes, one or more devices associated with the EEG, means for delivering auditory stimuli (e.g., wired and / or wireless audio devices and / or other devices), and one or more audio speakers. In this example, the audio speakers may be placed in and / or near and / or elsewhere in user 12's ears. The reference electrodes may be placed behind and / or elsewhere in the user's ears. In this example, the sensing electrodes may be configured to generate output signals that transmit information and / or other information about user 12's brain activity. The output signal may be transmitted wirelessly and / or via wire to a processor (e.g., processor 20 shown in Figure 1), a computing device which may or may not include a processor (e.g., a bedside laptop), and / or other devices. In this example, acoustic stimuli may be delivered to the user 12 via a wireless audio device and / or speaker. In this example, the sensing electrode, reference electrode, and EEG device may be represented, for example, by the sensor 14 in Figure 1. The wireless audio device and speaker may be represented, for example, by the sensory stimulation device 16 shown in Figure 1. In this example, the computing device may include the processor 20, electronic memory 22, user interface 24, and / or other components of the system 10 shown in Figure 1.

[0026] The sensory stimulator 16 is configured to provide sensory stimulation to the user 12. The sensory stimulator 16 is configured to provide the user 12 with auditory stimulation, visual stimulation, somatosensory stimulation, electrical stimulation, magnetic stimulation, and / or other sensory stimulation before a sleep session, during a sleep session, and / or at other times. In some embodiments, a sleep session may include any period of time when the user 12 is asleep and / or trying to sleep. A sleep session may include nighttime sleep, naps, and / or other sleep sessions. For example, the sensory stimulator 16 may be configured to provide stimulation to the user 12 during a sleep session to facilitate transitions to deeper and lighter sleep stages, to maintain sleep at a particular stage, to enhance the restorative effect of sleep, and / or for other purposes. In some embodiments, the sensory stimulator 16 may be configured such that facilitating transitions between deeper and lighter sleep stages includes reducing sleep slow waves in the user 12, and facilitating transitions between lighter and deeper sleep stages includes increasing sleep slow waves.

[0027] The sensory stimulation device 16 is configured to facilitate transitions between sleep stages, maintain sleep in specific stages, and / or enhance the sleep-restoring effect through non-invasive brain stimulation and / or other methods. The sensory stimulation device 16 may be configured to facilitate transitions between sleep stages, maintain sleep in specific stages, and / or enhance the sleep-restoring effect through non-invasive brain stimulation using auditory stimulation, electrical stimulation, magnetic stimulation, visual stimulation, somatosensory stimulation, and / or other sensory stimulation. Auditory stimulation, electrical stimulation, magnetic stimulation, visual stimulation, somatosensory stimulation, and / or other sensory stimulation may include auditory stimulation, visual stimulation, somatosensory stimulation, electrical stimulation, magnetic stimulation, combinations of different types of stimulation, and / or other stimulation. Auditory stimulation, electrical stimulation, magnetic stimulation, visual stimulation, somatosensory stimulation, and / or other sensory stimulation may include smell, sound, visual stimulation, touch, taste, somatosensory stimulation, tactile stimulation, electrical stimulation, magnetic stimulation, and / or other stimulation. Sensory stimulation may have intensity, timing, and / or other characteristics. For example, acoustic tones may be provided to user 12 to enhance the sleep-restoring effect on user 12. The acoustic tones may include one or more sets of tones of a determined length, separated from each other by intervals between tones. The volume (e.g., intensity) of individual tones may be modulated based on sleep depth and other factors (as described herein), such that louder tones are played during deeper sleep and softer tones are played during lighter sleep. The length (e.g., timing) of individual tones and / or the intervals (e.g., timing) between tones may also be adjusted depending on whether user 12 is in deeper or lighter sleep. This example is not intended to be limiting. Examples of sensory stimulation devices 16 may include one or more of the following: a sound source, a speaker, a music player, a tone generator, a vibrator (e.g., such as a piezoelectric element) for delivering vibrational stimulation, a coil that generates a magnetic field for directly stimulating the cerebral cortex, one or more photogenerators or lamps, an air freshener dispenser, and / or other devices. In some embodiments, the sensory stimulation device 16 is configured to adjust the intensity, timing, and / or other parameters of the stimulation provided to the user 12 (as described below, for example).

[0028] External resource 18 includes information sources (e.g., databases, websites, etc.), external entities participating in system 10 (e.g., one or more external sleep monitoring devices, healthcare provider's medical record systems, etc.), and / or other resources. For example, external resource 18 may include historical sleep depth information sources for a group of users, demographic information sources for a group of users, and / or other information sources. Historical sleep depth information for a group of users may relate to the brain activity of a group of users indicating sleep depth over time during sleep for that group of users. In some embodiments, historical sleep depth information for a group of users may relate to demographic information regarding a group of users in a given geographical area, sex, ethnicity, age, and / or other demographic information, physiological information regarding a group of users (e.g., weight, blood pressure, pulse rate, etc.), and / or other information. In some embodiments, this information may indicate whether individual users in a group of users are similar to user 12 demographically, physiologically, and / or otherwise.

