METHOD, DEVICE AND SYSTEM FOR TREATMENT OF ADHD

Abstract

A system used by a child diagnosed with ADHD and including a wearable device equipped with motion sensors and optionally a location or GPS tracker as a safety feature and using cloud based technology to facilitate the transfer of information among users. Motion data is used for two main purposes: 1) to objectively measure hyperactivity levels on specific metrics and optionally to detect presence or absence of aggression; and 2) to track the child's sleep-wake patterns (given a high percentage of children with ADHD are known to have sleep disorders). Behavior feedback is provided in real time based on the data obtained. Additional sensors may also be used to aid the assessment of child's behavioral functioning and sleep-wake patterns.

Claims

1. A method for the treatment of ADHD, comprising the steps of: providing a wearable device, said wearable device being connectable to an electronic device having an app thereon; defining a plurality of desired behaviors within the app, said behaviors including a plurality of motion based behaviors; defining and creating a plurality of input routines within said app; defining and creating pre-set parameters for generation and presentation of rewards on the wearable device; collecting motion data and/or location data via sensors in the wearable device; analyzing the motion data in the electronic device by an algorithm, comprising the steps of: determining a baseline compliance with the behaviors based on the analyzed motion data; determining deviations from the baseline compliance with the behaviors and routines; comparing the deviations to said pre-set parameters; and presenting a reward based on a positive determination of the deviations.

2. The method of claim 1, further comprising the step of: assigning different levels of deviation required for presentation of the reward.

3. The method of claim 1, further comprising the step of: transmitting the analyzed motion data to a predetermined group of treatment providers.

4. The method of claim 3, wherein the group of treatment providers are selected from the group consisting of: parents, therapists, prescribers, teachers and insurance providers.

5. The method of claim 1, further comprising the step of: reviewing the analyzed motion data over time to determine a compliance level with the input routine and the desired behaviors.

6. The method of claim 5, further comprising: adapting the pre-set parameters based on the review.

7. The method of claim 1, wherein the wearable device includes a display screen to display a pre-selected avatar.

8. The method of claim 7, wherein an appearance of the avatar changes based on the deviations.

9. The method of claim 7, wherein a parent/caregiver views the analysis of motion data in real time and interactively present additional rewards for display on the display screen.

10. A system for the treatment of ADHD, comprising: a wearable device, the wearable device being connectable to an electronic device having an app thereon; the app containing a plurality of desired behaviors including a plurality of motion based behaviors, a plurality of input routines, and pre-set parameters for generation and presentation of rewards on the wearable device; wherein the app collects motion data and/or location data via sensors in the wearable device and analyzes the motion data in the electronic device by an algorithm, comprising the steps of: determining a baseline compliance with the behaviors based on the analyzed motion data; determining deviations from the baseline compliance with said behaviors and routines; comparing said deviations to the pre-set parameters; and a display on the wearable device for presenting a reward based on a positive determination of the deviations.

11. The system of claim 10, further comprising: the app assigning different levels of deviation required for presentation of the reward.

12. The system of claim 10, further comprising: the electronic device transmitting the analyzed motion data to a predetermined group of treatment providers.

13. The system of claim 12, wherein the group of treatment providers are selected from the group consisting of: parents, therapists, prescribers, teachers and insurance providers.

14. The system of claim 10, wherein analyzed motion data is reviewed over time to determine a compliance level with the input routine and said desired behaviors.

15. The system of claim 14, wherein the pre-set parameters are adapted based on said review.

16. The system of claim 10, wherein the display screen displays a pre-selected avatar.

17. The system of claim 16, wherein an appearance of the avatar changes based on the deviations.

18. The system of claim 10, wherein a parent/caregiver views the analysis of motion data in real time and interactively present additional rewards for display on the display screen.

19. The system of claim 10, wherein a provider (therapist or prescriber) views the analysis of motion data and communicates adjustments in treatment to the parent/caregiver.

