Neural Signal Detection Circuit for Dry-Electrode EEG Accuracy
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Solution Overview
Problem
Existing EEG signal detection systems face challenges in accurately and quickly acquiring clean neural signals due to the millivolt scale of EEG signals, particularly with dry electrodes, and in efficiently processing these signals for analysis.
Innovation Solution
A neural signal detection circuit utilizing dry or wet electrodes, comprising a first and second temporal circuit, a transfer transistor, a reset transistor, and comparators, which converts detected voltages into pulse width signals for analog operations, allowing for operations like subtraction, addition, and absolute difference without digital conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If dry electrodes are used to acquire EEG signals, then the complexity in preparing the detection is reduced and preparation time is shortened, but the accuracy and quality of the acquired neural signals deteriorate due to the millivolt scale of EEG signals
Solution Approach 1:
The detection system is divided into multiple channels, each with independent temporal circuits (first and second temporal circuits) that process signals separately. This segmentation allows parallel processing of multiple EEG channels while maintaining signal integrity despite using simplified dry electrodes.
Solution Approach 2:
Temporal circuits serve as intermediary components between the dry electrodes and the final signal output. These circuits include capacitors and transistors that condition, amplify, and filter the weak millivolt-scale EEG signals, bridging the gap between the simple dry electrode interface and the requirement for high measurement precision.
2Measurement precision
If temporal circuits with multiple capacitors and transistors are used for each channel, then the signal processing capability and measurement precision are improved, but the device complexity increases
Solution Approach 1:
Multiple functional components (capacitors for temporal filtering, transistors for signal amplification and switching, reset transistors for circuit initialization) are merged into integrated temporal circuit blocks. Each temporal circuit is a self-contained module that combines several functions, reducing overall system complexity while maintaining high measurement precision through coordinated operation of these integrated components.
3Productivity
If voltage signals are converted to pulse width signals for analog operations, then the processing speed and real-time analysis capability are improved, but the conversion process and additional circuitry increase device complexity
Solution Approach 1:
The system replaces traditional digital conversion and processing mechanisms with an analog pulse width modulation approach. Voltage signals are directly converted to pulse width signals through comparator circuits, enabling real-time analog operations (addition, subtraction, multiplication, division) without requiring digital-to-analog or analog-to-digital converters, thus improving processing speed while managing complexity through analog circuit design.
Data Source
AI summary
There is provided a neural signal detection circuit capable of outputting time difference data or neural data, and including a first temporal circuit and a second temporal circuit. The first temporal circuit is used to store detected voltage energy of a first interval and a second interval as the time difference data. The second temporal circuit is used to store detected voltage energy of the second interval as the neural data. The neural signal detection circuit is used to output the time difference data or the neural data in different operating modes.