[0029] In some embodiments, the external resource 18 includes components that facilitate information communication, one or more servers outside the system 10, a network (e.g., the Internet), electronic storage devices, devices related to Wi-Fi technology, devices related to Bluetooth® technology, data input devices, sensors, scanners, computing devices related to individual users, and / or other resources. In some implementations, some or all of the functionality attributed to the external resource 18 herein may be provided by resources included in the system 10. The external resource 18 may be configured to communicate with the processor 20, user interface 24, sensor 14, electronic storage device 22, sensory stimulator 16, and / or other components of the system 10 via wired and / or wireless connections, via a network (e.g., a local area network and / or the Internet), via cellular technology, via Wi-Fi technology, and / or other resources.

[0030] The processor 20 is configured to provide information processing capabilities in the system 10. Therefore, the processor 20 may include one or more of the following: a digital processor, an analog processor, a digital circuit designed to process information, an analog circuit designed to process information, a state machine, and / or other mechanisms for electronically processing information. Although the processor 20 is shown as a single entity in Figure 1, this is for illustrative purposes only. In some embodiments, the processor 20 may include multiple processing units. These processing units may be physically located within the same device (e.g., a sensory stimulator 16, a user interface 24, etc.), or the processor 20 may represent the processing capabilities of multiple devices working together. In some embodiments, the processor 20 may be a computing device, and / or included within such a computing device, such as a desktop computer, a laptop computer, a smartphone, a tablet computer, a server, and / or other computing device. Such a computing device may run one or more electronic applications having a graphical user interface configured to facilitate user interaction with the system 10.

[0031] As shown in Figure 1, the processor 20 is configured to execute one or more computer program components. The computer program components may include, for example, software programs and / or algorithms that are encoded and / or otherwise embedded in the processor 20. The computer program components may include one or more of the following: a demographic component 30, a model component 32, a tuning component 34, a control component 36, and / or other components. The processor 20 may be configured to execute components 30, 32, 34, and / or 36 by software, hardware, firmware, several combinations of software, hardware, and / or firmware, and / or other mechanisms for configuring the processing capacity on the processor 20.

[0032] Although components 30, 32, 34, and 36 are illustrated in Figure 1 as being juxtaposed within a single processing unit, it should be understood that in embodiments where the processor 20 comprises multiple processing units, one or more of components 30, 32, 34, and / or 36 may be located remotely from the other components. The descriptions of the functionality provided by the different components 30, 32, 34, and / or 36 provided below are for illustrative purposes only and are not intended to be limiting, because any of components 30, 32, 34, and / or 36 may provide more or less functionality than described. For example, one or more of components 30, 32, 34, and / or 36 may be removed, and some or all of their functionality may be provided by the other components 30, 32, 34, and / or 36. As another example, the processor 20 may be configured to run one or more additional components that may perform some or all of the functionality attributable to one of components 30, 32, 34, and / or 36.

[0033] The demographic component 30 is configured to determine the demographic groups of user 12. A demographic group may include groups of individuals linked by one or more common demographic characteristics. For example, a demographic group may include groups of individuals having a common age or age range, a common sex, a common ethnicity, and / or other common demographic characteristics. In this specification, a demographic group is defined by an age range. This is an example and is not intended to be limiting. A demographic group may include any number and types of demographic groups that enable system 10 to function as described herein.

[0034] In some embodiments, the demographic group of user 12 is determined based on inputs and / or selections made by user 12 and / or other users (e.g., the user's caregivers, family members, friends, etc.). The inputs and / or selections may be or relating to the demographic characteristics of user 12 and / or other information. The inputs and / or selections may be made, for example, via the user interface 24 and / or other interfaces. In some embodiments, the demographic component 30 is configured to determine the demographic group of user 12 based on information about user 12 stored in the electronic storage device 22, external resources 18, and / or other information sources.

[0035] In some embodiments, the demographic group of user 12 is determined based on output signals from sensor 14, sensory stimuli delivered to user 12, and / or other information. In some embodiments, the demographic group is determined based on output signals and / or sensory stimuli generated during a first part of a sleep session, and / or one or more previous sleep sessions of user 12. In some embodiments, output signals and / or sensory stimuli generated during a first part of a sleep session and / or previous sleep sessions are used to determine the demographic group for the user based on the lack of explicit demographic group designation for the user (for example, user 12 did not input or select any demographic information via the user interface 24, or the demographic component 30 was unable to retrieve demographic information about user 12 from an electronic storage device, etc.).

[0036] In some embodiments, determining the demographic group of user 12 based on the output signal from sensor 14, the sensory stimulus delivered to user 12, and / or other information includes determining one or more sensory stimulus parameters of the sensory stimulus delivered to user 12. For example, if the demographic group of user 12 is unknown, the control component 36 (described below) may cause the sensory stimulator 16 to deliver a sensory stimulus based on the output signal from sensor 14, according to a predetermined therapy plan (e.g., a baseline or standard therapy plan). The resulting sensory stimulus parameters for the sensory stimulus delivered to user 12 may be compared to known sensory stimulus parameters for various demographic groups that have received therapy according to the same predetermined therapy plan. User 12 may be determined to belong to a particular demographic group in response that the sensory stimulus parameters of the sensory stimulus delivered to user 12 are similar to and / or the same as the sensory stimulus parameters of sensory stimuli typically delivered to users from that particular demographic group. For example, if the sensory stimulation device 16 is a tone generator or includes a tone generator, the sensory stimulation parameters may include the intensity, frequency, timing, duration, amount, and / or other characteristics of the auditory tone delivered to user 12 and / or other users.