Description

BRIEF DESCRIPTION OF THE DRAWING FIGURES

[0046] The novel features that are characteristic of the present disclosure are set forth in the appended claims. However, the preferred embodiments, together with further objects and attendant advantages, will be best understood by reference to the following detailed description taken in connection with the accompanying Figures in which:

[0047] FIG. 1 shows an exemplary home token economy program;

[0048] FIG. 2 shows an exemplary Daily Report Card;

[0049] FIG. 3 shows an exemplary weekly schedule chart as typically maintained for ADHD treatment;

[0050] FIG. 4 illustrates the flow of operation of the present disclosure;

[0051] FIG. 5 illustrates parent/service provider device interactivity of the present disclosure;

[0052] FIG. 6 shows the solution system loop to illustrate how therapists, prescribers and insurance companies utilize the platform to identify, through data analytics, optimized treatment protocols and aid in their population health management;

[0053] FIG. 7 is a tiled diagram of the features and interactions of the features of the present disclosure;

[0054] FIG. 8 is a schematic diagram illustrating the method and system of the present disclosure;

[0055] FIG. 9 shows parent child interaction using the method and system of the present disclosure;

[0056] FIG. 10 shows the operation of the device, method and system, as well as the child, in a school setting;

[0057] FIG. 11 illustrates the use of an Avatar in the device, method and system of the present disclosure;

[0058] FIG. 12 illustrates the reward component of the device, method and system of the present disclosure;

[0059] FIG. 13 illustrates the interaction of treatment professionals with the parent using the device, method and system of the present disclosure; and

[0060] FIG. 14 illustrates the interaction of the parent with the child using the device, method and system of the present disclosure.

DETAILED DESCRIPTION OF THE DISCLOSURE

[0061] The method, device and system of the present disclosure is shown in detail in the attached drawings figures and the detailed discussion below.

[0062] The present disclosure provides a system including a wearable device and using cloud based technology to facilitate the transfer of information allowing parents, therapists and prescribers to track, interpret and implement accurate treatment solutions in real time. The system will be used by a child diagnosed with ADHD. The wearable device in the preferred embodiment is equipped with at least motion sensors. Optionally, the wearable device may also include a location or GPS tracker as a safety feature. Motion data collected by the wearable device is used for two main purposes: 1) to objectively measure hyperactivity levels based on specific metrics (distance, time active, area, micro-events) or other metrics deemed relevant for treatment of ADHD; and 2) to track the child's sleep-wake patterns (given a high percentage of children with ADHD are known to have sleep disorders). Further, the wearable device may detect presence or absence of aggression. Additional sensors may be included to aid the assessment of sleep-wake patterns. Various features of the device, method, and system in accordance with the present disclosure are shown in FIGS. 4-14. The interrelationships of the device, method, and system, as well as the child, parent, therapist and prescriber can be seen illustrated in FIG. 8.

[0063] Also, the present invention may employ sensors other than or in addition to motion sensors. For example, heart rate sensors may be used to supplement the amount and type of data collected and increase the sensitivity and accuracy of the present invention.

[0064] Turning to FIG. 8 the system of the present disclosure is generally illustrated where the wearable device 10 of the present disclosure is shown as a bracelet but may be any wearable device or tag that is portable and can be kept or worn on the child. The wearable device 10 preferably connects to an electronic device 12 such as a smartphone or tablet having a computer processor therein via a wireless communications connection of any type known in the art. The wearable device interfaces 10 with an app operating on the electronic device 12 and includes both a child and a parent interface. The wearable device 12 also has connectivity to the provider via app connection to an electronic communications network or cloud-based exchange 14, such as both a therapist and prescriber, either through an app or direct integration in the electronic health record through an API. The wearable device is preferably in the form of a watch or a device worn on the wrist. The present disclosure may employ any type of wearable device that can be worn on any part of the body in any form, such as a jacket, vest, shirt, pants hat, shoes, belt, eyewear, and the like. Still further, the wearable device may be in the form of a smartphone or other device that may be held in the hand or stored in a pocket or other location on a person.

