Mental State Quantification via Biometric Sensors and Automated Actions
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Solution Overview
Problem
Current technologies lack effective methods to quantify and influence users' mental states using network-connected devices, failing to provide measurable improvements in mental well-being through automated actions.
Innovation Solution
A system that utilizes biometric sensors to quantify users' mental states and selects automated actions for network-connected devices, such as lighting, temperature, and media, based on effectiveness scores and priority rankings, to affect mental states in predetermined manners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated actions are implemented to affect mental states, then mental well-being is improved, but the system complexity increases
Solution Approach 1:
The system segments the complex task of mental state management into distinct components: biometric data collection, mental state quantification, automated action selection, and effect measurement. Each component is handled by separate modules (biometric sensors, processor, action selection system, and monitoring system), making the overall system more manageable and implementable while achieving reliable mental well-being improvement
Solution Approach 2:
The processor acts as an intermediary that receives biometric data from sensors, quantifies mental states, selects appropriate automated actions, and sends commands to network-connected devices. This intermediary layer abstracts the complexity between data collection and action execution, enabling reliable mental state management without requiring direct complex interactions between all system components
2Measurement precision
If biometric data collection is implemented to quantify mental states, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The biometric sensors are integrated into existing network-connected devices that users already possess, such as smartphones, wearables, and home appliances. These devices serve multiple functions: they collect biometric data, communicate over networks, and execute automated actions. This multi-functionality reduces the need for dedicated complex biometric sensing equipment while maintaining measurement precision for mental state quantification
3Productivity
If automated actions are selected based on effectiveness scores, then productivity of mental health intervention is improved, but computational requirements increase
Solution Approach 1:
The system pre-calculates effectiveness scores for different automated actions based on historical data and user profiles before actual mental state interventions are needed. These pre-computed effectiveness scores are stored and readily available when real-time decisions are required, eliminating the need for complex real-time computations and reducing energy consumption during critical intervention moments while maintaining high productivity
Data Source
AI summary
Devices, computer-readable media and methods for affecting mental states of a first user and a second user are disclosed. For example, a processor may receive first biometric data for a first user, quantify a mental state of the first user based upon the first biometric data, receive second biometric data for a second user, and quantify a mental state of the second user based upon the second biometric data. The processor may further select a first automated action to affect the mental state of the first user and the mental state of the second user, and implement the first automated action to affect the mental state of the first user and the mental state of the second user.