Medical content delivery and progress tracking system

Abstract

Apparatus and related methods relate to a dynamically induced package generation system (DIPGS). In illustrative examples, the DIPGS may include at least one verified digital therapy (DTx), a user profile, and a media profile associated with wild media content. For example, the DIPGS may include an evaluation engine configured to generate or update a user profile based on a log of user input and an observation of user behavior. The DIPGS may include a medical media package generation engine (MMPGE) configured to generate a dynamic induced media package (DUMP). In the induction mode, the DUMP may periodically play the wild media content selected by the user. Upon transition from the induction mode to a treatment mode, the MMPGE generates intervention monitoring content (IMC) including the verified DTx to provide a treatment for the user. Various embodiments may advantageously provide continuous medical guidance and progress monitoring to a user.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application Serial No. 63 / 268,905, entitled “FDA-Compliant Therapeutic Game Selection and Delivery Platform,” filed on March 4, 2022 by Ryan J. Douglas, U.S. Provisional Application Serial No. 63 / 362497, entitled “DTX Video Game Delivery and Tracking Digital Platform,” filed on April 5, 2022 by Ryan J. Douglas, U.S. Provisional Application Serial No. 63 / 363639, entitled “Media Delivery Tool for Self-Assessment of Physical and Mental States,” filed on April 26, 2022 by Ryan J. Douglas, and U.S. Provisional Application Serial No. 63 / 366521, entitled “Therapeutic Game Selection and Delivery Engine,” filed on June 16, 2022 by Ryan J. Douglas.

[0002] This application incorporates the entire contents of the above-mentioned application by reference.

[0003] The subject matter of this application may have common invention rights with and / or may be related to the following subject matter: PCT patent application serial number PCT / US2021 / 071585, entitled “Immersive Medical Translation Engine for Development and Reuse of Unproven and Validated Code,” filed by Ryan J. Douglas on September 24, 2021; U.S. Patent Application No. 11,295,261, entitled “FDA-Compliant Quality System for Risk Reduction, Development and Maintenance of Software-Based Medical Systems,” filed by Ryan J. Douglas on May 28, 2019; U.S. Patent Application No. 11,531,949, entitled “FDA-Compliant Quality System to Reduce Risk, Develop and Maintain Software-Based Medical Systems,” filed by Ryan J. Douglas on March 1, 2022; and, U.S. patent application serial number 18 / 055,754, titled “FDA-Compliant Quality System for Risk Reduction, Development and Maintenance of Software-Based Medical Systems,” filed by Ryan J. Douglas on November 15, 2022.

[0004] This application incorporates the entire contents of the above-mentioned application by reference. Technical Field

[0005] Various embodiments are generally directed to systems and methods for delivering regulated digital therapeutic media in an unregulated media content delivery network. Background Art

[0006] Medical treatment can include various exercises and / or equipment. Patients can receive medical treatment under the supervision of a caregiver (e.g., a physician, a therapist). For example, medical treatment can be performed in a medical facility (e.g., a hospital, a clinic) and / or in a home-based environment.

[0007] For example, a medical device may include a software component. The software component may be regulated by one or more regulatory agencies, such as the Food and Drug Administration in the United States, the European Medicines Agency (EMA), the European Food Safety Authority (EFSA), the Veterinary Medical Directorate (VMD) in the United Kingdom, Health Canada, the Canadian Food Inspection Agency (CFIA), the Pesticides and Veterinary Medicines Administration (APVMA) in Australia, the National Medical Products Administration (NMPA) of the People's Republic of China, the Taiwan Food and Drug Administration, the Pharmaceuticals and Medical Devices Agency (PMDA) of Japan, the Ministry of Health, Labour and Welfare (MHLW) of Japan, and / or the Ministry of Food and Drug Safety (MFDS) of the Republic of Korea. Medical device software components may need to be tested to regulatory standards before release.

[0008] For example, non-medical treatments may include health and / or performance enhancement. For example, various supplements and / or processes may be created to enhance performance and / or health. Such non-medical treatments may be unregulated or less restricted by legal requirements.

[0009] For example, digital assets can be obtained from one or more repositories and / or platforms (e.g., interactive). For example, digital assets can be obtained from a gaming platform. For example, a software developer can provide digital assets. For example, digital assets can be obtained from a book publisher and / or retailer. For example, digital assets can be obtained from a music and / or video publisher or retailer. Summary of the invention

[0010] The device and its associated method relate to a dynamic inducement package generation system (Dynamic Inducement Package Generate System, DIPGS for short). In an illustrative example, DIPGS may include at least one verified digital therapy (DTx) associated with wild media content, a user profile, and a media profile. For example, DIPGS may include an evaluation engine for generating or updating a user profile based on a log of user input and a user's behavioral observation. DIPGS may include a medical media package generation engine (MMPGE) for generating a dynamic inducement media package (DIMP). In induction mode, DIMP may periodically play wild media content selected by the user. After switching from induction mode to treatment mode, MMPGE generates intervention monitoring content (IMC) including a verified DTx to provide therapeutic treatment to the user. Various embodiments may advantageously provide users with continuous medical guidance and progress monitoring.

[0011] Various embodiments may achieve one or more advantages. For example, some embodiments may advantageously provide a historical and / or immediate assessment of a user's mental and / or physical health. For example, some embodiments may advantageously be configured to monitor a user's ongoing media use. For example, some embodiments may include a medical professional interface to advantageously allow a professional to gain insight into a user and / or interact directly with a patient. For example, some embodiments may advantageously assist in self-treating a patient by providing an immersive therapy mechanism that is dynamically generated based on a monitoring and tracking mechanism in an unmonitored media content environment. For example, some embodiments may advantageously provide the public with simple tools to assist with a user's health status based on a user experience, regardless of the environment, and without being attached to a game or specific media. For example, some embodiments may advantageously automatically verify updates on a verified DTx.

[0012] The details of various embodiments will be set forth in the following drawings and description. Other features and advantages will be apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1A and Figure 1B An illustrative dynamically induced package generation system (DIPGS) in an illustrative usage scenario is described, including a medical media packaging platform (MMPP) and a dynamically induced package state machine (DIPSM).

[0014] Figure 2 is a block diagram depicting an exemplary MMPP.

[0015] Figure 3is a flow chart describing an exemplary runtime method of an exemplary DIPGS.

[0016] Figure 4 is an exemplary architecture describing an exemplary risk assessment engine of DIPGS.

[0017] Figure 5 An exemplary use scenario is described that provides an exemplary standalone digital therapeutic (DTx) mode.

[0018] Figure 6 An exemplary digital gaming cloud (DGC) for delivering DTx games employed in illustrative use cases is described.

[0019] Figure 7 is a block diagram depicting an exemplary DGC.

[0020] Figure 8 is a description of an exemplary regulatory module for satisfying regulatory requirements for DTx gaming.

[0021] Fig. 9 An exemplary method of verifying changes in DTx is described.

[0022] Fig.10 An exemplary method for delivering a DTx game to a user and generating DTx guidance is described.

[0023] Like reference symbols in the various drawings indicate the same elements. DETAILED DESCRIPTION

[0024] For ease of understanding, this document is organized as follows: First, to help introduce the discussion of various embodiments, Figure 1A-3 Introduces a dynamic induction package generation system (Dynamic Induction Package Generate System, referred to as DIPGS). Figure 4-5 To introduce and describe some exemplary embodiments of the risk assessment and delivery features of DIPGS. Figure 6-8 , describes the digital game cloud in the application of an exemplary implementation of DIPGS. Figure 9-10 , this document describes exemplary apparatus and methods for updating and delivering validated digital therapeutics. Finally, the document also discusses embodiments, exemplary applications and aspects related to dynamic induced package generation and application.

[0025] Digital therapeutic media, such as audio or video content, can be used to treat a variety of health conditions, including, for example, mental health disorders, chronic pain, and addiction. In some examples, delivery of such media may traditionally be limited to regulated channels, such as regulatory (e.g., U.S. Food and Drug Administration (FDA)) approved telehealth platforms and / or medical devices, which may limit patient accessibility and scalability. Unregulated media content delivery networks, such as streaming services or social media platforms, may sometimes offer greater reach and flexibility. However, these platforms may lack the regulatory controls necessary to deliver digital therapeutic media, for example.

[0026] In some embodiments, digital therapeutic media can be delivered through various means, such as mobile applications, virtual reality platforms, and / or web-based portals. For example, such platforms can provide patients with a convenient and accessible treatment modality outside of a traditional doctor's office and independent of its location.

[0027] In some examples, digital therapeutic media can be used to train patients to perform involuntary actions (e.g., breathing). For example, these involuntary actions can improve mental health. In an illustrative example, breathing exercises can be an effective treatment for various mental health conditions, including anxiety and depression. Traditional methods of training patients to perform these exercises, for example, are time-consuming and costly. Sometimes, for example, in a doctor's office environment, patients may feel more nervous. For example, by using digital therapeutic media, patients can receive training in the comfort of their own home, at their own pace, without the need for a therapist or other healthcare professional to be present.

[0028] Figure 1a and Figure 1B An illustrative Dynamically Induced Packaging Generation System (DIPGS) in an illustrative use scenario is described, including a Medical Media Packaging Platform (MMPP) and a Dynamically Induced Packaging State Machine (DIPSM). Figure 1A In the example shown, the DIPGS 100 includes a self-medication user (STU 105). For example, the STU 105 can use a device 106 (e.g., a tablet, a game console, a personal computer) to find media (e.g., games). The device 106 (e.g., in response to input from the STU 105) runs a medical media delivery application (MMDA 110). For example, the MMDA 110 can help the STU 105 select a game that has a therapeutic benefit for the STU 105. For example, the device 106 can be a game station, a computer, a phone, or some combination thereof.

[0029] As shown, DIPGS 100 includes a Wild Media Platform (WMP 115) and a Medical Media Package Platform (MMPP 120). As shown, MMPP 120 includes an Evaluation Engine 125, a Medical Media Package Generation Engine (MMPGE 130), and a Data Store 135. For example, the Data Store 135 may store input from the STU 105. For example, the Data Store 135 may store media information (e.g., a list of available media archives). For example, the Data Store 135 may store (predetermined) caretaker archives.

[0030] In the depicted example, the data store 135 includes a user profile 140. For example, the user profile 140 may be embodied as a digital data structure having predetermined digital metadata associated with a corresponding patient (e.g., STU 105). For example, the user profile may include attributes (e.g., motivational attributes, pathology attributes, dynamic pathology state attributes), and / or a time distribution (activity) history of the STU 105. For example, the user profile 140 may include a player type that may be generated based on an extended Bartie model.

[0031] In the depicted example, data store 135 includes media archive 145. For example, media archive 145 may be embodied as a digital data structure corresponding to a particular media object (e.g., digital media, game, game component). Media archive 145 may, for example, define predetermined attributes of the associated media object. For example, MMPP 120 may select and / or filter games suitable for the user based on the predetermined attributes of the associated media object.

[0032] WMP115 includes various wild games 150. For example, wild games 150 may not be medically monitored. For example, wild games 150 may include games, music and / or videos developed for normal use (e.g., entertainment). For example, wild games 150 may be uploaded to WMP115 by game developers. In some examples, DIPGS100 may include games preloaded into WMP115. In some embodiments, WMP115 and MMPP120 may be a unified architecture and / or connected via a communication network. In some embodiments, WMP115 may include, for example, other unregulated digital media. For example, unregulated media may include books. In some embodiments, unregulated media may include, for example, films. In some embodiments, unregulated media may include, for example, audio. For example, unregulated media may be used as an attraction mechanism to attract users (e.g., STU105) to continue treatment and / or evaluation.

[0033] For example, the MMPP 120 may use the user profile 140 to categorize the STU 105. For example, the MMPP 120 may use the media profile 145 to categorize the wild games 150. For example, the MMPP 120 may compare the categorization and manage the treatment journey of the STU 105 through one or more wild games 150. For example, the MMPP 120 may suggest a flow of games and treatments. In some examples, the MMPP 120 may allow the patient to suggest a flow in treatment on his own.

[0034] In an illustrative example, for example, MMPP 120 may recommend therapy-based entertainment. For example, if STU 105 indicates that he / she has been in a scenario that they have difficulty passing, MMPP 120 may suggest a character game to play through a corresponding scenario where the patient can respond and / or control the scenario in a different way.

[0035] The data storage 135 includes a plurality of digital processing modules (DTx modules 155). For example, the DTx modules 155 may include validated therapeutic media content. For example, the DTx modules 155 may include therapeutic effects and mechanisms approved by regulatory organizations (e.g., the U.S. Food and Drug Administration, the U.S. Federal Communications Commission). In some embodiments, the DTx modules 155 may be stored in the data storage 135 only after being validated by the MMPP 120. Figure 6 Various embodiments of validating and managing the DTx module 155 are described.

