AI Mental Wellness Tracking System for Bias-Free Analysis
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Solution Overview
Problem
Current mental health resources lack proactive and impartial solutions for tracking and analyzing mental health, mood, and feelings over time, especially for children and young users, and fail to provide comprehensive insights to supervisory users without bias.
Innovation Solution
A system and method that allows users to input journal and session entries through various media (drawing, text, video, audio) and analyze these entries for markers or sequences using AI, alerting supervisory users if thresholds are exceeded, while providing contextual content management and data storage for mental health analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive manual tracking and analysis of mental health data is performed by supervisory users, then detailed insight and analysis can be provided, but the process is time-consuming and subject to human bias
Solution Approach 1:
The patent replaces manual mechanical analysis by supervisory users with automated computer-based analysis. The system uses software to automatically track, analyze, and interpret mental health data from multiple sources (journals, surveys, wearable devices), eliminating the time-consuming manual review process while maintaining or improving analysis accuracy through consistent algorithmic evaluation.
Solution Approach 2:
The system enables self-service by allowing users to automatically input and track their own mental health data through various interfaces and devices. The automated analysis engine then processes this data without requiring supervisory user intervention, enabling continuous monitoring while reducing the time burden on professionals.
2Loss of information
If multiple data collection methods (drawing, text, video, audio) are implemented to capture comprehensive mental health information, then the quality and depth of insights improve, but the system complexity increases
Solution Approach 1:
The patent implements a universal platform that handles multiple types of data input (drawings, text, video, audio) through a single integrated system. The common interface and centralized data storage structure allow the system to process diverse data types uniformly, capturing comprehensive mental health information without proportionally increasing system complexity.
Solution Approach 2:
The system introduces an intermediary layer consisting of standardized data processing pipelines and common storage formats that mediate between various input sources and the analysis engine. This intermediary structure simplifies the integration of multiple data collection methods by providing uniform interfaces and processing routines for each data type.
3Reliability
If automated analysis of journal entries and media inputs is performed to detect markers and patterns, then objectivity and consistency of analysis improve, but the risk of missing nuanced contextual understanding increases
Solution Approach 1:
The system implements feedback loops where automated analysis results are continuously refined based on user corrections, supervisory user validations, and pattern recognition improvements. The system learns from feedback to better understand contextual nuances while maintaining the consistency and objectivity of automated analysis through iterative algorithmic improvements.
Data Source
AI summary
A system and method for promoting, tracking, and assessing mental wellness. The method includes receiving an entry from a subject user, the entry including an input and a mood indicator, storing the entry in within a set of entries, the set including at least two entries received over a period of time, and determining a presence of at least one marker in the input of each entry within the set. The method further includes analyzing the set of entries for occurrences of markers or sequences of markers and alerting a supervisory user if the occurrences of markers or sequences of markers exceed a predetermined threshold. The method further includes associating contextual content from a supervisory user to an entry, the contextual content including a note, an attachment, a form, and/or a flag. The system includes a platform for accessing, managing, and storing data and analytics for implementing the method.