[0037] In some embodiments, determining the demographic group of user 12 based on the output signal from sensor 14, sensory stimuli delivered to user 12, and / or other information includes determining one or more brain activity parameters of user 12. User 12's brain activity parameters may be compared to known brain activity parameters typical of individuals from various demographic groups who have received sleep therapy. As described above, if user 12's demographic group is unknown, the control component 36 (described below) may cause the sensory stimulator 16 to deliver sensory stimuli based on the output signal from sensor 14, according to a predetermined therapy plan (e.g., baseline or standard therapy plan). User 12 may be determined to belong to a particular demographic group in response to the fact that user 12's brain activity parameters are similar to and / or the same as the brain activity parameters of a particular demographic group treated with the same predetermined therapy plan. Brain activity parameters may be determined by the demographic component 30 based on the output signal from sensor 14 and / or other information. Brain activity parameters may indicate the user's sleep depth and / or other information. In some embodiments, information in the output signal relating to brain activity indicates sleep depth over time. In some embodiments, information indicating sleep depth over time is information relating to, or includes, slow-wave activity in user 12. In some embodiments, user 12's slow-wave activity may indicate user 12's sleep stage. User 12's sleep stage may be associated with rapid eye movement (REM) sleep, non-rapid eye movement (NREM) sleep, and / or other sleep stages. The sleep stage may be one or more of NREM stages N1, N2, or N3, REM sleep, and / or other sleep stages. In some embodiments, user 12's sleep stage may be one or more of stages S1, S2, S3, or S4. In some embodiments, NREM stages 2 and / or 3 (and / or S3 and / or S4) may be slow-wave (e.g., deep) sleep. In some embodiments, the information relating to brain activity indicating sleep depth over time is one or more additional brain activity parameters and / or relating to such brain activity parameters.

[0038] In some embodiments, information relating to brain activity indicating sleep depth over time is EEG information generated during one or more sleep sessions, and / or includes such EEG information. In some embodiments, brain activity parameters may be determined based on EEG information. In some embodiments, brain activity parameters may be predetermined and may be part of chronological sleep depth information obtained from an external resource 18. In some embodiments, brain activity parameters may be the presence of a specific sleep pattern, such as frequency, amplitude, phase, spindle, K-complex, or sleep slow waves, alpha waves, and / or other features of the EEG signal, and / or are related thereto. In some embodiments, brain activity parameters are determined based on the frequency, amplitude, and / or other features of the EEG signal. In some embodiments, the determined brain activity parameters and / or EEG features may be sleep stages corresponding to the REM and / or NREM sleep stages described above, and / or may indicate them. For example, typical EEG features during NREM sleep include a transition from alpha waves (e.g., approximately 8–12 Hz) to theta waves (e.g., approximately 4–7 Hz) for sleep stage N1, the presence of sleep spindles (e.g., approximately 11–16 Hz) and / or K-complex waves (e.g., similar to sleep slow waves) for sleep stage N2, the presence of delta waves (e.g., approximately 0.5–4 Hz), also known as sleep slow waves, with inter-peak amplitudes greater than approximately 75 uV for sleep stage N3, the presence of light sleep and / or wakefulness, and / or other features. In some embodiments, light sleep may be characterized by the fact that alpha activity (e.g., EEG power in the 8–12 Hz band) is no longer present and slow waves are absent. In some embodiments, slow wave activity is a continuous value that is positive (e.g., EEG power in the 0.4–4 Hz band). In some embodiments, the absence of slow waves indicates light sleep. In addition, spindle activity (EEG power in the 11–16 Hz band) may be high. Deep sleep can be characterized by the fact that delta activity (e.g., EEG power in the 0.5–4 Hz band) is dominant. In some embodiments, EEG power in the delta band and SWA are the same when considering sleep EEG.In some embodiments, information regarding brain activity indicating sleep depth over time includes changes in EEG delta power over time, the amount of micro-awakening in a group of users, other EEG power levels, and / or other parameters.

[0039] The model component 32 is configured to select a stimulus parameter model relevant to the demographic group of user 12. The selection of stimulus parameters is based on a determination made using the demographic component 30 and / or other information to determine which demographic group user 12 belongs to. The stimulus parameter model is selected from a set of stimulus parameter models relevant to different demographic groups (e.g., different age ranges). The stimulus parameter models may be stored, for example, in an electronic memory device 22, an external resource 18, and / or other locations. Once a stimulus parameter model relevant to user 12's demographic group is selected, the control component 36 (described below) is configured to control the stimulator 16 to deliver sensory stimuli to user 12 based on the selected model.

[0040] The operations performed by the demographic component 30, the model component 32, and the control component 36 are illustrated in Figure 4. As shown in Figure 4, the demographic component 30 (Figure 1) may facilitate input of the user's gender and age range 400 (for example). The demographic component 30 may determine the demographic group to which the user belongs 402, and the model component 32 (Figure 1) may select an appropriate stimulus parameter model from the electronic memory device 22 and / or other information sources. Once a stimulus parameter model associated with the user's demographic group is selected, the control component 36 (Figure 1) is configured to control the delivery of sensory stimuli to the user based on the selected model. However, if the user's demographic group is unknown, the control component 36 may trigger the delivery of sensory stimuli 408 based on a sensor (for example, the sensor 14 shown in Figure 1) according to a predetermined therapy plan (e.g., a baseline or standard therapy plan). A user may be determined to belong to a particular demographic group 410, 412 in response to the fact that the user's brain activity parameters or the parameters of sensory stimuli delivered to the user are similar to and / or the same as the brain activity parameters and / or sensory stimuli parameters of a particular demographic group that has been treated with the same prescribed therapy plan.