[0036] In various embodiments, for example, the DTx module 155 may include a therapeutic behavior profile, source code, digital media (e.g., audio, video, image, text), an interaction sequence (e.g., an interaction profile), or some combination thereof. For example, various embodiments may include a treatment modality, a treatment mechanism, a healing mechanism, a healing modality, a game mechanism, or some combination thereof, such as described in U.S. Application Serial No. 63 / 202,881, entitled “Immersive Digital Therapeutics,” filed by Ryan J. Douglas on June 28, 2021, the entire contents of which are incorporated herein by reference. For example, at least paragraphs [0017-0026] and [0030-0063] discuss various implementations using therapeutic behavior profiles, game implementation profiles, game attribute profiles, therapeutic mechanisms, treatment modalities, game mechanisms, enhancement and / or adaptation management systems, and combinations thereof.

[0037] In some embodiments, the MMPGE 130 may generate a dynamically induced media dump (DUMP) by integrating the wild game 150 with one or more DTx modules 155 in response to a game request from the STU 105. For example, each of the media archives 145 may correspond to one of the wild games 150. The media archives 145, for example, may include DTx conversion points for integrating the wild games 150. In some embodiments, the media archives 145 may also include metadata, for example, suggesting which type of DTx module 155 may be integrated at each software insertion point. In some embodiments, at the software insertion point, the DTx module 155 may be inserted so that the software jumps at run time to execute instructions in the DTx module 155.

[0038] As an illustrative example without limitation, the evaluation engine 125 may operate on user input from the STU 105 to determine one or more recommended games for playing. The evaluation engine 125 may, for example, determine some games from the wild games 150 based on the user input, the user profile 140, and the media profile 145. For example, the recommended games may be presented on the MMDA 110 for the user to select. After the recommended games, for example, the MMPGE 130 may generate a DIMP based on the user selection. For example, the DIPGS 100 may deliver the generated DIMP directly from the MMPP 120 to the device 106. For example, the DIMP may be delivered to the device 106 via the WMP 115.

[0039] In this example, the MMDA 110 runs the received DIMP on a dynamic induction package state machine (DIPSM 160). As shown, the DIPSM 160 includes a treatment state and an induction state. In the induction state, for example, the DIPSM 160 can run a selected wild game 150. For example, the selected wild game 150 can run normally. In some examples, the selected wild game 150 can be run using adjusted parameters (e.g., game speed, control mechanism). For example, the adjusted parameters can be determined based on the user profile 140 and the media profile 145.

[0040] For example, in the treatment state, DIPSM 160 can interrupt the game play by running the treatment immersive medical package (TIMP 190). In some embodiments, MMPGE 130 can dynamically generate a set of state transition criteria based on the selected wild game 150 and the integrated DTx module 155, based on the user profile 140 and the media profile 145. For example, at the state transition, MMPGE 130 can generate TIMP 190 based on the DTx module 155, the user profile 140 and the media profile 145.

[0041] When the instance identified in the wild game 150 meets the transition criteria, in some embodiments, the DIPSM 160 can switch to the treatment state, and the MMPGE 130 can identify one of the DTx modules 155 based on the user profile 140 to generate intervention monitoring content (IMC 165) played in the treatment state. For example, the MMDA 110 can run the IMC 165 to present the TIMP 190. For example, the TIMP 190 can include guidance for the user in the identified instance. For example, the TIMP 190 can include a warning to the user in the identified instance. For example, the TIMP 190 can include a list of questions asked to the user in the identified instance. For example, a list of questions can be generated to access / track the treatment state of the STU 105. In some embodiments, the TIMP 190 can be generated based on the user profile 40 and the media archive of the wild game 150.

[0042] As shown in the following example, in the treatment state of DIPSM 160, IMC 165 can induce MMDA 110 to present treatment interface 170. For example, treatment interface 170 can include authenticated media content to be presented to STU 105. Figure 1B 170. For example, the treatment interface 170 can present a list of questions 175 for the STU 105 to answer. For example, the treatment interface 170 can include instructions 180. For example, the instructions 180 can include notes, warnings, information briefings (e.g., mental health information, physical health information), or a combination thereof. For example, the question list 175 can be generated from the DTx module 155 based on the current progress of the wild game 150 and the user profile 140.

[0043] In some embodiments, the STU 105 is prompted to respond to the treatment. For example, the STU 105 may be asked how it feels (e.g., absolute feeling, relative to how it felt just before the media was released). For example, the STU 105 may be asked to provide feedback related to its pathology, motivation, experience, delivery media, or some combination thereof. For example, the prompt may include selection (e.g., picking a smiley face or a frowny face), sorting, sentence completion, free response, or some combination thereof. In some embodiments, additional micro-log prompts may be provided.

[0044] After the STU 105 interacts with the treatment interface 170, as shown Figure 1A As shown, MMDA 110 may send response 185 to MMPP 120. For example, assessment engine 125 may process the response to update user profile 140. Figure 3-4 Various embodiments of updating user profile 140 and other exemplary methods of processing response 185 are discussed.

[0045] In illustrative aspects, the DIPGS 100 including various wild media content (e.g., wild game 150) may be used to generate a DIMP based on a user profile generated from a log of user input. During runtime of the DIMP, the DIPGS 100 may use the MMPGE 130 to generate a TIMP during playback of the selected media content. For example, the MMPGE 130 may generate a TIMP based on a set of state transition criteria. Based on a response to the received TIMP (e.g., response 185), the user profile (e.g., a profile of the user) may be updated.

[0046] In some embodiments, the MMPGE 130 can dynamically generate a set of state transition criteria based on the selected media content, the user profile, and the identified treatment instances in the DIMP. In some examples, the generated DIMP can include a media profile 145 based on the media content (e.g., wild game 150) and the user profile 140 at each identified instance and a verified set of media content recommendations (e.g., DTx module 155).

[0047] In some embodiments, the user profile 140 can be generated based on a log of user input (e.g., the user's initial profile, input from medical personnel, responses 185 received during the media playback process) received from the MMDA 110. For example, based on the log of user input, the DIPGS 100 can advantageously provide a historical and immediate assessment of the mental and / or physical health of the STU 105.

[0048] In various implementations, IMC 165 may include guidance and warnings presented to the user at predetermined times based on a set of state transition criteria. For example, guidance (eg, guidance 180) may include instructions for inducing autonomous function using the voluntary actions required to play DIMP.

[0049] As a non-limiting illustrative example, many people may turn to media to relieve mental and / or physical health issues. However, such users may lack guidance on the media that best suits their issues. For example, these users may not even be able to subjectively gauge whether the media is appropriate for them and / or whether their particular condition / situation requires more directed care. Furthermore, it may be difficult for users to track if the media they use has a positive impact on their condition and / or determine if they should seek additional help.

[0050] In various embodiments, for example, DIPGS 100 can be advantageously used to monitor the ongoing media usage of STU 105. For example, DIPGS 100 can determine (by assessment engine 125) whether health has deteriorated during the time media detection period (e.g., based on a log of user input). In some embodiments, DIPGS 100 can be used to try and solve related problems (e.g., during media usage and the number of days, weeks, months and / or years that an individual interacts with media for a particular health issue). In some embodiments, by way of example and not limitation, DIPGS 100 can be configured as a media delivery therapy companion system. In some embodiments, DIPGS 100 can include a media platform.

[0051] In some embodiments, DIPGS 100 can be configured as a subordinate code to (digital) media assets, for example. For example, DIPGS 100 can be configured as a wrapper application (e.g., software). As an example and not limitation, DIPGS 100 can be configured as a supplementary application (e.g., mobile application, game console application, MMDA 110). For example, DIPGS 100 can be directly integrated into a media delivery system that delivers media.

[0052] In a non-limiting illustrative example, if a user requires an in-game health assessment, he / she may have to be created by a trained medical professional to obtain medical advice. Before any medical advice can be provided, a trained medical professional may be required to study the media set (e.g., games, songs, movies). After conducting an in-depth study of all the media (e.g., watching a 10 minute video several times and studying the transcripts of the videos), the medical professional can identify appropriate break points based on the detailed medical records associated with the user and create guidance at each break point. As a result, the medical professional can easily spend days, if not weeks, just preparing a professional plan of media for the user.

[0053] In order to provide a self-assessment, the user would have to interrupt his or her work at a determined time. This would be very difficult and only a disciplined user could do it. On the other hand, the user could play the media in the presence of a medical professional, who would be interrupted during the playback and deliver medical instructions to the user. In this way, the cost of playing the media would be prohibitive. Furthermore, expanding the media library after the user tires of the media from the professional program requires an equally expensive process.

[0054] Using DIPGS 100, STU 105 can automatically enjoy verified media content generated by MMPGE 130. For example, evaluation engine 125 can advantageously provide medical guidance and monitor the progress of STU 105. In some embodiments, such as in conjunction with Figure 6-9As described, media content delivered to the STU 105 may be regulated. For example, the delivered content may comply with regulatory rules.

[0055] Figure 2 1 is a block diagram describing an exemplary MMPP (e.g., MMPP 120). In this example, MMPP 120 includes a therapy media generation and monitoring engine TMGAME 200. Engine MGAME 200 includes a processor 205. Processor 205 may, for example, include one or more processors. Processor 205 is operably connected to a communication module 210. Communication module 210 may, for example, include wired communication. Communication module 210 may, for example, include wireless communication. In the described example, communication module 210 is operably connected to MMDA 110 and WMP 115. In the described example, communication module 210 is operably connected to a medical professional interface 215 and medical validation rules 220. For example, medical professional interface 215 may allow medical professionals to adjust data stored in MMPP 120. For example, medical professional interface 215 may allow medical professionals to provide medical input to MMPP 120. For example, medical professional interface 215 provides a communication channel between medical professionals and patients. For example, the medical professional may, via the medical professional interface 215, ask, “How did you feel about that game? That game happens to play through the seven stages of grief.” Thus, the medical professional may advantageously provide insight to the patient and / or may interact directly with the patient.

[0056] In some embodiments, the DIPGS 100 may allow a medical professional to suggest a course of treatment and / or "homework" to a user. For example, a medical professional may instruct the MMPP 120 to focus on anxiety for a specified user for a period of time. For example, a medical professional may indicate that trauma issues will be addressed later, after anxiety is resolved.

[0057] The memory module 225 , for example, may be used to verify media content transmitted by the MMPP 120 . For example, the MMPP 120 may use the memory module 225 to automatically verify a generated IMC or DIMP.

[0058] The processor 205 is operably connected to the memory module 225. For example, the memory module 225 may include one or more memory modules (e.g., random access memory (RAM)). The processor 205 includes a storage module 230. For example, the storage module 230 may include one or more storage modules (e.g., non-volatile memory). In the depicted example, the storage module 230 includes the evaluation engine 125 and the MMPGE 130.

[0059] The MMPGE 130 may, for example, determine the interface 170 so that it is generated and presented to the STU 105. The assessment engine 125 may, for example, update the user profile 140 based on the user's input.

[0060] The media analysis engine 235, for example, can analyze media objects (e.g., wild games 150, other media content associated with WMP 115) to determine attributes. For example, in some embodiments, the media analysis engine 235 can be used to generate a media archive 145. In some embodiments, the media analysis engine 235 can include a machine learning model for automatically redefining and / or updating weights associated with attributes of a media object based on user input (e.g., micrologs, changes in pathology archives, caretaker input, authorized expert input).

[0061] In the depicted example, the storage module 230 includes a medical analysis engine 240. For example, the medical analysis engine 240 can generate output based on data stored in the data store 135. The data store 135 is operably connected to the processor 205. As depicted, the data store 135 includes the media archive 145, the user archive 140, the medical archive 250, and the micro log 255.

[0062] The micro-log 255, for example, can be embodied as a digital data structure having predetermined digital metadata associated with a particular user (e.g., user profile 140). As an example and not limitation, the micro-log 255 can store the corresponding user's historical responses (e.g., raw, summarized, evaluated raw responses) to treatments (e.g., to presented media).

[0063] In various embodiments, for example, the micro-log 255 may include, but is not limited to, pre-game and post-game inputs, and an associated database that associates games, durations, frequencies, and / or emotional states represented by user input and / or system-inferred information. By way of example and not limitation, such information may include an emotion rating scale (e.g., 1-5, expressions), word associations, sentence completions (e.g., related to current symptom states), free-writing input, a gratitude log, an experience log, or a combination thereof.

[0064] The user profile 140 includes a pathology profile 260, a motivation profile 265, a predetermined caretaker 270, and a dynamic state profile 275. For example, the motivation profile 265 can be embodied as a digital data structure having predetermined digital metadata associated with predetermined motivation types. For example, the motivation profile 265 can define attributes of the motivation types.

[0065] For example, the incentive profile 265 may include one or more profiles based on the above-described models.For example, the incentive analysis engine 240 may generate an incentive profile 265 for a user as a weighted distribution of multiple incentive types.

