Adaptive Cognitive-Musical Training for Learning Disorder Rehabilitation
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Solution Overview
Problem
There is a lack of digital therapeutic solutions that allow for the treatment of Special Learning Disorders (SLDs) without the physical presence of a health professional, limiting access to care for children with neurodevelopmental disorders, especially in underserved areas where access to healthcare is already limited.
Innovation Solution
The development of Cognitive-Musical Training (CMT) exercises as Software as a Medical Device (SaMD), which utilizes interactive video and audio content to provide cognitive and musical training through visual and auditory cues, allowing children to respond using gestures, touches, and verbal responses, with adaptive sequencing based on user performance, and can be used autonomously on devices like tablets and smartphones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital therapeutic solutions are developed for treating SLDs, then access to care is improved and healthcare availability increases, but the complexity of creating effective remote treatment systems increases
Solution Approach 1:
The system enables autonomous self-service treatment where children with SLDs can independently complete cognitive-musical training exercises without requiring a health professional to be physically present. The adaptive sequencing automatically adjusts exercise difficulty based on performance, and progress is automatically tracked and reported to professionals remotely.
Solution Approach 2:
The digital therapeutic platform serves multiple functions: delivering cognitive-musical training exercises, adapting exercise sequences based on performance, tracking progress over time, and enabling remote monitoring by health professionals. This multi-functionality consolidates what would otherwise require multiple separate systems into a single integrated solution.
2Reliability
If cognitive-musical training exercises are implemented with adaptive sequencing, then treatment effectiveness is improved, but the complexity of exercise delivery and performance tracking increases
Solution Approach 1:
The exercise sequencing is dynamically adaptive, automatically adjusting the difficulty and type of exercises based on real-time performance feedback. The system transitions from static pre-defined sequences to dynamic adaptive sequencing that responds to each child's individual progress, maintaining optimal challenge levels to maximize therapeutic effectiveness.
Solution Approach 2:
The system implements continuous feedback loops where exercise performance is automatically measured, analyzed, and used to adjust subsequent exercise sequences. This feedback mechanism ensures treatment effectiveness by adapting to individual progress while automating the complexity of performance tracking and sequence adjustment.
3Ease of operation
If remote digital therapy is used instead of physical presence of professionals, then accessibility is improved especially in underserved areas, but the quality of interaction and monitoring may deteriorate
Solution Approach 1:
The digital platform acts as an intermediary between children and health professionals, enabling remote interaction while maintaining care quality. Automated exercise delivery and progress tracking serve as mediators that ensure consistent, high-quality treatment delivery, while professionals receive detailed data for remote monitoring and intervention when needed.
Data Source
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AI summary
Devices, systems, and methods are provided for analyzing and treating learning disorders using software as a medical device. A method may include identifying, by a device, application-based cognitive musical training (CMT) exercises associated with performance of software; receiving a first user input to generate a first sequence of the application-based CMT exercises; presenting a first application-based CMT exercise of the application-based CMT exercises based on the first sequence; receiving, during the presentation of the first application-based CMT exercise, a second user input indicative of a user interaction with the first application-based CMT exercise; generating, based on a comparison of the second user input to a performance threshold, a second sequence of the application-based CMT exercises, the first sequence different than the second sequence; and presenting a second application-based CMT exercise of the application-based CMT exercises based on the second sequence.