[0065] The system of the present disclosure as shown at FIG. 8 may have four categories of users, such as child 16, parent/caregiver 18, therapist 20, prescriber 22, and the like, who will interact with the device through different channels and at different points in time with the ultimate goal of the system as a whole to facilitate the delivery of behavioral treatment (i.e. based on contingency theory and involving increasing desired behaviors by providing positive reinforcement) for ADHD. In operation, the child 16 wears the wearable device 10 that detects and collects data from various sensors contained therein. The collected data is transmitted to the app operating on the electronic device 12 for processing and comparison to various behavior targets that are programmed therein. The collected and target compared data is then transmitted from the electronic device 12 via communication network 14 for further interaction and analysis with a parent/caregiver, therapist 20 and or other medical professionals such as prescribers 22, insurance providers, etc., as will be discussed in more detail below.

[0066] In setting up and maintaining the system of the present disclosure during operation, as shown in FIG. 2, desired target behaviors 24 (up to five total at a given time) are identified by the parent (ideally along with a therapist) as shown in the exemplary daily report card and in the illustration at FIG. 9. The target behaviors 24 are set into the system and then used for baseline comparisons and further processing during the course of treatment. The consideration is to have three motion based behaviors that are selected from a drop-down list in the app (motion based behaviors, such as staying seated during class, no running, sitting still, no aggression) and two non-motion related behaviors (such as medication compliance, complete bedtime routine). The behaviors can be customized to be tracked during specific timeframes, such as school class, dinner time, homework time.

[0067] Additionally, the system of the present disclosure may employ a different approach to identifying, tracking and reinforcing child's behavioral functioning in addition to the pre-determined motion based behaviors described above.

[0068] Additionally, in accordance with the disclosure, parents/caregivers preferably create and input routines in the app on the electronic device 12 that generate a schedule 26 for the child 16 as is illustrated at FIGS. 3 and 10 for the child (e.g. morning/bedtime routine) via the connected app (with a parent interface) given that children with ADHD have significant difficulties in this area as part of their executive dysfunction. These routines provide a checklist for the child (including a visual) to follow and therefore aid their successful completion and being a non-motion related behavioral goal that is reinforced as described above.

[0069] As shown in the flow charts of FIGS. 4, 5 and 6, motion data 28 is collected and analyzed by an algorithm operating on the electronic device 12 with three main objectives: [0070] 1. Determine the child's baseline hyperactivity level (at the beginning of the treatment intervention) based on four specific metrics (distance, time active, area, micro-events) or other metrics deemed relevant. Metrics are preferably used for each specific behavior (e.g. for “no fidgeting”—micro-events/area, for “staying seated during class”—distance, area). [0071] 2. Collect motion data 28 as collected in the wearable device 10 and transmit the collected motion data 28 to the electronic device 12 for analysis by the app to determine changes in the hyperactivity level from baseline along those four specific metrics (or other metrics) once the intervention is initiated. The desired behaviors and rewards (positive reinforcement) are reviewed by the parent with the child and the child is aware of the plan/expectations which marks the beginning of the intervention. Also, the desired behaviors and rewards are reviewed with the child on an ongoing basis. [0072] 3. Determine based on pre-set parameters at what level of change the rewards will be generated and presented to the child. The algorithm adapts to the child's performance in order to deliver an appropriate challenge (not too difficult or too easy) and foster progress (i.e. behavioral shaping=initially reinforce small changes in behavior and later making it gradually more difficult for the child to earn rewards). For instance, at the start of treatment the reward could be set to be generated for a 10% change (decrease) in hyperactivity level along the specific metrics. However, if after a set period (e.g. 24 hrs.; specific duration to be determined during proof-of-concept studies) there is only a maximum 6% change in hyperactivity the algorithm will adapt and generate rewards for 6%. Subsequently after a set period (e.g. 48 hrs.) of the child consistently achieving 6% change in hyperactivity, the algorithm will start generating rewards for a higher % change (e.g. 7%) in order to increase the level of challenge and foster progress. While an embodiment of the algorithm is set forth below, it should be understood that the algorithm may be modified to suit the application at hand and the particular patient or health issue to be treated, such as ADHD.

[0073] Further, FIG. 7 shows a tiled diagram of the features and interactions of the features of the present disclosure as discussed in detail herein.