[0066] Exemplary examples of self-assessments that may be implemented to help determine whether a user suffers from mild to moderate stress, anxiety, and / or depressive symptoms may include, but are not limited to, the Patient Health Questionnaire (PHQ-9). For example, the PHQ-9 may be a validated screening measurement that helps diagnose and assess the severity of depressive symptoms, and may be used, for example, as a symptom severity tracker to monitor the effectiveness of a treatment plan. In some embodiments, by way of example and not limitation, the MMPP 120 may be used to use validated assessment measures to better "understand" the core symptoms of each disorder / symptom state (e.g., generate pathology profile 260, generate treatment profile 250). For example, in depression, SIGECAPS (a sleep aid that describes the pathological morphological symptoms of depression listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)) may be implemented as a framework.

[0067] For example, a treatment profile 250 may be embodied as a digital data structure corresponding to a particular treatment. For example, one or more treatment profiles 250 may be linked to one or more patient pathology profiles 260, and / or vice versa. For example, but not limited to, a treatment profile 250 may define predetermined attributes of a treatment (e.g., respiratory profile, time duration, indicative symptoms, indicative pathologies).

[0068] In some embodiments, the treatment analysis engine 240 can, by way of example and not limitation, operate on the user profiles 140 to determine the user's association with one or more pathologies. For example, the treatment analysis engine 240 can generate a pathology profile 260 based on data retrieved from and / or associated with one of the user profiles 140. For example, a pathology profile 260 can be generated corresponding to attributes defined by one or more pathology definitions. For example, the treatment analysis engine 240 can generate a pathology profile 260 that includes one or more weights associated with each of a plurality of pathology definitions.

[0069] For example, a pathology definition, for example, can be embodied as a digital data structure corresponding to a particular pathology (e.g., depression, cardiomyopathy, post-traumatic stress disorder). For example, a pathology definition can define predetermined attributes of a corresponding pathology (e.g., associated symptoms, associated treatments). In some embodiments, a pathology definition can define one or more states and associated attributes of a pathology. In some embodiments, a pathology definition can be accessed in an external database using the communication module 210. In some embodiments, the pathology definition can be pre-loaded in the data store 135.

[0070] In this example, the data store 135 also includes DTx modules 155. As shown, each DTx module 155 may include a treatment profile 280. For example, the treatment profile 280 may include attributes and parameters of the corresponding DTx module 155. For example, the MMPGE 130 may generate a DIMP from the DTx modules based on the treatment profile 280.

[0071] In some embodiments, the medical analysis engine 240 can, for example, operate on the user profile 140 (e.g., a patient pathology profile 260 retrieved from and / or through association with the user profile) as a function of the medical profile 250 to generate an associated patient treatment profile (not shown). For example, the medical analysis engine 240 can, for example, determine recommended media content based on the user profile 140 as a function of the medical profile 250, the media profile 145, and / or the motivational profile 265 of the user profile 140. For example, the medical analysis engine 240 can include a machine learning model for automatically redefining and / or updating weights associated with attributes of the patient treatment profile based on user input (e.g., micrologs, changes in pathology profiles, changes in media profiles, caretaker input, authorized professional input).

[0072] In some embodiments, the assessment engine 125 may, for example, operate on the user profile 140 and / or the micro log 255 to determine the current state of the associated user. In some embodiments, by way of example and not limitation, the assessment engine 125 may operate on the user profile 140 and / or the micro log 255 associated with a patient (e.g., STU 105) to determine the user's current state (e.g., in a pathology process) as a function of the medical profile 250. In some embodiments, the assessment engine 125 may, for example, operate on the user profile 140 and / or the micro log 255 to determine the current state of the associated user. In some embodiments, by way of example and not limitation, the assessment engine 125 may operate on the user profile 140 and / or the motivational profile 265 associated with a patient (e.g., STU 105) to determine the user's motivational profile 265.

[0073] In some embodiments, when it is determined that in-person intervention is needed, the assessment engine 125 can generate a message to the medical professional interface 215 and / or the intended caretaker 270. For example, the assessment engine 125 can be configured, by way of example and not limitation, to access a user-generated dynamic state profile 275 of the user's current mental health state using, for example, the Sleep, Interest, Attribution, Energy, Concentration and Minima, Psychomotor and Suicidal Ideation (SIGECAPS) framework. For example, the assessment engine 125 can determine to contact the intended caretaker 270 based on the updated dynamic state profile 275.

[0074] Figure 3is a flow chart illustrating an exemplary runtime method 300 of an exemplary DIPGS. For example, MMPP 120 may be used to perform method 300. Method 300 begins at step 305 when input is received from a user device. For example, device 106 may transmit input from STU 105 to MMPP 120. In some embodiments, MMPP 120 may include a continuous evaluation engine to help determine, by way of example and not limitation, the effectiveness of a game, a list of recommended games, whether a user should be directed to a higher level of personal care (e.g., rather than self-treatment).

[0075] For example, the STU 105 may use the MMDA 110 to send user input including a micro-log description of the self-assessment to the MMPP 120. In decision point 310, it is determined whether the user is a new user. If the user is a new user, then in step 315, a new user profile is generated based on the received input. For example, the new user profile may be stored in the user profile 140. If the user is not a new user, then in step 320, the existing user profile is updated based on the received input. For example, the assessment engine 125 may update the micro-log 255 in the user profile 140 based on the user input.

[0076] For example, input to the operations in step 305 may include responses to a predetermined set of questions presented to the STU 105. In some embodiments, the set of questions may be retrieved from the data store 135 and presented to the STU 105. In some embodiments, the set of questions may be dynamically generated, for example, based on responses from the STU 105. In some embodiments, the set of questions may be provided to the STU 105 by a third party (e.g., the STU 105 may be directed to the set of questions and / or a signal indicating results from the third party set of questions may be sent to the MMPP 120).

[0077] After step 315 or step 320, in decision point 325, it is determined whether to end method 300. For example, STU 105 may shut down MMDA 110 after completing micro-logging. If method 300 is to end, method 300 ends.

[0078] If the method 300 is not terminated, media recommendations are generated based on the user profile in step 330. For example, the MMGE 130 may generate a list of recommended wild games 150 to the user based on the user profile 140 of the user. Next, in step 335, the recommended media is delivered. In some embodiments, the media may be delivered, for example, from and / or through the WMP 115. For example, the MMPP 120 may deliver a link in the WMP 115 to the STU 105. For example, the MMPP 120 may deliver a DIMP including the recommended media to the STU 105. For example, the media analysis engine 235 may be run on the user profile 140 to generate recommended media by way of example and not limitation, the media profile 145, the pathology profile 260, the medical profile 250, the motivation profile 265, the assessment engine 125, the patient pathology profile 260, and / or the dynamic state profile 275.

[0079] In step 340, user responses are recorded in a background process while in the induced state of the media. For example, DIPSM 160 may transmit user profile 140 based on user interactions within wild game 150 in the induced state. For example, the responses may be transmitted periodically. For example, the responses may be transmitted when predetermined criteria are met.

[0080] At decision point 345, a determination is made as to whether to make a state transition. For example, DIPSM 160 may determine that a transition from the induction state to the treatment state is made when a predetermined set of criteria generated by MMPGE 130 is met. If a state transition is not to be made, step 340 is repeated. If a state transition is to be made, then at step 350, the media is interrupted, the digital therapeutic (e.g., TIMP 190) is delivered to the user (e.g., MMDA 110), and step 305 is repeated. For example, DTx module 155 may include, by way of example and without limitation, treatment recommendations and / or instructions (e.g., at least in combination with Figure 1B For example, the STU 105's responses, media suggestions and / or a history of selected media, a history of interactions with delivered media, or some combination thereof may be saved in association with the user profile 140 (e.g., in a micro-diary 255).

[0081] After step 320, the user profiles 140 of other users are updated (e.g., media profiles 145, pathology profiles 260, medical profiles 250, motivational profiles 265). For example, the user profiles 140 may be updated based on actual actions and / or responses of similar users to improve accuracy, rather than relying solely on initial self-assessments.

[0082] In various implementations, DIPSM 160 is used to identify a treatment instance in DIPGS during runtime of DIPGS, interrupt runtime of DIPGS, present one or more treatment modes to the user, and update the user profile and DIPGS based on the results of the treatment modes.

[0083] Figure 4 An exemplary architecture 400 of an exemplary risk assessment engine of the DIPGS is shown. In the described example, for example, the guidance and warning layer 405 can provide media and / or prompts to the user and / or receive input from the user. For example, the observation layer 410 can generate metrics corresponding to predetermined criteria based on the guidance and warning layer 405. The risk assessment layer 415 can generate instructions and / or messages corresponding to the recommendations based on the metrics. In some embodiments, the assessment engine 125 can include the guidance and warning layer 405, the observation layer 410, and the risk assessment layer 415.

[0084] like Figure 4 As shown in the illustrative example of , STU 105 may be, for example, a self-processing of using media in WMP 115. Observation layer 410 may receive (eg, via presentation layer modules) input corresponding to STU 105 using media and / or progress associated with monitoring conditions.

[0085] As an illustrative example, the observation layer 410 can be used to collect information about health indicators (e.g., prompting the user to enter a rating). For example, a user can seek to self-treat pain and / or range of motion limitations. For example, a user can rate pain and / or range of motion. A game can be suggested and / or delivered that entices the user to move incrementally in a way that can address pain and / or range of motion limitations. The observation engine can prompt the user to provide periodic feedback. Based on the feedback, the evaluation engine can make recommendations (e.g., continue playing, play another game, seek further help). For example, a "recommended" recommendation can be generated based on a predetermined metric (e.g., a pain scale and / or pain metric increase exceeding a predetermined recommendation standard).

[0086] Thus, the observation layer 410 can advantageously help the user become more aware of predetermined factors (e.g., pain, depression, etc.). In some embodiments, the observation layer 410 can observe the user's behavior (e.g., during the game, at the end of the game) to collect health metric information. For example, based on the collected information, the observation layer 410 can request a response from the user (e.g., recommend a game, send a questionnaire). For example, in an illustrative use case about depression, if the user ranks their emotions corresponding to mild / moderate depression, and the user feels better after playing, the suggestion layer and / or engine can generate a message recommending tomorrow's play. If the user feels worse, a message can be generated to recommend the user to play a different game. If the user indicates additional stress and / or significant deterioration, a message and / or indication can be generated prompting the user to seek help (e.g., a predetermined caretaker).

[0087] In some embodiments, the observation layer and / or engine can monitor the user's physical attributes. For example, physical monitoring can include biosensors (e.g., heart rate, temperature, blood pressure). In some embodiments, physical monitoring can include, for example, a camera. For example, a camera can be used to detect gestures. In some embodiments, a metric can include response speed (e.g., during game play). For example, recommendations can be determined based on physical attributes.

[0088] The risk assessment layer 415 may operate based on metrics determined from the inputs by the observation layer 410. The risk assessment layer 415 may compare the metrics to predetermined criteria related to progress and / or risk. The risk assessment layer 415 may generate one or more signals to change the visual indicia presented to the STU 105 as a function of the metrics and the predetermined criteria (e.g., risk scale). For example, the guidance and warning layer 405 may cause (dynamic) indicia 435 to respond to signals from the risk assessment layer 415. For example, indicia may be presented in the treatment interface 170, such as Figure 1A -B.

[0089] As an illustrative example, the risk assessment layer 415 may include a risk assessment and / or notification engine for generating alerts, reminders, and / or instructing a player to seek additional attention during an attempt to use gaming as a coping mechanism. For example, by way of example and not limitation, a player may be instructed to seek additional help when a player's self-assessed symptoms exceed a mild to moderate level, when a player's mood while playing the game moves toward a negative direction, or when a player's mood tends to be more negative during a duration when relaxation or at least stability is desired. In some embodiments, the assessment engine 125 may be used to further assist an individual in obtaining appropriate resources for their health issues (e.g., mental, physical) based on one or more factors (e.g., including self-assessment, interaction with the self-assessment, and the gaming system).

[0090] In this example, the STU 105 presents a visual marker 420. In some embodiments, the marker 420 may include a help button. For example, the STU 105 may use the help button to self-identify help. For example, the STU 105 may click on the help button to report the perception of the potential problem to the caretaker 430 (e.g., a scheduled caretaker, a suggested caretaker). In some embodiments, the help button may change shape and / or color according to the intensity of the risk. For example, when the risk level is low, the shape of the help button 425a may be gray and rectangular, as in the described example. When the risk level increases, for example, the help button 425a may change from gray to green, and the shape of the help button 425b may change from rectangular to circular. In this example, when the risk level further increases to medium-high risk, the help button 425b may increase in size and change color to yellow, as shown in the help button 425c. When the risk level is high, as an example, the size of the help button 425d may further increase, the text may turn red, and it may flash.

