Emotion Evaluation via Sympathovagal Balance and Brain-Wave Synchronization
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Solution Overview
Problem
Current technologies for evaluating human emotions, particularly in wearable devices, face challenges in accurately determining emotional states through cardiac-activity and brain-wave data due to noise interference and the complexity of interpreting sympathovagal balance and brain-wave activity.
Innovation Solution
The development of software that processes cardiac-activity and brain-wave data to determine shifts in sympathovagal balance and emotional states, using noise correction techniques and machine learning algorithms to identify emotional characteristics and energy levels, and synchronizes data for accurate emotion estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cardiac-activity data and brain-wave activity data are used to evaluate emotional states, then the accuracy of emotion evaluation is improved, but noise interference increases and makes interpretation more complex
Solution Approach 1:
The patent segments the complex task of emotion evaluation into distinct components: cardiac-activity analysis for sympathovagal balance determination and brain-wave activity analysis for emotional-state characteristic extraction. Each component is processed separately through dedicated software modules, making the overall complex system more manageable and interpretable while maintaining high accuracy.
2Reliability
If multiple data processing techniques are applied to reduce noise, then measurement reliability is improved, but processing complexity increases
Solution Approach 1:
The patent introduces intermediary processing layers including noise correction techniques and synchronization mechanisms that mediate between raw cardiac-activity and brain-wave data. These intermediaries filter and prepare the data before final emotion evaluation, improving reliability while managing complexity through structured intermediate processing steps.
3Speed
If real-time emotion evaluation is implemented, then responsiveness is improved, but computational requirements increase
Solution Approach 1:
The patent performs preliminary actions by continuously monitoring and pre-processing cardiac-activity and brain-wave data in real-time before full emotion evaluation is needed. Data synchronization and noise correction are performed continuously at lower computational cost, so when emotion evaluation is required, the system can quickly produce results without intensive real-time computation.
Data Source
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AI summary
In one embodiment, one or more computer-readable non-transitory storage media embody software that is operable when executed to determine, based on cardiac-activity data, a shift in sympathovagal balance (SVB) during the period of time; obtain an emotional-state characteristic, the emotional-state characteristic being based on brain-wave activity data; and determine, based on the SVB shift and the emotional-state characteristic, an estimate of an emotional state of the user during the period of time.