Wearable Emotion Adjustment via Physiological Data Analysis
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Solution Overview
Problem
Current methods for adjusting user emotions lack convenience and effectiveness, often requiring dedicated devices and failing to consider individual differences in emotional responses.
Innovation Solution
A method and apparatus using wearable devices to collect real-time physiological data, which is sent to a terminal device to determine emotions and perform adjustments, incorporating artificial intelligence to update parameter weights for improved accuracy and incorporating social emotion adjustment methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated devices (e.g., finger sensors) are used to detect user physical condition, then measurement precision of physiological parameters is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent applies multi-functionality by enabling smartphones and wearable devices to perform both their original functions and emotion detection functions. The smartphone uses its existing camera, microphone, and sensors to detect physiological parameters, while wearable devices like smartwatches use their integrated sensors for continuous monitoring. This eliminates the need for dedicated emotion detection devices while maintaining measurement precision.
Solution Approach 2:
The system applies self-service by automatically detecting physiological parameters and determining user emotions without requiring manual intervention. The wearable device continuously monitors heart rate, temperature, and other parameters, and the system automatically processes this data to identify emotional states, freeing the user from active participation in the detection process.
2Measurement precision
If multiple parameters are collected and analyzed, then emotion determination accuracy is improved, but device complexity and data processing requirements increase
Solution Approach 1:
The patent applies segmentation by dividing the emotion detection system into modular components: wearable devices for data collection, smartphones for initial processing, and servers for comprehensive analysis. Each segment handles specific tasks, reducing the complexity burden on any single device while maintaining high accuracy through collective processing of multiple parameters.
Solution Approach 2:
The patent introduces an intermediary layer (the smartphone and server algorithms) that processes and integrates data from multiple sensors. This intermediary systematically combines heart rate, temperature, motion, and other parameter data using machine learning models, managing the complexity of multi-parameter analysis while improving emotion determination accuracy.
3Productivity
If real-time emotion adjustment operations are performed, then responsiveness and productivity are improved, but energy consumption increases
Solution Approach 1:
The patent applies periodic action by implementing continuous but optimized monitoring cycles. The wearable device collects physiological parameters at regular intervals rather than continuously, and the system performs emotion analysis at strategically determined moments. This periodic approach maintains real-time responsiveness while significantly reducing energy consumption compared to constant monitoring and processing.
Data Source
AI summary
A method and an apparatus for adjusting a user emotion are provided. In one example, the method includes obtaining, by a terminal device, data that represents a physical condition of a user, where the data comprises first data, and the first data is at least one parameter value detected for the user by a wearable device connected to the terminal device. The method also includes obtaining, by the terminal device, emotion information determined based on the data and performing, by the terminal device, an operation corresponding to the emotion information.