[0041] Returning to Figure 1, the stimulus parameter model may be, and / or may represent, a relationship between one or more stimulus control parameters and a target variable for a sensory stimulus. The stimulus control parameters may be one or more tunable parameters that are used to control the sensory stimulus delivered to user 12. In some embodiments, the stimulus parameter model may be thought of as analogous to a recipe used when setting the stimulus control parameters when delivering a sensory stimulus to the user. The stimulus control parameters for use in the model may be stimulus control parameters that have a relatively large influence on the target variable compared to other stimulus control parameters. The stimulus control parameters used in the model may be the same or different for individual demographic groups. A given model may vary depending on the target variable for the sensory stimulus (e.g., the stimulus control parameters used in the model may vary, and the relationships between stimulus control parameters may vary). The target variable may be a variable to which the model component 32 and / or tuning component 34 are configured to augment for user 12. The target variable may be determined by the model component 32 and / or adjustment component 34 based on information from previous sleep sessions of user 12 or users demographically similar to user 12, may be determined during the manufacture of the system 10, may be input and / or selected by user 12 and / or other users (e.g., via the user interface 24), and / or may be determined in other ways. In some embodiments, the target variable may be the number of tones delivered to user 12 (e.g., because the number of tones is known to decrease with age in conventional systems, as described above). In some embodiments, the target variable may be one or more target variables.For example, target variables may be the number of tones delivered to user 12, the amount of N3 sleep detected, the average N3 duration, the detected N1 and / or N2 sleep duration, N3 sensitivity and / or specificity, Kappa, wakefulness sensitivity and / or specificity, wakefulness duration detected as N3, REM detection sensitivity and / or specificity, sleep efficiency (e.g., time spent asleep divided by time in bed), sleep maintenance (e.g., sleep bout duration and / or one or more other target variables; a sleep bout is a continuous period of sleep not interrupted by wakefulness (N1, N2, N3, or REM)). The relationship between the target variables and the stimulus control parameters in the model may be linear or nonlinear. Individual stimulus control parameters may be weighted or unweighted.

[0042] The adjustment component 34 is configured to determine and / or adjust the stimulus parameter model within a set of stimulus parameter models. In some embodiments, determining and / or adjusting a set of stimulus parameter models involves obtaining historical brain activity information for a population of users in a given demographic group. As described above, historical brain activity information indicates the sleep depth over time during sleep sessions for a population of users. Determining and / or adjusting a stimulus parameter model involves (i) performing a simulation of sensory stimuli for users in a particular demographic group based on historical brain activity information for users in that demographic group, and (ii) one or more stimulus control parameters. Determining and / or adjusting a stimulus parameter model involves adjusting the stimulus control parameters multiple times between each simulation of the simulation so that the simulation is performed based on stimulus control parameters that have been adjusted multiple times. This involves determining, for each adjustment, the effect of adjusting the stimulus control parameters on a target variable. Based on the effect of the adjustments, the adjustment component 34 is configured to determine a set of stimulus control parameters for a given stimulus parameter model related to a given demographic group. Individually determined and / or adjusted stimulus parameter models are stored as part of a set of stimulus parameter models.

[0043] In some embodiments, the adjustment component 34 is configured to determine and / or adjust the stimulus parameter models within a set of stimulus parameter models, which includes determining which stimulus control parameters have a greater influence on the target variable compared to other stimulus control parameters. The adjustment component 34 may be configured to determine and / or adjust individual stimulus parameter models based on the stimulus control parameters that have a relatively greater influence on the target variable. In some embodiments, stimulus control parameters that have a relatively greater influence on the target outcome variable include delta threshold, slow wave peak threshold, slow wave density threshold, sleep depth threshold, and / or other stimulus control parameters. In some embodiments, for example, the sensory stimulation device includes a tone generator, and the target variable includes a number of tones delivered during a simulated sleep session.

[0044] As a non-limiting example, stimulus control parameters that have a relatively greater influence on the number of tones delivered to user 12 may include a delta threshold for RMS power in the delta (0.5–4 Hz) band above which N3 sleep can be detected, a slow wave peak threshold for the negative peak of slow wave events to be detected as actual slow waves, a slow wave density threshold for the minimum number of detected slow wave events that lead to N3 sleep, and a sleep depth threshold for the log-ratio delta / beta characterizing the sleep depth to which stimuli can be delivered. In this example, demographic groups are defined as men and women within the age groups of 20–40 years, 40–50 years, and 50 years and older. These groups should not be considered limiting. For example, differences within narrower age group ranges may be identified, and / or age may be used as a continuous variable.

[0045] As described above, a model is determined for each demographic group. The model characterizes the number of tones (the target variable in this example) based on configurable (stimulus control) parameters. The number of tones is an example of a target variable (outcome) that may be modeled. Other examples of target variables include SWA, CSWA, and / or other sleep architecture outcomes as described above (e.g., duration of N3 sleep).