[0074] To add more nuance to the algorithm of the present disclosure and more intensive re-enforcement, different degrees of rewards (e.g., number of points) for different performance level (% change in hyperactivity metrics) may be rewarded. For instance, a 4% change provides 10 points, and a 6% change provides 20 points.

[0075] The pre-set parameters based on which rewards are generated will be contingent on additional factors. The child's age will be one of the contingencies given expected developmental variations of the child's ability for self-control and response to rewards (e.g. younger children may require reinforcements for smaller % changes). Additionally, the algorithm will adapt the parameters (i.e. % change based on which rewards are generated) to the child's sleep quality in a given day reflected by a “sleep score” (determined based on the analysis of sleep data) given the expected possible decline in a child's overall performance in the context of poor sleep. The “sleep score” and specific cut-offs to classify the sleep quality (e.g. normal or mild/moderate/severe sleep impairment) will be determined through proof-of-concept studies. Other contingencies may be considered in algorithm development for example gender, setting (i.e. school or home) among others. Furthermore, the algorithm and specifically the pre-set parameters will be fine-tuned based on population-level performance with growing population data being collected.

[0076] The present disclosure also provides additional consideration for utilization of motion data and other physiological data. For example, machine learning tools (e.g. entropy analysis) will be used to assess impulsivity or inattention (the other core features of ADHD besides hyperactivity) using this wearable. Additionally, similar data analytics tools may be employed to make a determination relative to the presence or absence of aggression which could be part of the ADHD clinical picture. The ability to detect/track those symptoms further strengthens the therapeutic value of the wearable device as they could be included among the target behaviors (e.g. lack of aggression) to be tracked and reinforced.

[0077] The method, device and system of the present disclosure provides for child device interaction. The child 16 wears the wearable device 10 continuously (most of the day and night and across settings) and will be able to access the app (using a child interface) operating on the electronic device 12 and connected to the wearable device 10 on a smartphone or tablet.

[0078] As described at FIG. 4 and illustrated at FIG. 11, the wearable device 10 includes a display 30 on which the child 16 chooses an Avatar 32 (from several alternatives provided) to be displayed and used as one of the channels for rewards delivery. The Avatar's size/color or strength changes as shown in improved Avatar 34 in correlation with the rewards/points determined by the algorithm. Several Avatar choices are provided to appeal to children of different age, gender, cultural background. The app interface operating on the electronic device 12 presents the list of desired behaviors (up to five), the daily routines (as entered by parents) and a performance review/points balance for viewing by the child 16. An interactive feature of the wearable device 10 prompts the child visually or haptically through a display or vibration each time the tracking period is starting (e.g. math class is starting and he/she is expected to sit in the chair) and may provide reminders of target behaviors in a child friendly format.

[0079] The wearable device 10 itself, includes a display 30 where the child 16 can see the Avatar 32 and its changes to an improved Avatar 34. The changes in the Avatar constitute the visual component of the positive reinforcement that is updated immediately following the desired behavior and the Avatar update is delivered autonomously without requiring caregiver firsthand involvement.

[0080] Additionally, the system of the present disclosure may employ a different approach for the visual component of the positive reinforcement other than Avatar if deemed necessary in order to optimize its impact and attend to a diverse patient population.

[0081] The positive reinforcement for the desired behavior has two additional components. The first one entails points earned as calculated by the algorithm. Further points can be entered manually by the parent for the non-motion related goals. The points will be presented as illustrated in FIGS. 1 and 9 to the child 16 using the app in a summary format at the end of each day/week/month as points balance and performance review in form of a graph or other child friendly visual. As shown at FIG. 12, the points are then translated into a reward 36 such as family movie night, videogame time or other rewards as predetermined by the parent 18 and previously discussed with the child 16. Ultimately the goal is for the points to translate automatically in videogame time or features in a particular game that the child accesses or plays through the app interface.

[0082] The second component stems from the parent being able to see in real-time the child's performance (via app interface) and through an interactive feature to be able to send a random reinforcement to the child, such as a “great job” emoji for presentation to the child 16 on the display 30.

