Emotion Tracking Interface with Gesture-Based Viscosity Feedback
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Solution Overview
Problem
Current methods for tracking and responding to mental health changes lack effective and user-friendly solutions for seamlessly capturing emotional states and prompting support when needed.
Innovation Solution
A method involving a graphical user interface that allows users to input emotion values through gestures, updating a virtual object's color and viscosity, and automatically prompting external entities for support when predefined trigger values are reached, enabling tracking and response to mental health changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional mental health tracking methods are used, then comprehensive emotional data can be collected, but user burden and complexity increase
Solution Approach 1:
The system automatically collects emotional data through passive monitoring of user interactions with the device, eliminating the need for active user input. The graphical object updates based on inferred emotional states from usage patterns, allowing the system to serve itself by automatically tracking mental health metrics without burdening the user.
Solution Approach 2:
The patent replaces manual self-reporting mechanisms with automated computational methods. Instead of requiring users to actively input emotional data, the system uses algorithms to infer emotional states from digital footprints and interaction patterns, substituting mechanical user actions with automated electronic monitoring.
2Loss of time
If frequent monitoring is implemented, then timely intervention is possible, but user privacy and data security concerns increase
Solution Approach 1:
The system extracts only the essential emotional state information needed for monitoring purposes while leaving detailed personal data private. By focusing on aggregated emotional trends rather than granular personal details, the system achieves timely monitoring while minimizing privacy intrusion through selective data extraction.
Solution Approach 2:
The graphical object serves as an intermediary that visualizes emotional states without exposing raw personal data. The color-coded representation acts as a mediator between the user's private emotional state and the monitoring system, allowing timely detection of mental health changes while maintaining a layer of privacy protection.
3Ease of operation
If simple interaction methods are used, then ease of use improves, but measurement precision of emotional states decreases
Solution Approach 1:
The system adds temporal and contextual dimensions to simple gesture inputs. By analyzing the pattern, timing, and context of gestures rather than relying on single isolated inputs, the system maintains measurement precision while preserving ease of operation. The graphical object's evolution over time provides additional measurement data without requiring more complex user actions.
Data Source
AI summary
One variation of a method for tracking and responding to mental health changes in a user, the method includes: rendering a graphical object within a graphical user interface; indexing an emotion value assigned to the graphical object through a spectrum of emotion values according to a direction of an input into the graphical user interface; within the graphical user interface, updating the graphical object to visually correspond to the emotion value assigned to the graphical object; recording submission of a final emotion value through the graphical user interface; and in response to the final emotion value equaling a trigger value, distributing a prompt to monitor the user to an external entity.