[0046] Following this example, Figure 5 illustrates the process of determining and / or adjusting the stimulus parameter model by performing simulations of sensory stimuli for users within a specific demographic group. As shown in Figure 5, sleep EEG data from subjects within a targeted demographic group 500 are processed through a simulator 502 (e.g., adjustment component 34 shown in Figure 1) which determines the outcome 504 (e.g., multiple tones and other target variables, as shown in Figure 5) depending on different combinations of configurable (stimulus control) parameters 506. The configurable parameters 506 are provided as potential components of the model 510 (508). Configurable (stimulus control) parameters 506 that have a greater impact on the outcome 504 (target variables) compared to other configurable parameters 506 are identified based on the simulation and used as part of the model 510 (512). In this example, the number of tones (target variable) in a demographic group of men aged 50 years or older may be modeled by a mixed-effects model, as shown in the lower right section 514 of Figure 5. This model provides an estimate of changes in stimuli (e.g., delivered tone) in response to changes in configurable (stimulus control) parameters that have a relatively large influence. For example, a decrease in units at the delta threshold may increase the stimulus by an average of 93.9 tones. More complex models than the one represented in Figure 5 (e.g., nonlinear models) are conceivable. However, linear approximations around specific points may be constructed using local derivatives.

[0047] For example, points can correspond to default parameters. For instance, this means the following:

number

[0048] In some embodiments, determining and / or adjusting the model (e.g., an action performed by the adjustment component 34 shown in Figure 1) may include making changes to the stimulus control parameters relative to their default values. The adjustment component 34 is configured to change those stimulus control parameters such that small variations (e.g., a single unit) produce a relatively large effect on the outcome (target variable). If we use males of the 50+ demographic and models 510, 514 in Figure 5, then a unit change in either (i) the sleep depth threshold (e.g., having a weighting or multiplier of 172.2 in the model) or (ii) the slow wave density threshold (e.g., having a weighting or multiplier of 172.9) produces about twice the effect of a unit change in (iii) the slow wave peak threshold (i.e., the threshold with a weighting or multiplier of 92) or (iv) the delta threshold (i.e., the threshold with a weighting or multiplier of 93.9).

[0049] Figure 6 illustrates an exemplary optimization of stimulus control parameter values ​​for a demographic stimulus parameter model of men aged 50 years and older (as an example). Lowering the sleep depth threshold by 2 units from the default or otherwise predetermined parameter value (600), lowering the slow wave density threshold by 2 units (602), lowering the slow wave peak threshold by 1 unit (604), and lowering the delta power threshold by 1 unit (606) increases the median number of tones in this demographic from 400 to around 1300. As the above example demonstrates, for a single target variable (outcome), stimulus control parameter values ​​that guarantee the maximum (or minimum, optimized, etc.) level for that demographic group can be easily determined. In some embodiments, the adjustment component 34 (Figure 1) is configured to determine and / or adjust the model based on multiple target variables (outcomes). In some embodiments, this may include optimizing a linear combination of target variables (outcomes), establishing rules for individual target variables (outcomes), and / or other operations. To better understand optimization, assuming we want to maximize both N3 sensitivity and N3 specificity, but with a greater emphasis on sensitivity, we can consider the following linear combination as the target: T = λ * N3 sensitivity + (1 - λ) * N3 specificity, where λ = 0.8. For example, by considering subtraction, it is possible to minimize and maximize simultaneously. In the above example, if the number of tones is selected as the target variable (result), the adjustment component 34 selects sleep depth, slow wave density, slow wave peak, and delta threshold that correspond to the maximum number of tones estimated through the simulation. For example, if N3 sensitivity and specificity are selected as the combined target variables (result), the adjustment component 34 selects sleep depth, slow wave density, slow wave peak, and delta threshold that achieve the maximum accuracy defined by their linear combined accuracy = weight 1 × N3 sensitivity + weight 2 × N3 specificity.If it is necessary to maximize both N3 sensitivity and N3 specificity, the system 10 may be configured such that, for example, weights 1 and 2 are selected (or set so by the system 10) to be positive. In a rule-based embodiment, the tuning component 34 selects any combination of parameters that exceed a predetermined threshold for the target variable (result) (e.g., N3 sensitivity > 0.9 and N3 specificity > 0.8).

[0050] In some embodiments, given demographic information and the minimum desired value of the target variable (outcome), the stimulus control parameter value, may be determined and / or adjusted differently. In the example above, the adjustment component 34 changes the stimulus control parameter to a value that achieves the minimum desired number of tones, e.g., 1000 tones, rather than a value that yields the maximum number of tones. This embodiment may be useful when extensive testing is conducted to define a general (default) parameter set, or when the adjustment component 34 is configured to deviate as little as possible from the general parameter set so as not to affect (or minimize the effect of) other target variables that are not considered during the determination and / or adjustment of the model.

[0051] Returning to Figure 1, the control component 36 is configured to deliver sensory stimuli to the sensory stimulator 16. The control component 36 delivers sensory stimuli based on an output signal, a stimulus parameter model for the demographic group of user 12, and / or other information. For example, if the demographic group of user 12 is unknown, the control component 36 may deliver sensory stimuli to the sensory stimulator 16 based on an output signal from the sensory stimulator 16, according to a predetermined therapy plan. This may occur, for example, during the first part of a sleep session. This may also occur between one or more previous sleep sessions. One of these previous sleep sessions may be, for example, a calibration sleep session or another sleep session. This means that in some embodiments, this type of stimulation may be delivered entirely before the current sleep session. If the demographic group of user 12 is known, and / or if the demographic group of user 12 is determined and / or adjusted by system 10 as described above, the control component 36 is configured to deliver sensory stimuli to the sensory stimulator 16 based on a stimulus parameter model for the demographic group of user 12. In some embodiments, sensory stimuli are delivered based on a stimulus parameter model for the user's demographic group and an output signal generated during a second part of the sleep session (e.g., following a first part of the sleep session). However, in some embodiments, if the stimuli are delivered during one or more previous sleep sessions, such as calibration sessions, according to a predetermined therapeutic plan, the control component 36 may deliver stimuli to the sensory stimulator 16 based on a stimulus parameter model for the demographic group of user 12 directly from the start of the current sleep session (e.g., not just during a second part of the sleep session).

