Adaptive Emotion Recognition Therapy for Depression
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Solution Overview
Problem
Current treatments for affective disorders such as major depressive disorder (MDD), post-traumatic stress disorder (PTSD), and anxiety disorders are inadequate, as they induce remission in only one-third of subjects, necessitating more effective interventions that target impaired brain regions involved in these conditions.
Innovation Solution
A computing system that conducts therapy sessions by displaying a series of expression images with varying intensities, challenging the subject to identify emotional consistency across images, and adjusts the difficulty level based on performance, thereby enhancing cognitive control over emotional information processing and emotion regulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional treatments (medication, psychotherapy) are used for affective disorders, then treatment is provided, but remission is achieved in only one-third of subjects
Solution Approach 1:
The patent replaces conventional mechanical/chemical treatments (medication and standard psychotherapy) with a computer-based cognitive training system that uses computational algorithms to deliver adaptive emotional regulation exercises, thereby improving remission rates while maintaining treatment accessibility
Solution Approach 2:
The system dynamically adjusts training parameters including exercise difficulty level, session duration, and task complexity based on real-time performance monitoring, allowing personalized adaptation to individual patient needs and optimizing treatment effectiveness across different severity levels
2Reliability
If cognitive emotional exercises are implemented to enhance cognitive control, then emotion regulation improves, but the complexity of the therapy system increases
Solution Approach 1:
The comprehensive cognitive emotional training program is divided into distinct functional modules including emotion identification exercises, emotional regulation tasks, cognitive retraining exercises, and self-monitoring components, allowing systematic delivery and easier implementation while maintaining overall therapeutic effectiveness
Solution Approach 2:
The system incorporates automated performance monitoring and adaptive algorithm adjustment that operates without continuous clinician intervention, with the computer system automatically analyzing patient responses and modifying exercise parameters to maintain optimal challenge levels, thereby reducing operational complexity
3Productivity
If expression images with varying intensities are displayed to challenge emotional consistency, then cognitive processing improves, but the difficulty of the therapy task increases
Solution Approach 1:
The system dynamically adjusts the difficulty level of emotional consistency tasks based on real-time performance monitoring, automatically increasing challenge when performance is strong and reducing difficulty when struggles are detected, thereby maintaining optimal learning zones without overwhelming the patient
Solution Approach 2:
Real-time feedback mechanisms provide immediate reinforcement for correct emotional identification and regulation responses, while adaptive algorithms adjust subsequent task difficulty based on performance data, creating a self-regulating system that balances challenge and capability to maximize cognitive processing benefits
Data Source
AI summary
Systems and methods for treating a subject with a psychiatric disorder are provided in winch a therapy session is conducted. In the therapy session, each respective expression image in a plurality of expression images is sequentially displayed. Each expression image is independently associated with an expression. The successive display of images is construed as a tiled series of expression image subsets, each consisting of N expression images. Upon completion of the display of each respective subset, the user is challenged as to whether the first and the last images in the respective subset exhibit the same emotion. A score is determined for the respective subset based on whether the subject learned to respond correctly. The number of images in each subset is adjusted to a new number based on these scores. A treatment regimen is prescribed to the subject for the psychiatric disorder based at least in part on the scores.