[0091] In various embodiments, the assessment engine 125 may include a safety mechanism that is configured to make a referral to a predetermined caretaker 430 (e.g., a predetermined caretaker 270 stored in the data store 135) in all cases where the media will not or will not continue to serve the individual to address their health condition. The predetermined caretaker 430 may, for example, include a family member. The predetermined caretaker 430 may, for example, include a professional service or similar helpline. For example, the referral can help the individual self-assess and / or recognize the need for a higher level of care. For example, the recommendation can provide an access point for advice on care.

[0092] In various embodiments, the media may advantageously act to engage and keep individuals in assessing their level of physical / mental health and on a path of self-discovery that may lead to seeking additional care. In an illustrative example, video game players and / or other individuals with mental health conditions may access information online through a peer-to-peer network, or may be able to self-discover that video games may be a source of relief for mental health symptoms. However, in making such self-determination decisions, selecting and playing these games, they may not select games that are appropriate or best for them. Furthermore, if the individual does not find the relief they are seeking, use of video games for a particular condition may not be necessary and / or may cause additional harm. The act of self-identifying support or care needs is an important step, for example, and may be an ongoing process of receiving care, especially for those who are unable and / or cannot afford care.

[0093] In some examples, conditions may exist where, once an individual self-identifies as having a mental health issue, they may not be motivated to continue self-monitoring and assessment to help determine if the selected game is helping their condition, or, more generally, if the condition is becoming more severe outside of the gaming experience.

[0094] Recommending against the use of video games to address mental health conditions may remove an important option as a family coping mechanism and does not represent a realistic approach to dealing with the current mental health support and treatment environment, nor does it represent how individuals continue to view games and other media sources as aids to health and personal improvement. Accordingly, method 300 may advantageously address the technical problem of assisting self-treating patients by providing a dynamically generated immersive treatment mechanism based on monitoring and tracking mechanisms in an unregulated media content environment of STU 105.

[0095] In some embodiments, DIPSM 160 may be used to adjust a predetermined set of run-time parameters for the DIMP based on the therapy profiles of the TIMP 190 and DTx module 155 in TIMP 190 and the user profile 140 .

[0096] As an example, a patient may download the MMDA 110. The MMDA 110 may prompt the patient to answer some questions upon registration. For example, in response to receiving user input, the assessment engine 125 may determine in response to the questions that the patient is feeling bad (e.g., feeling low, feeling bad). The assessment engine 125 may determine that the patient is associated with post-traumatic stress disorder, anxiety, and / or trauma. For example, the assessment engine 125 may determine that the patient is depressed due to trauma and / or depression is so associated with trauma that it must be addressed before other issues based on information from a therapist.

[0097] The assessment engine 125 may determine that recreational exercise is needed (e.g., based on input from the patient and / or therapist, based on historical results of other patients with statistically similar responses within a predetermined confidence interval). The MMPP 120 may recommend a Tetris-based game ("tetris"). The patient may acquire (e.g., purchase, download) Tetris (e.g., on WMP 115, purchase the standalone game). The patient may log into the Tetris game in a manner that notifies the assessment engine 125 that access to Tetris is complete.

[0098] In response to the notification, MMPP 120 may cause MMDA 110 to generate an interface with warnings and alerts (e.g., as authorized by FDA regulations). MMPP 120 may cause the application to generate an interface (e.g., "Based on the data you provided, I want you to see when you experienced traumatic events and what scares you."). For example, DIPGS 100 may prompt the user to play Tetris (e.g., "Try playing Tetris for 20 minutes"). After the suggested time and / or when MMPP 120 is notified that the user has stopped playing, MMPP 120 may cause the application to generate an interface (e.g., therapy interface 170) asking the patient one or more questions about how the patient is feeling now (e.g., 1-2 short questions). MMPP 120 may suggest follow-up actions (e.g., "You should do this again tomorrow").

[0099] Thus, DIPGS 100 may use playing Tetris, by way of example and not limitation, to induce a patient to reconnect with trauma-related thoughts. For example, DIPGS 100 may not alter the game at all from a "normal" non-medical practice. DIPGS 100 may use Tetris as a tool for medical treatment, suggesting that a patient think about something while playing.

[0100] For example, DIPGS 100 may be collecting and / or analyzing monitoring and / or feedback data to understand why a patient is depressed. For example, DIPGS 100 may help a patient treat depression through a collection of games. For example, DIPGS 100 may add therapeutic elements (e.g., tags, suggestions) to these games. For example, DIPGS 100 may track a patient's behavior over time in a user profile 140 (e.g., provide patient and / or physician feedback to gain insight into a patient's performance and / or how well a treatment is working).

[0101] In some embodiments, DIPGS100 can be used to enable patients to perform self-directed care. For example, in the above figure, if the patient responds that the patient does not want to play Tetris, MMPP120 can suggest other puzzle games. If the patient does not want to play puzzle games, but likes to play action games, MMPP120 can suggest playing action games.

[0102] For example, the patient may play an action game. Once the patient is a little anxious, the assessment engine 125 may come back again and suggest that the patient try thinking about these traumatic moments for a minute and then go play some Tetris. The patient may play for a while and then express boredom with playing Tetris. The assessment engine 125 may encourage them and suggest another jigsaw puzzle game while performing the therapeutic action (e.g., thinking about the trauma first). In some such examples, the game may be unchanged relative to the "off-the-shelf non-therapeutic use". In some embodiments, a kernel (e.g., a check-in module) may be provided.

[0103] In some embodiments, the guidance and alert layer 405 may also include general health software functions to promote, track and / or encourage choices as part of a healthy lifestyle, which may help with healthy living, or reduce the risk of certain chronic mental illnesses or diseases, where the link between healthy living and reducing the risk or impact of chronic mental illnesses or diseases is well known. For example, chronic mental illnesses may include depression, anxiety, obsessive-compulsive disorder, autism, attention deficit hyperactivity disorder. The platform may also provide physical health and general health treatments and guidance.

[0104] In some examples, the general health software functionality may provide statements such as: "Device X provides daily motivational reminders to perform physical activity, which can help people with chronic depression live well" or "Device Y provides memory and meditation activities, which can help people with chronic anxiety live well."

[0105] In some embodiments, the universal wellness software functionality can help patients diagnosed with mental illness maintain their behavioral coping skills, including non-binding recommendations 12, by providing “daily skills” behavioral techniques or audio messages that users can access when they are experiencing increased anxiety related to the COVID-19 public health emergency.

[0106] In some implementations, the universal wellness software functionality can help users “just notice,” “accept,” and “accept” difficult or previously undesirable thoughts and feelings during the COVID-19 public health emergency, thereby opening the user up to learning not to overreact to these unpleasant feelings or avoid situations in which they are called upon. In some examples, the universal wellness software functionality can present images or other messages at opportune times for substance users who want to stop addictive behaviors due to increased anxiety during the COVID-19 public health emergency.

[0107] In some examples, the general health software functionality may help a patient or user self-manage their disease or condition without providing specific treatment or therapy recommendations. In some examples, the general health software functionality may use a checklist or questionnaire to identify common signs and symptoms of mental illness (e.g., anxiety due to a stay-at-home order) and provide a list of possible medical conditions and recommendations for when to consult a healthcare provider. In some examples, the general health software functionality may guide a user through a questionnaire on signs and symptoms of mental disorders (e.g., anxiety or stress due to a stay-at-home order) and provide recommendations for the type of medical facility that best suits their needs.

[0108] Figure 5An exemplary use scenario for providing an exemplary independent digital therapy (IDTx) mode is described. In this example, the STU 105 may be in a non-gaming suitable environment 500. For example, the STU 105 may be working in an office and may not be able to play games. However, if Figure 5 As shown, STU 105 may want to get help with breathing. In this example, STU 105 can use MMDA 110 to transmit a help signal specifying help. For example, the help signal can indicate that STU 105 needs help with breathing. For example, the help signal can indicate that STU 105 is experiencing an anxiety attack.

[0109] After receiving the help signal, the MMPGE 130 may process the help signal to determine that the presentation of the DIMP is inappropriate, for example, based on environmental constraints. In some embodiments, the MMPGE 130 may determine the non-game appropriate environment 500 based on the user profile 140 and the location of the STU 105 .

[0110] In this example, the MMPGE 130 determines to generate a respiration-related IDTx 505 based on the user profile 140 of the STU 105. For example, the respiration-related IDTx 505 may be a reduced DIMP. For example, the MMPGE 130 may access the microlog 255, the incentive profile 265, and the dynamic state profile 275. For example, the MMPGE 130 may determine the respiration-related IDTx 505 based on historical user feedback and historical game play of the STU 105 and / or similar users.

[0111] As shown, the breathing-related IDTx 505 includes a breathing DTx 510 and a specification 515. For example, the breathing DTx 510 can be generated based on a TIMP previously played by the STU 105. For example, the specification 515 can be dynamically generated based on the breathing DTx 510 and the user profile 140. In some embodiments, the specification 515 may include instructions and warnings for guiding the user. In this example, the specification 515 may include guidance for the user to perform breathing exercises. For example, the guidance can be generated by artificial intelligence based on the breathing DTx 510, the user profile 140, and the media profile 145.

[0112] Upon receiving the specification 515, the MMDA 110 generates a virtual treatment room 525. In some embodiments, the virtual treatment room 525 can provide a short-term immersive treatment experience for the user. For example, the virtual treatment room 525 can provide the user with 3-minute breathing exercises and anti-anxiety music and / or videos.

[0113] In various implementations, when DIPGS 100 determines that the presentation of a DIMP is not appropriate based on environmental constraints or based on receiving a user request, DIPGS 100 may generate a streamlined DIMP including a TIMP 190 based on the user profile and the history of the DIMPs played. Accordingly, for example, DIPGS 100 may advantageously provide a solution to provide the public with a simple tool to assist the user's health status based on the user experience, regardless of the environment, and without being attached to a game or a specific media. For example, DIPGS 100 may act as an "assistant" for health self-assessment (e.g., physical, mental).

[0114] Figure 6 An exemplary digital gaming cloud (DGC 600 ) is shown for delivering a DTx game employed in an illustrative use case. For example, a user 610 may receive a DTx game 605 from a gaming platform 615 .

[0115] In some embodiments, DGC600 may include MMPP120 to advantageously implement the personalization, planning, coordination, tracking, and / or delivery of video games as an integrated platform for digital therapeutics. For example, DTx game 605 may include a DIMP generated by MMPGE130. For example, DGC600 may be used in conjunction with one or more supported gaming platforms (e.g., WMP115). For example, DGC600 may enable user 610 to play a game at a local location of the game. For example, DGC600 may remove the regulatory burden from individual games, allowing the game to proceed as originally intended. For example, DGC600 may advantageously perform the required regulatory work (e.g., all regulatory work) to ensure the safe and effective delivery of mental health treatment using games delivered by DGC600.

[0116] As a further combination Figure 7-8 For example, DGC 600 can manage regulatory burdens by delivering games that have been cleared as medical devices, delivering games with health claims associated with cleared games, and / or delivering games in which DGC 600 performs regulatory work including, but not limited to, labeling, treatment settings, and / or follow-up (pre-game and / or post-game messaging delivery, monitoring, or inquiry).

[0117] In various implementations, the DGC 600 may receive usage information from the game platform 615. For example, the DGC 600 may identify from data provided by the game platform 615 that the user 610 is playing a particular game at a particular time. In some implementations, the interconnectivity between the game platform 615 and the DGC 600 may be provided by a digital connection between the game platform 615 and the DGC 600. For example, in some implementations, the DGC 600 may at least provide a signal identifying which game the user is playing and when. In some implementations, when such a connection may not exist, the DGC 600 may allow the user 610 to manually report usage information (e.g., usage and play duration of the game).

[0118] Figure 7 6 is a block diagram describing an exemplary DGC. In this example, the DGC 600 includes an initial self-assessment tool 705 and a log module 710. For example, the initial self-assessment tool 705 can help the user 610 determine which games are most suitable for their health problems and current state of dysfunction. For example, the initial self-assessment tool 705 can use the assessment engine 125 to assess the user's current state to recommend the most suitable game.

[0119] In some embodiments, the initial self-assessment tool 705 may include an entry point self-assessment tool for helping the user determine whether the DGC is appropriate for the player's needs. For example, the entry self-assessment tool may determine (e.g., based on the archive in the data store 135) whether the currently cleared platform instructions are used (e.g., predetermined clearing instructions associated with pathology archives, treatment archives, and / or dynamic pathology states) to meet the user's needs and current archive. For example, if mild to moderate stress, anxiety, and depression symptoms are cleared, the self-assessment tool may be configured, for example, to help the user self-determine whether they have appropriate symptoms and whether these symptoms are actually consistent with a mild to moderate form of disease state. The DGC 600 may be configured so that the information, for example, may also form a basis or baseline for further self- and / or system-based assessments.