[0052] The control component 36 is configured to control the stimulator 16 to provide stimulation to the user 12 according to a predetermined therapy plan and / or based on a stimulation parameter model for the user's demographic group 12 during sleep and / or at other times. The control component 36 is configured to cause the sensory stimulator 16 to provide sensory stimulation to the user 12 based on the user 12's sleep stage and / or other information. The control component 36 is configured to cause the sensory stimulator 16 to provide sensory stimulation to the user 12 based on sleep stages (e.g., according to a predetermined therapy plan, stimulation parameter model, and / or other information) and / or other information over time during a sleep session. The control component 36 is configured to cause the sensory stimulator 16 to provide sensory stimulation to the user 12 in response to the user 12 being in or appearing to be in sleep of sufficient depth for stimulation (e.g., deep (N3) sleep).

[0053] In some embodiments, the stimulator 16 is controlled by a control component 36 to enhance sleep slow waves through stimuli delivered during NREM sleep (e.g., peripheral auditory stimulation, magnetic stimulation, electrical stimulation, and / or other stimuli) as described herein. In some embodiments, the control component 36 (and / or one or more other processor components described herein) performs operations similar to and / or the same operations as those described in Patent Document 1 (titled "System and Method for Sleep Session Management Based on Slow Wave Sleep Activity in a Subject"), Patent Document 2 (titled "System and Method for Enhancing Sleep Slow Wave Activity Based on Cardiac Activity"), Patent Document 3 (titled "Adjustment of Sensory Stimulation Intensity to Enhance Sleep Slow Wave Activity"), Patent Document 4 (titled "System and Method for Determining Sleep Stage Based on Sleep Cycle"), and / or Patent Document 5 (titled "System and Method for Facilitating Sleep Stage Transitions"), the full texts of which are incorporated by reference individually.

[0054] The electronic storage device 22 includes an electronic storage medium for electronically storing information. The electronic storage medium of the electronic storage device 22 may include one or both of a system storage device provided integrally with the system 10 (i.e., substantially inremovably) and / or a removable storage device that can be detachably connected to the system 10 via, for example, a port (e.g., a USB port, a FireWire port, etc.) or a drive (e.g., a disk drive, etc.). The electronic storage device 22 may include one or more of the following: an optically readable storage medium (e.g., an optical disc, etc.), a magnetically readable storage medium (e.g., a magnetic tape, a magnetic hard drive, a floppy drive, etc.), a charge-based storage medium (e.g., an EPROM, RAM, etc.), a solid-state storage medium (e.g., a flash drive, etc.), a cloud storage device, and / or other electronically readable storage media. The electronic storage device 22 may store software algorithms, information determined by the processor 20, information received via the user interface 24 and / or an external computing system (e.g., an external resource 18), and / or other information that enables the system 10 to function as described herein. The electronic storage device 22 may be a separate component within the system 10 (whole or in part), or it may be provided integrally with one or more other components of the system 10 (e.g., the processor 20) (whole or in part).

[0055] The user interface 24 is configured to provide an interface between the system 10 and user 12 and / or other users, allowing user 12 and / or other users to provide information to and receive information from the system 10. This enables data, cues, results, and / or commands, collectively referred to as “information,” and any other communicable items to be communicated between the user (e.g., user 12) and one or more of the sensors 14, sensory stimulators 16, external resources 18, processor 20, and / or other components of the system 10. For example, hypnograms, EEG data, and / or other information may be displayed for user 12 or other users via the user interface 24. As another example, user 12 may input and / or select demographic information via the user interface 24. The user interface 24 may be and / or contained within a computing device, such as a desktop computer, laptop computer, smartphone, tablet computer, and / or other computing device. Such computing devices may run one or more electronic applications having a graphical user interface configured to provide information to and / or receive information from a user.

[0056] Examples of interface devices suitable for inclusion in the user interface 24 include keypads, buttons, switches, keyboards, knobs, levers, display screens, touchscreens, speakers, microphones, indicator lights, audible alarms, printers, haptic feedback devices, and / or other interface devices. In some embodiments, the user interface 24 includes multiple separate interfaces. In some embodiments, the user interface 24 includes at least one interface provided integrally with the processor 20 and / or other components of the system 10. In some embodiments, the user interface 24 is configured to communicate wirelessly with the processor 20 and / or other components of the system 10.

[0057] Figure 7 illustrates a method 700 for delivering sensory stimuli to a user using a delivery system. The system includes one or more sensors, one or more sensory stimulators, one or more processors comprising machine-readable instructions, and / or other components. The processors are configured to execute computer program components, which include demographic components, model components, tuning components, control components, and / or other components. The operation of method 700 described below is intended to be illustrative. In some embodiments, method 700 may be achieved with one or more additional operations not described and / or without one or more of the operations discussed. In addition, the order in which the operation of method 700 is illustrated in Figure 7 and described below is not intended to be limiting.