[0083] The app interface operating on the electronic device 12 presents to the child 16 the expected daily routines (e.g. morning and night) in form a picture board or another child friendly format.

[0084] The wearable device 10, is connected to the app operating on the electronic device 12 and also may be connected via the electronic device 12 and communications network 14 and integrate with software platforms used by teachers to communicate homework schedule/requirements (e.g. eChalk). This will assist children having ADHD with their planning challenges as part of their executive dysfunction. Additional features in some embodiments may include the device prompting the child to engage in up to 30 min of moderate-vigorous physical activity daily given data showing acute physical exercise to lead to improvement in executive functioning in children with ADHD. This could be a set goal for the child with its completion being determined by tracking motion data. Further, integration with exergaming can facilitate the child's engagement in a moderate-vigorous physical activity.

[0085] The method, device and system of the present disclosure also provides a unique parent-device interactivity, as seen in FIGS. 5 and 12. For the example, the parent will interact with the device primarily through the app interface which will allow her/him to enter behavioral goals and daily routines, enter points for the non-motion based goals (e.g. medication compliance/routine completion) and see child performance. The parent will identify desired behaviors, ideally along with a therapist, and enter them through the app. Additionally, the parent will create the daily routines by inputting them through the app from a drop-down list, such as get out of bed, brush teeth, get dressed, or the like.

[0086] The parent will be able to see the child's performance on the motion based goals both in real time and at the end of the day/week/month. In this context, the parent will be able to reinforce the child both in real time through the interactive feature (e.g. sending “great job” emoji) and at the end of the day/week/month. The parent will input manually points for the non-motion based goals (e.g. medication compliance).

[0087] Therapist 20 and prescriber 22 interaction is also provided with the present disclosure, as seen in FIGS. 6, 8 and 13. For example, the therapist 20 and prescriber 22 interacts with the device mainly through the wireless communication network 14 directly to the app operating on the electronic device 12 or through the electronic medical record which is integrated with the app. The interface shares a child's performance, analyzed motion data (e.g. graphs showing hyperactivity variation throughout the day), and sleep data, which would inform adjusted treatment decisions, for prescriber (medication adjustments) and for therapist behavioral goals adjustments. These changes in treatment 38 are sent by the medical professionals for presentation on the parent interface of the app operating on the electronic device 12 or any other electronic device carried by the parent.

[0088] Other users may interact with the method and system of the present disclosure. The growing customer base coupled with the long-term use of the wearable device will allow for de-identified and privacy compliant data collection including motion and sleep data (and other sensor data), medication choices/dosage/compliance, treatment response and demographics. The accumulated data provides a valuable platform for multiple uses such as 1) Clinical/treatment research including but not limited to the use of predictive analytics to identify determinants of treatment response or risk factors for treatment resistance; and 2) pharmaceutical companies could utilize this platform and the device to aid their clinical trials for drug development including dosage optimization. Currently, drug efficacy during clinical trials is determined by using questionnaires administered either by a clinical investigator (e.g. ADHD Rating Scale (ADHD-RS), Clinical Global Impression-Improvement (CGI-I) rating scale) or by the parent (Conners' Parent Rating Scale). While those questionnaires are standardized tools, they add a level of subjectivity and are also labor/staff intensive therefore costly. For instance, ADHD Rating Scale (ADHD-RS) is an 18-item questionnaire with a score range of 0-54 points that measures the core symptoms of ADHD which includes both hyperactive/impulsive and inattentive subscales, and 3) Insurance companies could also utilize the platform to identify through data analytics optimized treatment protocols and aid in their population health management, as in FIG. 6.

[0089] It should be understood that the invention herein is not limited to the treatment of ADHD. The same principles, tools, methods, devices and system of the present invention can be used for treating other health issues, such as other disruptive behavior disorders, obesity, depression, and the like.

[0090] While there is shown and described herein certain specific structure embodying the disclosure, it will be manifest to those skilled in the art that various modifications and rearrangements of the parts may be made without departing from the spirit and scope of the underlying inventive concept and that the same is not limited to the particular forms herein shown and described except insofar as indicated by the scope of the appended claims.