[0120] In some embodiments, the initial self-assessment tool 705 may help the player determine which game is best suited for the player's motivation / play type (e.g., assessment engine 125), pathology (e.g., mental health issues) (e.g., patient pathology profile 260), and current state of dysfunction associated with the pathology (e.g., dynamic state profile 275).

[0121] The log module 710 may include ongoing self-assessment tools, for example, that may help the user 610 determine which games are best suited for their health issues and current state of dysfunction. In some embodiments, the log may be done as a micro-logging tool that may use AI and lastly context / situational awareness to bring small, recorded comments from the user 610 into context. In some embodiments, the log module may advantageously reduce the need for the user to spend a lot of time recording or explaining feelings. In some embodiments, the log recording tool may include methods that allow the user 610 to rate their current state before, during, or after play. These methods include, but are not limited to, picking a list of words related to the game or the player's current physical or mental health, recording spoken words with options for conversion to written words, using short sentences or small phrases, all of which are related to recent game play experiences. (Contextual Awareness) Context that helps get information from the patient / player.

[0122] In this example, DGC600 also includes a game selection module 715. For example, user 610 can use game selection module 715 to select a game according to its intended use or associated use. In some embodiments, game selection module 715 can generate a suggested game play list. For example, a game list can be organized according to the suggestions of use instructions, associated use, action mechanism, type, platform and / or other similar users. In some embodiments, game selection module 715 can generate a suggested next game list. For example, the next game play list can be generated based on a predetermined processing path based on initial user input and / or standard processing protocol and / or a game played before responding to the user's experience or an update to a user self-assessment tool or diagnostic tool.

[0124] In some examples, the game selection module can recommend additional games based on the responses and measured progress of the user 610. For example, the user 610 can make his or her own selection from a pre-selected game set. In some embodiments, the recommended game can be a successful game of the game history of the user 610. In some examples, the therapeutic mechanism used in the recommended game can be shown to the user 610. In some embodiments, the game selection module 715 can recommend games based on past game history and / or its game preferences or statistics of preferences for other players with similar characteristics (including but not limited to health problems, similar responses to treatment, or other similar treatment preferences) to advantageously promote more neural engagement, thereby potentially achieving a higher success rate. Further, users can obtain game selections from other platform users they follow or connect to so that they can choose similar games / treatment paths.

[0125] In this example, the DGC 600 includes a warning and alert delivery module 720. For example, the warning and alert delivery module 720 can deliver warnings and alerts as required by relevant regulatory agencies. In some embodiments, the DGC 600 can provide guidance to the user 610 before, during, and / or after the game to help focus on the therapeutic intent of the DTx game 605. In some embodiments, the warning delivery module 720 can be combined with Figure 4 In some embodiments, 720 can provide pre- and / or post-explanation and / or suggestions on how to get more out of the game and / or therapy based on the game instructions for the game and / or the motivational tool used for the game as therapy.

[0126] The DGC 600 includes a platform communication module 725 for connecting the DGC 600 to a gaming platform 615. In some embodiments, the DGC 600 can be connected to a gaming platform 615 implemented via software and / or middleware-based connectivity. For example, the connectivity can allow the DGC 600 to know the length of a game that the user 610 is playing.

[0127] DGC600 includes a game feedback module 730 and a feedback analysis module 735. In some embodiments, the game feedback module 730 can recommend game use based on its experience using games for treatment. In some embodiments, the feedback analysis module 735 can track the user 610 game and obtain self-evaluation, including surveys, (micro) logs and other forms of self-reflection and reporting, for example, using the collected data to improve the recommended treatment path for a specific DGC user. In some examples, the feedback analysis module 735 can use the collected data to improve the recommended treatment path for other DGC users with similar needs, history and / or other catalogued characteristics.

[0128] In some embodiments, the DGC 600 includes a medical professional module 740 (e.g., in the medical professional interface 215) for providing an interface for therapists and / or related medical professionals (e.g., medical professionals) to view the game play history, self-assessment, and other related reports of DGC users, including but not limited to log records, micro-log records, user associations, or any other information that may help medical professionals understand the current mental and / or physical health status of users. For example, the medical professional module 740 may include a means for medical professionals to shape or suggest games, treatment mechanisms, themes, or treatment directions or control other parts of the platform to improve the user's treatment experience and results. In some embodiments, medical professionals can use the medical professional module 740 to assign homework or other auxiliary work in conjunction with the patient's treatment plan to create a coordinated treatment method. Medical professionals can also use the information provided by the platform to create a more complete patient profile or understanding to develop a more coordinated treatment plan.

[0129] In some embodiments, a user may be provided with control over data privacy of the data recorded and / or recorded data. For example, a user may be provided with an option to transmit raw log and / or log data to a medical professional using the medical professional module 740. In some examples, a user may be provided with an option to transmit a summary and / or edited (e.g., manually, automatically) log and / or log data to a medical professional. In some embodiments, by way of example and not limitation, a user may be provided with a customized presentation of historical data (e.g., log records). For example, the DGC 600 may generate different (e.g., customized) historical data presentations to medical professionals.

[0130] In this example, DGC600 includes a revenue module 745 for determining that DGC is a recommended source for purchasing and playing games suitable for satisfying. Contractual obligations and calculations of shared revenue agreements signed with a series of potential partners (including but not limited to game developers / publishers, processing professionals, supplementary platforms and other processing or game-related tools and services). For example, the revenue module 745 can determine the DTx game 605 of DGC600 that was previously recommended to the user 610. For example, the revenue module can track the usage data and billing access of DGC600. In some examples, the revenue module 745 can determine that part of the proceeds from purchasing a separate game can be billable.

[0131] In this example, the DGC 600 uses the regulatory module 750 to meet regulatory requirements. In some embodiments, the regulatory module 750 can advantageously minimize the impact on game developers and simplify the ongoing verification and validation requirements for the game platform (e.g., centralizing on a web-based platform for ingestion and tagging and other required regulatory functions that require ongoing verification and validation). For example, when the DGC 600 is delivering the DTx game 605, there may be regulatory requirements for all digital therapeutic games that make therapeutic claims that are not cleared as medical devices alone.

[0132] Figure 8 An exemplary regulatory module for satisfying regulatory requirements for DTx games is described. For example, the DGC 600 may use the regulatory module 750 to satisfy regulatory requirements for at least some DTx games that would not be cleared as medical devices on their own.

[0133] As shown, the supervision module 750 includes a software testing module 805, a network security module 810, a labeling module 815, and a user agreement generator 820. For example, the software testing module 805 can perform software verification, validation, and risk analysis to ensure that the device implements the treatment model as expected. For example, the network security module 810 can provide appropriate network security protection that complies with authorization (e.g., FDA's pre-sale and post-sale recommendations). For example, the labeling module 815 may include user instructions for instructing the patient to contact a doctor before using the device. For example, the user agreement generator 820 may be prompted to confirm the advice to contact a doctor before use. For example, the user agreement generator 820 may provide an independent checkbox separated from the end user license agreement. In some embodiments, the end user license agreement may include a clear statement that the patient can contact a doctor before using the device, even if the device is sold directly to consumers.

[0134] In some embodiments, the end user license agreement may include user instructions for providing information on how to access additional resources related to the treatment of mental illness. In some examples, the instructions for use may include images that demonstrate how to use and interact with the device. For example, the conditions may include reference to recommendations made to the public by medical professional organizations (e.g., the American Psychological Association or other associations, etc.). In some embodiments, the end user license agreement may clearly describe the instructions for the device, including the mental illness / disorder that the device is intended to treat, and a description of the expected patient population (symptom type, duration, severity, and age range (adults vs. children / adolescents), etc.) for which it is expected to be effective. In some embodiments, the label module 815 may provide a description of the treatment method (behavioral therapy, cognitive restructuring, etc.). In some embodiments, the end user license agreement may clearly describe the recommended duration and frequency of use.

[0135] In some embodiments, the end user license agreement can provide a summary of clinical testing with the device. In various embodiments, the summary can include an outline of available clinical performance testing, including methods (e.g., clinical endpoints studied, study type, sample size, etc.) and results (e.g., group / responder analysis, performance goals, etc.). In some embodiments, the summary can include a statement that the device has not been clinically tested and therefore may have unknown benefits and risks.

[0136] The end user license agreement may, for example, describe the method for determining any medical advice. In some examples, the end user license agreement may provide a prominent notice to the patient and healthcare provider, as applicable, that the advice provided by the device is auxiliary (supportive) and cannot be relied upon entirely or primarily for the treatment of mental illness. In some embodiments, the end user license agreement may provide a warning that the device does not represent a replacement for the patient's medication. In some examples, the end user license agreement may provide a statement about whether a prescription is available for the device. In some examples, the end user license agreement may include instructions on when (under what circumstances, how often) the user should consult a healthcare provider. In some examples, the end user license agreement may also include clear instructions on what to do if symptoms are not improved, and what to do within the expected time period. For example, the end user license agreement may include instructions on how to deal with medical emergencies. For example, the end user license agreement may include clear identification of any device indications / functions that are not approved by the FDA.

[0137] In some embodiments, DGC600 may deliver the game as a non-medical device that encourages a healthy lifestyle that is not related to a specific diagnosis, cure, mitigation, prevention, or treatment of a disease or condition. For example, DGC600 may include general health software features that are not related to a specific disease or condition, such as promoting relaxation, mindfulness, meditation, and / or reducing stress, fatigue, or isolation due to the COVID-19 public health emergency or other situations that create isolation or perceived isolation for users. For example, DGC600 may include general sleep software features related to sleep, such as promoting good sleep, improving sleep experience, more relaxing or restful sleep, nighttime sleep, or full night sleep. For example, DGC600 may include general health software features related to mental health or mental illness, such as DGC600 providing motivational prompts through text and other messages that are intended to reduce stress and promote a positive mental outlook that can help users live well during the COVID-19 public health emergency or in general or perceived isolation.

[0138] As an illustrative example, the DGC 600 may include a tagging engine (e.g., in the guidance and warnings layer 405) for generating (digital) tags to help individuals understand warnings and alerts related to playing games, with the expectation of alleviating symptoms of mild / moderate depression, anxiety, or stress.

[0139] In various embodiments, upon receiving a change at one of the DTx games 605, the treatment profile 280 of the changed media content is updated based on a predetermined set of validation rules so that the changed media content complies with the validation rules and is appropriate for the treatment intent.

[0140] Fig. 9An exemplary method 900 for verifying a wild game as a DTx game is described. For example, the method 900 may be performed by the regulatory module 750. In this example, the method 900 begins when an update of a verified DTx (e.g., a DTx module 155 in the data store 135) is received from the gaming platform in step 905. For example, the gaming platform 615 may notify the DGC 600 of the update via an interconnection between the gaming platform 615 and the DGC 600. For example, a game developer may change a portion of an unregulated game (e.g., a wild game 150) (e.g., a background color of one of the displays).

[0141] In step 910, the validation rules are retrieved. For example, the supervisor module 750 can retrieve the validation rules from the medical validation rules 220. Next, the updated DTx is evaluated based on the validation rules retrieved in step 915. For example, the software testing module 805 can test the updated component according to the validation rules.

[0142] At decision point 920, it is determined whether the updated DTx complies with (e.g., regulatory rules). If so, then at step 925, an updated treatment profile for the DTx is generated and the method 900 ends. For example, the treatment profile 280 can be updated based on the changes in the DTx. For example, the label module 815 can generate appropriate labels based on the updated components to generate the updated DTx. Accordingly, it can be advantageously verified that the DTx is suitable for the treatment intent.

[0143] If not, then in step 930, an error report is generated and the update is rejected, and method 900 ends. For example, the error report may include the reason for the rejection. PCT patent application serial number PCT / US2021 / 071585 describes various embodiments of testing and validating non-medical digital components of medical digital assets, entitled "Immersive Medical Translation Engine for Development and Reinstallation of Non-Verified and Verified Code", filed by Ryan J. Douglas on September 24, 2021, the entire contents of which are incorporated herein by reference.

[0144] Fig.10 An exemplary method 1000 for delivering a dynamic induced media package (DIMP) to a user and providing continuous monitoring is shown. For example, MMPP 120 can be used to perform method 1000. Method 1000 begins when a signal corresponding to a user's request for media is received in step 1005. For example, the requested media can be an unregulated game (e.g., wild game 150). In step 1010, the user is prompted to answer a predetermined question. For example, assessment engine 125 can transmit the question to device 106.

[0145] Next, in step 1015, the user profile is updated based on the received answers. For example, the evaluation engine 125 can update the user profile 140 based on the answers received from the transmitted questions. After the user profile is updated, in step 1020, transition criteria corresponding to the requested media are dynamically generated. For example, the MMPGE 130 can generate state transition criteria for the wild game selected by the user. In step 1025, a DIMP is generated based on the requested media and one or more DTxs.