[0058] In some embodiments, Method 700 may be implemented in one or more processing devices such as one or more processors 20 described herein (e.g., digital processors, analog processors, digital circuits designed to process information, analog circuits designed to process information, state machines, and / or other mechanisms for electronically processing information). The processing device may include one or more devices that perform some or all of the operations of Method 700 in response to instructions electronically stored on an electronic storage medium. The processing device may include one or more devices that consist of hardware, firmware, and / or software specifically designed to perform one or more of the operations of Method 700.

[0059] Operation 702 generates an output signal that transmits information about the user's brain activity during a sleep session. In some embodiments, operation 702 is performed by one or more sensors, the same or similar to sensor 14 (shown in Figure 1 and described herein).

[0060] In operation 704, sensory stimulation is provided to the user during the sleep session. In some embodiments, the sensory stimulation is provided to the user during the first part of the sleep session (or the entire previous sleep session) based on an output signal generated during the first part of the sleep session (or the entire previous sleep session). In some embodiments, operation 704 is performed by one or more sensory stimulators, the same or similar as sensory stimulator 16 (shown in Figure 1 and described herein).

[0061] In operation 706, the user's demographic group is determined. The demographic group is determined based on output signals. In some embodiments, the demographic group is determined based on output signals generated during a first part of a sleep session (or a previous sleep session). In some embodiments, the demographic group is determined based on sensory stimuli delivered during a first part of a sleep session (or a previous sleep session). In some embodiments, operation 706 includes using output signals generated during a first part of a sleep session (or a previous sleep session) to determine the demographic group for a user based on the lack of explicit demographic group designation for the user. In some embodiments, operation 706 is performed by a processor component that is the same as or similar to the demographic component 30 (shown in Figure 1 and described herein).

[0062] In operation 708, a stimulus parameter model related to the user's demographic group is selected. The stimulus parameter model is selected from a set of stimulus parameter models related to different demographic groups. In some embodiments, operation 708 includes determining and / or adjusting the stimulus parameter model in a set of stimulus parameter models. For example, in some embodiments, operation 708 includes obtaining historical brain activity information for a group of users in a given demographic group. Historical brain activity information indicates the sleep depth over time during a sleep session for the group of users. Operation 708 includes (i) performing a simulation of sensory stimuli based on the historical brain activity information and (ii) one or more stimulus control parameters. Operation 708 includes adjusting one or more stimulus control parameters at multiple times between each of the simulations so that the simulation is performed based on one or more stimulus control parameters such that the simulation is adjusted at multiple times. For each adjustment, operation 708 includes determining the effect of the adjustment of one or more stimulus control parameters on a target variable. Operation 708 includes determining a set of stimulus control parameters for a given stimulus parameter model associated with a given demographic group, based on the effect of adjustment. Operation 708 also includes storing the given stimulus parameter model as part of a set of stimulus parameter models. In some embodiments, for example, one or more sensory stimulators include tone generators, and the target variable includes a number of tones delivered during a simulated sleep session. In some embodiments, operation 708 is performed by the same or similar processor components as the model component 32 and / or adjustment component 34 (shown in Figure 1 and described herein).

[0063] In operation 710, one or more sensory stimulators are controlled to deliver sensory stimuli based on a stimulus parameter model for the user's demographic group. In some embodiments, the sensory stimuli are delivered based on a stimulus parameter model for the user's demographic group and an output signal generated during (e.g.) a second part of a sleep session (or a later sleep session). In some embodiments, this stimulus is delivered during the second part of a sleep session (or a later sleep session). The second part of a sleep session (or a second sleep session) follows the first part of a sleep session (or a first sleep session). In some embodiments, operation 710 is performed by a processor component that is the same as or similar to the control component 36 (shown in Figure 1 and described herein).

[0064] In a claim, reference numerals in parentheses should not be construed as limiting the claim. The words “comprising” or “including” do not exclude the existence of elements or steps other than those enumerated in the claim. In a device claim enumerating several means, some of these means may be embodied by hardware of the same item. An element expressed in the singular does not exclude the existence of multiple such elements. In any device claim enumerating several means, some of these means may be embodied by hardware of the same item. The mere fact that certain elements are referenced in different dependent claims does not indicate that these elements cannot be used in combination.

[0065] The descriptions provided above provide details for illustrative purposes based on the most practical and preferred embodiments currently available. However, such details are for illustrative purposes only, and it should be understood that this disclosure is not limited to the expressly disclosed embodiments, but rather intended to cover modifications and equivalent configurations within the spirit and scope of the appended claims. For example, it should be understood that, to the extent possible, this disclosure is intended to allow one or more configurations of any embodiment to be combined with one or more configurations of any other embodiment. [Prior art documents] [Patent Documents]

[0066] [Patent Document 1] U.S. Patent Application No. 14 / 784,782 [Patent Document 2] U.S. Patent Application No. 14 / 783,114 [Patent Document 3] U.S. Patent Application No. 14 / 784,746 [Patent Document 4] U.S. Patent Application No. 15 / 101,008 [Patent Document 5] U.S. Patent Application No. 15 / 100,435

Claims

1. A system configured to deliver sensory stimuli to a user during a sleep session, One or more sensors configured to generate output signals that transmit information about the user's brain activity during the sleep session, One or more sensory stimulation devices configured to provide the user with the sensory stimulation during the sleep session, The system includes one or more sensors and one or more processors connected to one or more sensory stimulators, and these one or more processors receive machine-readable instructions. In response to the information of the output signal generated during the first portion of the sleep session being similar to and / or identical to the corresponding information of a particular demographic group, the user is determined to belong to the particular demographic group. During the sleep session, a stimulus parameter model corresponding to the specific demographic group for the user is selected from a set of stimulus parameter models corresponding to demographic groups having different demographic characteristics. During the second portion of the sleep session, one or more sensory stimulators are controlled to deliver the sensory stimuli to the user, based on the stimulus parameter model corresponding to the specific demographic group for the user and the output signals generated during the second portion of the sleep session. It is configured in such a way, The second portion of the sleep session follows, in terms of time, the first portion of the sleep session. system.

