Real-Time Neurofeedback System Using Local Brain Wave Collection
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Solution Overview
Problem
Existing biological feedback training systems fail to provide real-time feedback, requiring hours or days for data analysis and lacking immediate physiological signal feedback, especially in remote settings where equipment like fMRI is expensive and impractical for real-time analysis.
Innovation Solution
A system comprising a local brain wave collection device, a docking device, and a dongle for wireless communication, uploading brain wave and heart rate variability data to a remote cloud system for immediate comparison and feedback, using 19-channel brain wave data to provide visual or auditory feedback for real-time adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If physiological data is uploaded to cloud platform via wired or wireless transmission for analysis, then data can be stored and analyzed remotely, but the feedback time is delayed by several hours to several days
Solution Approach 1:
The patent pre-loads reference physiological data and analysis algorithms into the local device before actual use. This preliminary preparation enables the device to perform real-time comparison and feedback without needing to upload data to the cloud during the feedback moment, thus reducing feedback time while maintaining remote analysis capability
Solution Approach 2:
The patent introduces a local edge computing device as an intermediary between the physiological sensor and the cloud platform. This intermediary performs preliminary data processing, comparison with reference data, and generates feedback locally in real-time, while still maintaining connection to the cloud for updates and comprehensive analysis, thus solving the time delay issue without excessive system complexity
2Measurement precision
If fMRI equipment is used for real-time neurofeedback, then accurate brain imaging can be achieved, but the equipment is expensive and requires more than 30 minutes for signal collection and 10 minutes for feedback calculation
Solution Approach 1:
The patent replaces expensive, complex fMRI equipment with cheaper, portable brain wave collection devices that can be easily deployed. While fMRI provides high precision, this patent uses affordable sensors that capture sufficient brain wave data for feedback purposes, making the system accessible and enabling real-time operation without the 30+ minute collection time required by fMRI
Solution Approach 2:
The patent changes the detection parameters from fMRI's slow, high-resolution imaging to faster brain wave signal detection. By using electrical activity measurement (EEG) instead of magnetic resonance imaging, the system achieves real-time feedback capability while maintaining sufficient accuracy for neurofeedback training purposes
3Ease of operation
If existing biological feedback training systems are used, then physiological data can be collected, but the subject cannot obtain physiological information immediately and requires opening applications to read data retrospectively
Solution Approach 1:
The patent enables the system to automatically perform data collection, analysis, comparison with reference data, and feedback generation without requiring user intervention to open applications or manually retrieve data. The system serves itself by providing real-time feedback directly to the user, eliminating the need for retrospective data reading and improving both convenience and speed
Data Source
AI summary
A system for providing real-time biological feedback training through remote transmission is provided and includes a local brain wave collection device, a docking device, and a dongle. The local brain wave collection device is used to detect a brain wave and a heart rate variability data of a subject. The docking device communicates with the local brain wave collection device remotely to connect a remote cloud system to compare the brain wave and the heart rate variability data with a brain wave database to generate a comparison result, and according to the comparison result, the system provides the subject a feedback training interface.