[0146] After the DIMP is generated, the user's behavior is observed during the runtime of the requested media in step 1030. For example, the observation layer 410 may observe the user's behavior while playing the wild game 150. In decision point 1035, it is determined whether the state transfer criteria are met. If the state transfer criteria are not met, step 1030 is repeated.

[0147] If the state transition criteria are met, the validated treatment content is presented in step 1040. For example, DIPSM 160 may transition DIMP from the induction state to the treatment state, and MMPGE 130 may generate a treatment interface 170 to be presented on device 106. In step 1045, the user's progress is evaluated. For example, evaluation engine 125 may evaluate the responses received from treatment interface 170.

[0148] In decision point 1050, it is determined whether the user's health condition has been improved. For example, the assessment engine 125 may specifically assess the user's anxiety. If the user's health condition has been improved, a notification message is generated in step 1055, and step 1030 is repeated. If the user's health condition has not been improved, a suggestion is generated in step 1060. For example, the guidance and warning layer 405 may generate some suggestions based on the user's dynamic status profile 275.

[0149] At decision point 1065, a determination is made as to whether intervention is required. For example, risk assessment layer 415 may determine in the assessment step that intervention is required when the user's condition is below a predetermined intervention threshold. If intervention is not required, step 1030 is repeated.

[0150] If intervention is required, then the intervention is generated in step 1070. For example, the risk assessment layer 415 may generate a message to a predetermined caretaker 270 to check on the user.

[0151] Although various embodiments have been described in conjunction with the accompanying drawings, other embodiments are possible. In some implementations, DGC 600 (e.g., using an application as a "wrapper" to deliver a medical treatment associated with a non-medical / unregulated game) can, for example, advantageously enable distributors to deliver back catalog games with minimal intervention by the developer. For example, it can provide a new revenue stream for developers of existing games. For example, it can enable game developers to associate games well. For example, it can provide powerful treatments for patients.

[0152] In some embodiments, DGC 600 can monitor the environmental conditions of the game. In some embodiments, DGC 600 can suggest that the game can also be used as an independent medical device outside the application environment.

[0153] As an illustrative example, a game (e.g., "Game X") may be provided through the platform of the system. The diagnostic engine of DGC600 (e.g., part of MMPGE130, in cooperation with the selection engine) may prompt the user that a specific problem exists. The system may suggest that Game X has the highest historical success rate in solving a specific problem (e.g., based on diagnostic factors, environmental factors, personality). Game X may be recommended. DGC600 may enable users of Game X (e.g., Game X may not be medically approved and / or delivered) to be associated with medical treatment by providing tags and / or treatment input and / or monitoring related to playing Game X. DGC600 may monitor (e.g., through an API, through user input) how the interaction with Game X proceeds. For example, the system may have feedback information from Game X. In some embodiments, by way of example and not limitation, the information may include at least (a) user login to the game (e.g., confirmation that the user is playing the game), and (b) play duration (e.g., when the user starts and stops playing the game).

[0154] In some embodiments, MMDA110 may not be a medical device. For example, MMDA110 may be used as a collection device. MMDA110 may enable device 106 to transmit data (e.g., unchanged) to DGC600 (e.g., cloud server). Accordingly, MMDA110 or device 106 may not need to be verified as a medical device. Medical devices may, for example, be embodied in a cloud server (e.g., MMPP120 or DGC 600). Server-based systems (e.g., including diagnostic engines, selection engines, monitoring engines) may be maintained, verified and / or validated (e.g., according to regulatory controls). Accordingly, for example, wild games 150 may be 'free games', and / or applications may be 'free mobile apps' without the need for continuous verification. As an illustrative example, a distributed network of servers may be managed to comply with regulations (e.g., comply with ISO13485).

[0155] In some embodiments, the MMDA 110 and / or wild games 150 can be configured so that they cannot disrupt the healing mechanism. For example, the healing mechanism can advantageously rely entirely on a server-based system. The system can receive, analyze, and / or respond to information from the game and / or the patient. The system can interact with the patient through an application. The system can send information to the game (e.g., generate a presentation, prompt a play time report).

[0156] For example, the cloud server can execute a program of instructions to recommend games to play (e.g., via a diagnostic engine and / or a selection engine), monitor when a game is completed (e.g., via a monitoring engine), recommend that the patient perform therapeutic actions, and / or inquire and review what the patient has worked on. For example, the DGC 600 can provide an interface for the patient and / or therapist (e.g., via an application, via a web interface). The DGC 600 can monitor who has been recommended what game and why.

[0157] In some embodiments, the DGC 600 may make direct recommendations (e.g., “Hey, you look like the kind of person who should play game X”). The DGC 600 may recommend channels that play game X (e.g., “By the way, here are really great places for you to play game X”). The DGC 600 may prompt for feedback (e.g., “Hey, you played game X. How are you feeling now?”). The DGC 600 may prompt for a self-assessment (e.g., “Hey, did you have fun? How did you feel about it?”). For example, the responses may be stored in a structure associated with the game, user, and / or disorder. The game selection module 715 may update recommendations to the user and / or other users based on the feedback. Accordingly, by way of example and not limitation, the recommendations may advantageously become more therapeutic and / or make an already performed user action (e.g., playing a game they like) more therapeutic.

[0158] In some embodiments, for example, DGC 600 can generate promising suggestions (e.g., “Did you know that within three weeks of these feelings, in similar scenarios, you said we felt better?”). For example, DGC 600 can associate promising suggestions with suggested actions (e.g., “By the way, this is what you do when you feel this way, and you start feeling better after doing it”). DGC 600 can implement non-pressure suggestions (e.g., “You can get ready at the beginning. Remember, they are games and they are fun! You have fun playing them. Here is one of your favorites. Remember that game you really liked? Why don’t you try it for 20 minutes?”)

[0159] In some embodiments, DIPGS100 may not be associated with the source code of the game. For example, DIPGS100 may provide a code and / or a link (e.g., through a visual marker such as a logo, icon, etc.). The activation code and / or link may direct the patient to a selected game programmed by DIPGS100. For example, the patient may own the game and / or purchase the game from a third party (e.g., a gaming platform).

[0160] In various embodiments, a game (e.g., wild game 150, DTx game 605) may be provided on one or more platforms. For example, a game may be provided through a third-party platform. The selection engine may indicate to the user one or more platforms that may be used to access the game. The selection engine may generate an identifier associated with the user and / or the recommendation. When the user accesses the game, the monitoring engine may associate the identifier with the user and / or the recommendation. The monitoring engine may determine attributes associated with game play based on input received from an engine associated with the game (e.g., a third-party game engine) and / or user input. For example, but not limited to, the attributes may include a game start time, a game duration, a game end time, or a combination thereof.

[0161] The monitoring engine can interact with the user before, during, and / or after the game. For example, the monitoring engine can provide warnings, alerts, and / or regulatory information to the user at the start of the game. In some examples, the monitoring engine can provide the user with guidance for playing the game (e.g., the start of the game play). The monitoring engine can, for example, collect feedback from the user. For example, the monitoring engine can prompt the user to feedback their experience, feelings, current status, noticed improvements, or a combination thereof. The monitoring engine can, for example, provide feedback to the selection engine. Accordingly, the selection engine can dynamically update suggestions and / or metadata related to the game based on feedback received from the user and / or others.

[0162] DGC600 can suggest games to be played at therapeutically relevant intervals. DGC600 can ask (e.g., via application prompts) players to think and / or do things while playing games. DGC600 can check (e.g., via prompts) to monitor whether the user follows the suggestions. Accordingly, DGC600 can advantageously cause a change in the user's outlook. For example, DGC600 and processes can produce a healing effect.

[0163] For example, such an embodiment can advantageously integrate one or more levels of games with the game to (selectively) apply the game to induce a positive therapeutic effect. For example, the system (e.g., through the application of user input, through an API associated with the system and the game) can receive feedback when the patient plays the game and for how long. For example, the system can retrieve a list of games that have been integrated with the system. In some embodiments, one or more games can be hosted and / or accessed through a platform associated with the system. For example, a user can access at least some games through the local environment of the game (e.g., Microsoft Playstation, PlayStation, Wii). For example, the game may not be required to be hosted on a platform provided by the system for treatment selection, delivery, and / or monitoring. For example, these implementations can provide little or no integration burden for game developers. Accordingly, various such embodiments can advantageously provide extended access for patients.

[0164] In various embodiments, the assessment engine 125 can retrieve, generate, and / or store information about the user's personality based on a profile (e.g., performed during setup, performed periodically, provided by a therapist). For example, the assessment engine 125 can guide the patient to use a game that best suits their medical problem. For example, the assessment engine 125 can record data related to usage so that, for example, the patient can control the application themselves. In some embodiments, a third party (e.g., a medical practitioner, a doctor) can provide input for the selection of guidance for the game.

[0165] In various embodiments, information about recommendations, feedback, responses, engagement, duration of play, or some combination thereof can be recorded in a data structure (e.g., patient-related, disease-related, game-related). For example, the information can be analyzed for diagnosis and improved treatment (e.g., using an artificial intelligence model such as a neural network).

[0166] Although an exemplary system has been described in conjunction with FIG. ***, other industrial, scientific, medical, commercial, and / or residential applications may deploy other implementations.

[0167] In some embodiments, regulatory requirements may include an explicit statement that a patient should contact a physician before using the device, even if the device is marketed directly to consumers. Regulatory requirements may include labeling, including user instructions, that provides information about how to obtain additional resources related to the treatment of mental illness, such as references to recommendations made to the public by medical professional organizations or the American Psychological Association or other associations. Regulatory requirements may include a clear description of the indications for the device, including the mental condition / disorder that the device is intended to treat, and a description of the expected patient population (type of symptoms, duration, severity, and age range (adults vs. children / adolescents), expected effectiveness, etc.).

[0168] For example, regulatory requirements may include a description of the treatment method (e.g., cognitive behavioral psychotherapy, etc.). For example, regulatory requirements may include a clear description of the recommended duration and frequency of use. For example, regulatory requirements may include instructions for use, including images demonstrating how to interact with the device. For example, regulatory requirements may include a summary of the clinical testing of the device. For example, regulatory requirements may include a description of the method used to determine any treatment recommendations. For example, regulatory requirements may include prominent notices to patients and healthcare providers (if applicable) that the recommendations provided by the device are auxiliary (supportive) and should not be relied upon solely or primarily to treat mental illness. For example, regulatory requirements may include a warning that the device is not intended to replace the patient's medication. For example, regulatory requirements may include a statement regarding whether a prescription for the device is available. For example, regulatory requirements may include instructions regarding when (under what circumstances, how often) the user should consult a healthcare provider. For example, regulatory requirements may include clear instructions on what to do if symptoms do not improve and within the expected time period. For example, regulatory requirements may include instructions on what to do in a medical emergency. For example, regulatory requirements may include clear identification of any device indications / functions that are not approved by the FDA.

[0169] In some embodiments, by way of example and not limitation, various systems (e.g., DIMP generation, delivery, and / or monitoring systems) may be used to manage inductions, excluding the actual performance of treatment. For example, DIPGS (e.g., as disclosed herein) may manage induction delivery, induction monitoring, and / or peripheral induction monitoring (e.g., determining when to trigger an induction, determining how to modify an induction, determining when to terminate an induction). By way of example and not limitation, DIPGS may not actually provide treatment. For example, a separate treatment delivery module may provide treatment. DIPGS may, for example, generate an induction package. For example, DIPGS may deliver an induction. For example, DIPGS may release responsibility for a treatment module and / or person. For example, DIPGS may receive treatment results. For example, DIPGS may generate an updated induction package (e.g., DIMP) based on the results of the treatment and / or induction.

[0170] MMPGE (e.g., as described herein) can, for example, package inductions and treatments. In some embodiments, by way of example and not limitation, for example, MMPGE can perform no treatment operations. For example, MMPGE can generate packaged medical media and non-medical inducements (e.g., non-medical media) and provide a final media package for delivery. In some embodiments, by way of example and not limitation, MMPGE can, for example, monitor delivery. In some embodiments, MMPGE can receive the results of treatment delivery from a separate module (e.g., treatment module, DIPGS). For example, in some embodiments, DIPGS and / or MMPGE can dynamically create and / or adjust media packages (e.g., DIMPs) based on the results of treatment and / or induction without providing treatment and / or performing treatment.

[0171] A computer program product may include a set of instructions which, when executed by a processor device, cause the processor to perform specified functions. These functions may be performed in conjunction with a controlled device in operable communication with the processor. A computer program product may include software, which may be stored in a storage medium, such as a data memory on an electronic, magnetic or rotating storage device, which may be fixed or removable (e.g., hard disk, floppy disk, thumb drive, CD, DVD).

[0172] Although an example of a system has been described in conjunction with the above figures, which system may be portable, other implementations may be deployed in other processing applications, such as desktop and network environments.

