Mental Wellness Platform Using ML for Personalized Therapy

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Solution Overview

Problem

Existing technologies for managing mental wellness are inadequate as they fail to assess and diagnose individual mental health parameters effectively, lack personalized feedback, and cannot manage multiple mental disorders simultaneously, leading to insufficient self-management tools for users.

Innovation Solution

A system and method that uses a communication device to transmit a natural language questionnaire to a user device, analyzes responses using a machine learning model to determine mental health assessments, and identifies therapy information for personalized mental wellness management, incorporating sound, color, and digital art therapies within a mobile application platform.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If existing online platforms provide sensory stimulation therapy through light, sound, and vibrations, then users can access mental health therapy, but the treatment is generalized and same for each individual without appropriate analysis of user input patterns

Engineering Contradiction:

Improvepersonalization of therapyVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system continuously collects user input data during therapy sessions and provides real-time feedback by adjusting the sensory stimulation parameters. The machine learning model analyzes user responses and feeds this information back to modify the therapy protocol dynamically, creating a closed-loop system that adapts to individual user patterns while maintaining manageable complexity through automated feedback mechanisms.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system employs machine learning models that automatically analyze user input patterns and generate personalized therapy protocols without requiring manual intervention from therapists. The automated analysis and adaptation processes enable the system to serve itself in creating customized treatments, reducing the complexity burden on human operators while delivering personalized care.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If existing technologies provide separate therapy methods for different mental states, then specific conditions can be addressed, but multiple mental disorders cannot be managed simultaneously on a single platform

Engineering Contradiction:

Improvemulti-disorder management capabilityVSAvoidcomprehensive user data integration

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The system is designed as a universal platform that can handle multiple types of mental disorders simultaneously through a single integrated interface. The machine learning model is trained to recognize and process various patterns associated with different disorders, enabling the system to provide comprehensive multi-disorder management without requiring separate systems for each condition.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system merges multiple therapy approaches (sensory stimulation, visual arts, audio processing) into a single integrated platform that can address multiple disorders concurrently. By combining different therapeutic modalities and integrating user data from various sources, the system creates a unified solution that manages complex multi-disorder cases while preserving comprehensive user information.

Inventive Principle:

Principle #5Merging (Combining)

3Measurement precision

If existing platforms do not assess and diagnose individual mental health parameters, then the system is simpler to operate, but personalized feedback and therapy protocols cannot be provided

Engineering Contradiction:

Improvemental health assessment accuracyVSAvoiduser operation simplicity

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system replaces manual mental health assessment processes with automated machine learning models that perform diagnosis and analysis. This substitution enables precise measurement of mental health parameters through algorithmic analysis of user input, while maintaining ease of operation as the automated system handles the complex assessment tasks without requiring user expertise in mental health evaluation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20230136754A1Methods and systems of facilitating management of mental wellness

Publication Date: 2023.05.04 ASIS DANIEL GUILLERMO

AI summary

The present disclosure may provide a method of facilitating management of mental wellness. Further, the method may include transmitting a questionnaire information to a user device associated with a user. Further, the questionnaire information is based on a natural language. Further, the method may include receiving a response information from the user device. Further, the response information may comprise a response based on the questionnaire information. Further, the response information is based on the natural language. Further, the method may include analyzing the response information using a first machine learning model. Further, the method may include determining a mental health assessment of the user based on the analyzing of the response information. Further, the method may include identifying a therapy information for the user based on the determination of the mental health assessment of the user.