2. The one or more processors described above are: During the first portion of the sleep session, one or more sensory stimulation devices are controlled to deliver the sensory stimulation. In addition to the sensory stimuli delivered during the first portion of the sleep session, the specific demographic group of the user is determined based on the sensory stimuli delivered during the first portion of the sleep session. It is further constructed in such a way. The system according to claim 1.

3. The system according to claim 1, wherein one or more processors are configured to determine the specific demographic group for the user if there is no explicit designation of a demographic group for the user, using the output signals generated during the first portion of the sleep session.

4. Selecting the stimulus parameter model corresponding to a particular demographic group for the user from the set of stimulus parameter models corresponding to demographic groups having different demographic characteristics is, The one or more processors described above We obtain historical brain activity information for a group of users within a given demographic group. (i) Based on the historical brain activity information, and (ii) based on one or more stimulus control parameters, a simulation of sensory stimuli is performed for users of the specific demographic group: The one or more stimulus control parameters are adjusted multiple times between each of the simulations so that the simulation is performed based on the one or more stimulus control parameters that have been adjusted multiple times. For each of the above adjustments, the effect of adjusting one or more stimulus control parameters on the target variable is determined by determining which of the one or more stimulus control parameters has a greater influence on the target variable compared to the other stimulus control parameters. Based on the effects of the greater adjustments, a set of stimulus control parameters is determined for a given stimulus parameter model associated with the particular demographic group. The given stimulus parameter model is stored as part of the set of stimulus parameter models. This includes being further configured in such a way, The aforementioned historical brain activity information indicates the sleep depth over time during the sleep sessions of the group of users. The system according to claim 1.

5. The system according to claim 4, wherein the one or more sensory stimulation devices include a tone generator, and the one or more processors are configured such that the target variable includes the number of tones to be delivered during a simulated sleep session.

6. A method for operating a delivery system that delivers sensory stimuli to a user during a sleep session, The delivery system includes one or more sensors, one or more sensory stimulators, and one or more processors, and the operation method is The processor causes one or more sensors to generate output signals that transmit information about the user's brain activity during the sleep session, The processor determines control parameters that control the sensory stimulation provided to the user during the sleep session by one or more sensory stimulation devices, The one or more processors determine that the user belongs to the particular demographic group in response that the information of the output signal generated during the first part of the sleep session is similar to and / or the same as the corresponding information of the particular demographic group, The one or more processors, during the sleep session, select a stimulus parameter model corresponding to a particular demographic group for the user from a set of stimulus parameter models corresponding to demographic groups having different demographic characteristics, The one or more processors control the one or more sensory stimulators during the second portion of the sleep session, based on the stimulus parameter model corresponding to a particular demographic group for the user and the output signals generated during the second portion of the sleep session, to deliver the sensory stimuli to the user. The second portion of the sleep session follows, in terms of time, the first portion of the sleep session. How to operate.

7. The one or more processors control the one or more sensory stimulators to deliver the sensory stimuli based on the output signals generated during the first portion of the sleep session, The one or more processors further include determining the particular demographic group for the user based in addition to the sensory stimuli delivered during the first portion of the sleep session, The operating method according to claim 6.

8. The operating method according to claim 6, further comprising determining the specific demographic group for the user using the output signal generated during the first portion of the sleep session, if the processor lacks an explicit designation of a demographic group for the user.

9. Selecting the stimulus parameter model corresponding to a particular demographic group for the user from the set of stimulus parameter models corresponding to demographic groups having different demographic characteristics is, The acquisition of historical brain activity information for a group of users within a given demographic group, wherein the historical brain activity information indicates the sleep depth over time during sleep sessions of the group of users. The one or more processors perform a simulation of sensory stimuli for users of the specific demographic group based on (i) the historical brain activity information and (ii) one or more stimulus control parameters. The one or more processors adjust the one or more stimulus control parameters multiple times between each of the simulations so that the simulation is performed based on the one or more stimulus control parameters that have been adjusted multiple times. The one or more processors determine, with respect to each of the adjustments, which of the one or more stimulus control parameters has a greater influence on the target variable compared to the other stimulus control parameters, thereby determining the effect of the adjustments of the one or more stimulus control parameters on the target variable. The one or more processors determine a set of stimulus control parameters for a given stimulus parameter model associated with a particular demographic group, based on the greater effect of the adjustments. The one or more processors include storing the given stimulus parameter model as part of the set of stimulus parameter models, The operating method according to claim 6.

10. The method of operation according to claim 9, wherein the one or more sensory stimulation devices include a tone generator, and the target variable includes the number of tones delivered during a simulated sleep session.

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