[0173] For example, temporary auxiliary energy input can be received from a rechargeable or disposable battery, which can be enabled in portable or remote applications. Some embodiments can work with other DC voltage sources such as a 9V battery. An alternating current (AC) input can be received through a rectifier and appropriate scaling, and the AC input can be provided, for example, from a 50 / 60Hz power port or from a portable generator. Providing an AC (e.g., sine wave, square wave, triangle wave) input can include a line frequency converter to provide voltage step-up, voltage step-down, and / or isolation.

[0174] Although specific features of the architecture have been described, other features may be combined to improve performance. For example, caches (e.g., L1, L2, ...) may use techniques. Random access memory may be included, for example, to provide scraper memory and / or load stored executable code or parameter information for use during runtime operations. Other hardware and software may be provided to perform operations, such as network or other communications using one or more protocols, wireless (e.g., infrared) communications, stored operating energy and power (e.g., batteries), switching and / or linear power supply circuits, software maintenance (e.g., self-tests, upgrades), etc. One or more communication interfaces may be provided to support data storage and related operations.

[0175] Some systems may be implemented as computer systems that can be used in various implementations. For example, various implementations may include digital circuits, analog circuits, computer hardware, firmware, software, or a combination thereof. The apparatus may be implemented in a computer program product that may be embodied in an information carrier, such as in a machine-readable storage device, for execution by a programmable processor; the method may be executed by a programmable processor to execute a program of instructions to perform the functions of various embodiments by operating on input data and generating output. Various embodiments may be advantageously implemented in one or more computer programs executable on a programmable system, the one or more computer programs including at least one programmable processor connected to receive data and instructions from a data storage system, at least one input device, and / or at least one output device and transmitting data and instructions to the data storage system, at least one input device, and / or at least one output device. A computer program is a set of instructions that can directly or indirectly perform an activity or produce a result in a computer. A computer program may be written in any form of programming language, including compiled or interpreted languages, and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0176] Processors suitable for executing a program of instructions include, for example, general and special purpose microprocessors, which may include a single processor or one of multiple processors of any type of computer. Typically, the processor will receive instructions and data from a read-only memory or a random access memory or both. The basic elements of a computer are a processor for executing instructions and one or more memories for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data files, or be operatively communicating with one or more mass storage devices; these devices include magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and optical disks. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory, for example, including semiconductor memory devices, such as EPROM, EEPROM and flash memory devices; magnetic disks, such as internal hard disks, removable disks, etc.; magneto-optical disks; CD-ROM and DVD-ROM disks. The processor and memory may be supplemented or incorporated by an ASIC (Application Specific Integrated Circuit).

[0177] In some embodiments, each system can be programmed with the same or similar information and / or initialized with substantially the same information stored in volatile and / or non-volatile memory. For example, the data interface can be used to perform auto-configuration, auto-download, and / or auto-update functions when connected to an appropriate host device, such as a desktop computer or server.

[0178] In some embodiments, one or more user interface features can be customized to perform specific functions. Various embodiments can be implemented in a computer system including a graphical user interface and / or an Internet browser. In order to provide interaction with a user, some implementations can be implemented on a computer with a rendering device. The rendering device can, for example, include an LED (light emitting diode) display. In some embodiments, the rendering device can, for example, include a CRT (cathode ray tube). In some embodiments, the rendering device can, for example, include an LCD (liquid crystal display). A rendering device (e.g., a monitor) can be used, for example, to present information to a user. For example, some implementations can include a keyboard and / or a pointing device (e.g., a mouse, a trackpad, a trackball, a joystick), and for example, a user can provide input to the computer via a keyboard and / or a pointing device.

[0179] In various implementations, the system can communicate using suitable communication methods, devices, and techniques. For example, the system can communicate with compatible devices (e.g., devices capable of transmitting data to and / or from the system) using point-to-point communications, wherein messages are transmitted directly from the source to the receiver via a dedicated physical link (e.g., a fiber optic link, point-to-point wiring, a daisy chain). The components of the system can exchange information via any form or medium of analog or digital data communication, including messages based on data encapsulation in a communication network. Examples of communication networks include, for example, a LAN (local area network), a WAN (wide area network); a metropolitan area network, a wireless and / or optical network, computers and networks that constitute the Internet, or a combination thereof. Other embodiments can transmit messages by broadcasting to all or substantially all devices connected together by the communication network, for example, via an omnidirectional radio frequency (RF) signal. Yet another implementation can transmit messages with high directivity, such as RF signals transmitted using a directional (i.e., narrow beam) antenna or an infrared signal optionally used with focusing optics. Other implementations may also be made using appropriate interfaces and protocols, such as, for example, USB 2.0, Firewire, ATA / IDE, RS-232, RS-422, RS-485, 802.11a / b / g, Wi-Fi, Ethernet, IrDA, FDDI (Fiber Distributed Data Interface), Token Ring networks, multiplexing techniques based on frequency. Time, code division, or some combination thereof. Some implementations may optionally include error checking and correction (ECC) for data integrity or security measures, such as encryption (e.g., WEP) and password protection, among other features.

[0180] In various embodiments, a computer system may include an Internet of Things (IoT) device. An IoT device may include objects embedded with electronics, software, sensors, actuators, and network connectivity that are capable of collecting and exchanging data. IoT devices may be used with wired or wireless devices by sending data to other devices through an interface. IoT devices may collect useful data and then autonomously flow the data between other devices.

[0181] Various examples of modules can be implemented by circuits, including various electronic hardware. As an example and not limitation, hardware can include transistors, resistors, capacitors, switches, integrated circuits, other modules, or combinations thereof. In various examples, modules can include analog logic, digital logic, discrete components, traces, and / or memory circuits manufactured on a silicon substrate, which includes various integrated circuits (e.g., FPGAs, ASICs) or some combination thereof. In some embodiments, modules can include software that executes pre-programmed instructions, processors, or some combination thereof. For example, various modules can include both hardware and software.

[0182] In illustrative aspects, a dynamic induction package generation system (DIPGS) (e.g., 100), for example, can include a data store. For example, the data store can include a validated digital therapeutic (e.g., 155), a treatment profile associated with one of the validated therapies (e.g., 280), a user profile associated with a user (e.g., 140), and a media profile (e.g., 145) associated with a wild video game (e.g., 150).

[0183] For example, the DIPGS may include an assessment engine (eg, 125) coupled to a data store and configured to generate a user profile based on a log of user input (eg, 255).

[0184] For example, the DIPGS may include a medical media package generation engine (e.g., 130) coupled to a data storage device, wherein the medical media package generation engine may be used, for example, to generate a dynamic induction media package (DIMP). For example, the DIMP may include one or more of a validated digital therapeutic based on a user profile, a treatment profile, and a media profile associated with a user-selected wild video game. For example, the DIMP may include state transition criteria generated based on the user profile and the validated digital therapeutics in the DIMP, wherein when the state transition criteria are met, the operating state of the DIMP may be, for example, transitioned from an induction mode to a treatment mode.

[0185] For example, the DIMP can be configured to run in a user device (e.g., 106), which is remotely connected to the dynamic induction package generation system. During the runtime of the DIMP, in the induction mode, a wild video game selected by the user can be played on a timed basis, for example. When the runtime conditions meet the state transition criteria, the DIMP can, for example, be transformed from the induction mode to the treatment mode, and the medical media package generation engine can, for example, generate a therapeutic immersion media package (TIMP). For example, the TIMP can include a verified set of media content recommendations based on a verified digital therapy treatment profile and a user profile. For example, a verified set of media content recommendations can be presented in a treatment interface of a user device.

[0186] In treatment mode, the medical media package generation engine can, for example, generate intervention monitoring content (IMC). The IMC can, for example, include a TIMP so that the DIMP switches from running a wild video game selected by the user to a validated digital therapeutic. When a response to the IMC is received, the evaluation engine can, for example, update the user profile based on the received response, thereby continuously and automatically providing medical guidance and progress monitors to the user.

[0187] For example, the verified media content may include a set of questions.

[0188] The DIPGS may also include, for example, a dynamic induction encapsulation state machine (e.g., DIPSM) for, during runtime of the DIMP, (a) identifying at least one transition point in the DIMP, (b) transitioning the runtime of the DIMP from an induction mode to a treatment mode, (c) presenting the TIMP on a user device, and (d) sending a signal to an assessment engine to update a user profile based on results of the TIMP.

[0189] For example, DIPSM may also be used to adjust a predetermined set of run-time parameters of the DIMP based on the TIMP and the treatment profile of the validated media content in the TIMP as well as the user profile.

[0190] For example, switching from running a user-selected wild video game to a validated digital therapeutic may include inserting instructions within the wild video game.

[0191] For example, switching from running a user-selected wild video game to a validated digital therapeutic may include interrupting the runtime of the DIMP during play of the wild video game.

[0192] DIPGS may also include, for example, an observation layer. For example, the observation layer may be used to observe the user's behavior of collecting health indicator information and to request a response from the user based on the collected information.

[0193] When the presentation of the DIMP may not be appropriate, for example, the medical media package generation engine can be used to generate a condensed DIMP. For example, the DIMP can include a TIMP based on the user profile and the history of playing the DIMP.

[0194] The TIMP may include, for example, instructions and warnings for the user. For example, the instructions and warnings may be presented based on state transition criteria. For example, the instructions and warnings may include instructions for inducing autonomous functions using the voluntary actions required to play the TIMP.

[0195] For example, the DIPGS may also include an adjustment module. For example, the adjustment module may be used to update the treatment profile of the changed digital therapy based on a predetermined set of verification rules after receiving a change to one of the verified digital therapies, for example, so that the changed digital therapy can be verified as suitable for treatment intent. In illustrative terms, a dynamic induction package generation system (DIPGS) (e.g., 100) may, for example, include a data storage. For example, the data storage may include a verified digital therapy (e.g., 155), a user profile associated with a user (e.g., 140), and a media profile associated with wild media content (e.g., 145). For example, the DIPGS may include an evaluation engine (e.g., 125) connected to the data storage, and used to generate a user profile based on a log (e.g., 255) of user input. For example, the DIPGS may include a medical media package generation engine (e.g., 130) connected to the data storage, wherein the medical media package generation engine may, for example, be used to generate a dynamic induction media package (e.g., DIMP) based on the user profile, and a media profile associated with the wild media content selected by the user.

[0196] The DIMP may, for example, include state transition criteria, and the DIMP may, for example, be configured to run in a user device remotely connected to a dynamic induction package generation system, such that during the runtime of the DIMP, the DIMP runs in an induction mode and / or a treatment mode.

[0197] In the induction mode, the wild media content selected by the user can be played at a fixed time, for example. When the runtime condition meets the state transition criteria, for example, the DIMP can be converted from the induction mode to the treatment mode. In the treatment mode, the medical media package generation engine generates intervention monitoring content (e.g., IMC). For example, the IMC can include at least one of a plurality of verified digital therapies, so that the DIMP switches from running the wild media content selected by the user to the verified digital therapy. When receiving the response of the IMC, the evaluation engine can, for example, update the user profile according to the received response, thereby continuously and automatically providing medical guidance and progress monitors to the user. For example, the medical media package generation engine can be used to dynamically generate state transition criteria based on the user profile and the verified digital therapy in the DIMP, identify at least one transition point in the DIMP, wherein at each of the transition points, the runtime of the DIMP is converted from the induction mode to the treatment mode, and generate a treatment immersive media package (e.g., TIMP). For example, the TIMP can include a verified media content recommendation set at each identified transition point based on the treatment profile and user profile of the verified digital therapy. For example, the verified media content recommendation set can be configured to be (e.g., automatically) presented on the treatment interface of the user device.

[0198] For example, the verified media content may include a set of questions.

[0199] For example, the DIPGS may also include a dynamic induction encapsulation state machine (e.g., DIPSM) that, during runtime of the DIMP, (a) identifies a transition point in at least one DIMP, (b) transitions the runtime of the DIMP from an induction mode to a treatment mode, (c) presents the TIMP on a user device, and (d) transmits a signal to an assessment engine to update a user profile based on the results of the TIMP.

[0200] For example, DIPSM may also be used to adjust a predetermined set of run-time parameters of the DIMP based on the TIMP and the treatment profile of the validated media content in the TIMP as well as the user profile.

[0201] For example, switching from running user-selected wild media content to a validated digital therapeutic could include inserting instructions within the wild media content.

[0202] For example, switching from running user-selected wild media content to a validated digital therapeutic may include interrupting the runtime of the DIMP during playback of the wild media content.

[0203] DIPGS may also include, for example, an observation layer, which may be used to observe the user's behavior of collecting health indicator information and to respond to the user's request based on the collected information.

[0204] The DIPGS can be configured such that when the presentation of the DIMP may, for example, be inappropriate (e.g., based on one or more predetermined suitability criteria, based on user discretion and / or input), the medical media package generation engine can be configured to generate a condensed DIMP. The condensed DIMP can, for example, include a TIMP based on a user profile and a history of played DIMPs.

[0205] For example, the TIMP may include instructions and warnings for the user, wherein the instructions and warnings are determined to be presented based on the state transition criteria. For example, the instructions and warnings may include instructions to induce autonomous functions using the voluntary actions required to play the TIMP.

[0206] For example, DIPGS may also include an adjustment module, wherein the adjustment module may, for example, be used to update the treatment profile of the changed digital therapy based on a predetermined set of verification rules when a change to one of the verified digital therapeutics is received, so that the changed digital therapy may, for example, be verified as suitable for the treatment intent.

[0207] The system for generating a dynamic induction package according to claim 12, characterized in that the wild media content may include, for example, a video game. In an illustrative aspect, a computer-implemented method may be executed by at least one processor to automatically provide a dynamically generated immersive healing mechanism based on a monitoring and tracking mechanism in an unregulated media content environment. For example, the method may include receiving a signal corresponding to a user request to play wild media content (e.g., 1005). For example, the method may include dynamically generating a set of transitions. Based on the criteria of the user profile and the treatment profile of the requested media content (e.g., 1020). For example, the method may include observing the behavior of the user during the runtime of the media content (e.g., 1030). The method may include, for example, when the set of transition criteria is met, transferring the runtime of the media content from an induction mode to a treatment mode (e.g., 1035). For example, the method may include dynamically generating verified treatment content in a treatment mode, including questions and instructions generated based on a user profile (e.g., 1040). For example, the method may include evaluating the progress of the user (e.g., 1045) based on the responses received from the verified treatment content and the observed behavior of the user. For example, the method may include generating an intervention if the user's progress is below an intervention threshold (eg, 1065) such that medical guidance and progress monitoring of the treatment process is continuously provided.

[0208] In illustrative aspects, for example, a computer program product (e.g., CPP) may include a program of instructions tangibly embodied on a non-transitory computer-readable medium, wherein when the instructions are executed on a processor, the processor causes a dynamically induced media package generation and presentation mode to operate to automatically provide a dynamically generated immersive healing mechanism based on a monitoring and tracking mechanism in an unregulated media content environment. For example, the operation may include receiving a signal corresponding to a user request to play wild media content (e.g., 1005). For example, the operation may include dynamically generating a set of transition criteria based on a user profile and a treatment profile of the requested media content (e.g., 1020). For example, the operation may include observing the behavior of a user during the runtime of the media content (e.g., 1030). The operation may include, for example, transferring the runtime of the media content from an induced mode to a treatment mode (e.g., 1035) when the set of transition criteria is met. For example, the operation may include dynamically generating verified treatment content in a treatment mode, including questions and guidance generated based on a user profile (e.g., 1040). Operations may include, for example, evaluating the user's progress based on responses received from validated treatment content and observed user behavior (e.g., 1045). For example, operations may include: if the user's progress, for example, may be below an intervention threshold (e.g., 1065), thereby continuing to provide medical guidance and progress monitoring of the treatment process, then intervening.

[0209] A variety of implementations have been described. However, it should be understood that various modifications may be made. For example, advantageous results may be achieved if the steps of the disclosed techniques are performed in a different order, or if the components of the disclosed systems are combined in a different manner, or if additional components are added. Accordingly, other implementations are contemplated within the scope of the following claims.

Claims

1. A dynamic induction package generation system (100), characterized in that: The system (100) comprises: a data store comprising a plurality of verified digital therapeutics (155), a plurality of treatment profiles (280) each associated with one of the verified therapies, a user profile (140) associated with a user, and a plurality of media profiles (145) associated with a plurality of wild electronic games (150); an assessment engine (125) coupled to the data store and configured to generate the user profile based on a log (255) of user input; and A medical media package generation engine (130) coupled to the data store, wherein the medical media package generation engine is configured to generate a dynamically induced media package (DIMP) comprising: one or more of the plurality of validated digital therapeutics based on the user profile, the plurality of treatment profiles, and the media profile associated with the user-selected wildlife video game, state transition criteria generated according to the user profile and the validated digital therapeutic in the DIMP, wherein when the state transition criteria are met, the operating state of the DIMP is transitioned from an induction mode to a treatment mode, and wherein: The DIMP is configured to run in a user device (106) remotely connected to the dynamic induction package generation system, and wherein, during the runtime of the DIMP, In the induction mode, the wild electronic game selected by the user is played regularly, When a runtime condition satisfies the state transition criteria, the DIMP transitions from the induction mode to the treatment mode, the medical media package generation engine generates an immersive treatment media package (TIMP), the TIMP comprising a treatment profile based on the validated digital therapeutic and a validated set of media content recommendations for the user profile, wherein the validated set of media content recommendations is presented on a treatment interface of the user device, In the treatment mode, the medical media package generation engine generates intervention monitoring content (IMC) including the TIMP so that the DIMP switches from running the user-selected wild video game to the validated digital therapeutic, and Upon receiving a response from the IMC, the assessment engine updates the user profile based on the received response in order to continuously and automatically provide medical guidance and progress monitoring to the user.

2. The dynamic induction package generation system according to claim 1, characterized in that: The authenticated media content includes a set of questions.

3. The dynamic induction package generation system according to claim 1, characterized in that: Also included is a dynamically induced package state machine (DIPSM), the DIPSM being configured to, during the DIMP runtime (a) identifying at least one transition point in said DIMP, (b) switching the operating time of the DIMP from the induction mode to the treatment mode, (c) presenting the TEMP on the user equipment, and (d) sending a signal to the assessment engine to update the user profile based on the results of the TEMP.

4. The dynamic induction package generation system according to claim 3, characterized in that: The DIPSM is further configured to adjust a predetermined set of runtime parameters of the DIMP based on the TEMP and the therapy profile and the user profile of the validated media content in the TEMP.

5. The dynamic induction package generation system according to claim 1, characterized in that: Switching from running the user-selected wild electronic game to the validated digital therapeutic includes inserting instructions into the wild electronic game.

6. The dynamic induction package generation system according to claim 1, characterized in that: Switching from running the user-selected wild electronic game to the validated digital therapeutic includes interrupting the running time of the DIMP during play of the wild electronic game.

7. The dynamic induction package generation system according to claim 1, characterized in that: Also included is an observation layer, wherein the observation layer is configured to observe the user's behavior to collect health indicator information, and Based on the collected information, a response is solicited from the user.

8. The dynamic induction package generation system according to claim 1, characterized in that: The medical media package generation engine is configured to generate a simplified DIMP including the TIMP based on the user profile and the history of played DIMPs when the presentation of the DIMP is not appropriate.

9. The dynamic induction package generation system according to claim 2, characterized in that: The TIMP includes instructions and warnings for the user, wherein the instructions and warnings are determined to be presented based on the state transition criteria.

10. The dynamic induction package generation system according to claim 9, characterized in that: The guidance and warnings include instructions to induce autonomic function using voluntary actions required when playing the DIMP.

11. The dynamic induction package generation system according to claim 3, characterized in that: It also includes a regulatory module, which: The administration module is configured to, upon receiving a change to one of the validated digital therapeutics, update the treatment profile of the modified digital therapeutic based on a predetermined set of validation rules, thereby validating that the modified digital therapeutic complies with the treatment intent.

12. A dynamic induction package generation system (100), characterized in that: include: a data store comprising a plurality of validated digital therapeutics (155), a user profile (140) associated with a user, and a plurality of media profiles (145) associated with a plurality of wild media content; an assessment engine (125) connected to the data store, and the assessment engine (125) is configured to generate the user profile based on the log (255) of user input; as well as, a medical media package generation engine (130) coupled to the data store, wherein the medical media package generation engine is configured to generate a dynamically induced media package (DIMP) based on the user profile and a media profile associated with user-selected wild media content, wherein: The DIMP includes a state transition criterion, and the DIMP is configured to run in a user device remotely connected to the dynamic induction package generation system, and wherein, at the running time of the DIMP, In the induction mode, the wild media content selected by the user is played regularly, When the runtime conditions satisfy the state transition criteria, the DIMP switches from the induction mode to the treatment mode, in the treatment mode, the medical media package generation engine generates intervention monitoring content (IMC) including at least one of the plurality of validated digital therapeutics so that the DIMP switches from running the user-selected wild media content to the validated digital therapeutic, and, Upon receiving a response from the IMC, the assessment engine updates the user profile based on the received response to provide medical guidance and progress monitoring to the user on an ongoing and automatic basis.

13. The dynamic induction package generation system according to claim 12, characterized in that: The medical media package generation engine is configured to dynamically generate the state transition criteria based on the user profile and the validated digital therapeutics in the DIMP, At least one transition point is identified in the DIMP, wherein at each of the transition points, the runtime of the DIMP is switched from the induction mode to the treatment mode, and, based on the treatment profile of the validated digital therapeutic and the user profile, an immersive therapeutic media package (TIMP) including the validated set of media content recommendations is generated at each determined transition point, wherein the validated set of media content recommendations is presented on a treatment interface of the user device.

14. The dynamic induction package generation system according to claim 13, characterized in that: The authenticated media content includes a set of questions.

15. The dynamic induction package generation system according to claim 13, characterized in that: Also included is a dynamically induced packing state machine (DIPSM), the state machine being configured to, during the DIMP runtime, (a) identifying at least one transition point in the DIMP, (b) switching the operation time of the DIMP from the induction mode to the treatment mode, (c) presenting the TIMP on the user equipment, and (d) sending a signal to the assessment engine to update the user profile based on the results of the TIMP.

16. The dynamic induction package generation system according to claim 15, characterized in that: The DIPSM is further configured to adjust a predetermined set of runtime parameters of the DIMP based on the TIMP and the therapy profile and the user profile of the validated media content in the TIMP.

17. The dynamic induction package generation system according to claim 12, characterized in that: Switching from running the user-selected wild media content to the verified digital therapeutic includes inserting instructions into the wild media content.

18. The dynamic induction package generation system according to claim 12, characterized in that: Switching from running the user-selected wild media content to the validated digital therapeutic includes interrupting the running time of the DIMP during playing of the wild media content.

19. The dynamic induction package generation system according to claim 12, characterized in that: Also included is an observation layer, wherein the observation layer is configured to observe the user's behavior to collect health indicator information, and Based on the collected information, a response is solicited from the user.

20. The dynamic induction package generation system according to claim 13, characterized in that: The medical media package generation engine is configured to generate a simplified DIMP including the TIMP based on the user profile and the history of played DIMPs when the presentation of the DIMP is not appropriate.

21. The dynamic induction package generation system according to claim 13, characterized in that: The TEMP includes instructions and warnings for the user, wherein the instructions and warnings are determined to be presented based on the state transition criteria.

22. The dynamic induction package generation system according to claim 21, characterized in that: The guidance and warnings include instructions to induce autonomic function using voluntary actions required when playing the DIMP.

23. The dynamic induction package generation system according to claim 14, characterized in that: It also includes a regulatory module, which: The administration module is configured to, upon receiving a change to one of the validated digital therapeutics, update the treatment profile of the modified digital therapeutic based on a predetermined set of validation rules, thereby validating that the modified digital therapeutic complies with the treatment intent.

24. The dynamic induction package generation system according to claim 12, characterized in that: The wild media content includes electronic games.

25. A computer-implemented method executed by at least one processor for automatically providing a dynamically generated immersive therapy mechanism based on a monitoring and tracking mechanism in an unregulated media content environment, characterized in that, The method comprises: Receiving a signal corresponding to a user request to play wild media content (1005); dynamically generating a set of conversion criteria based on the user profile and the treatment profile of the requested media content (1020); observing user behavior during runtime of the media content (1030); converting the runtime of the media content from an induction mode to a treatment mode when the set of transition criteria is met (1035); In the treatment mode, dynamically generating validated treatment content including questions and instructions generated based on the user profile (1040); evaluating the user's progress based on responses received from the validated therapeutic content and observed user behavior (1045); and, An intervention is generated (1065) if the user's progress is below an intervention threshold to continue providing medical guidance and progress monitoring of the treatment process.

26. A computer program product (CPP), characterized in that The CPP includes a program of instructions embodied on a non-transitory computer readable medium, wherein when the instructions are executed on a processor, the processor causes dynamically induced media package generation and presentation operations to automatically provide a dynamically generated immersive therapy mechanism based on a monitoring and tracking mechanism in an unregulated media content environment, the operations comprising: Receiving a signal corresponding to a user request to play wild media content (1005); dynamically generating a set of conversion criteria based on the user profile and the treatment profile of the requested media content (1020); observing user behavior during runtime of the media content (1030); converting the runtime of the media content from an induction mode to a treatment mode when the set of transition criteria is met (1035); In the treatment mode, dynamically generating validated treatment content including questions and instructions generated based on the user profile (1040); evaluating the user's progress based on responses received from the validated therapeutic content and observed user behavior (1045); and, An intervention is generated (1065) if the user's progress is below an intervention threshold to continue providing medical guidance and progress monitoring of the treatment process.

Images