Brain Wave Detection Using Pulse Wave Referencing for Noise Reduction
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Solution Overview
Problem
Existing brain wave detection devices struggle to effectively reduce noise from muscles where sensors are not placed, leading to difficulties in improving the signal-to-noise ratio due to myoelectric noise.
Innovation Solution
A brain wave detection system that utilizes a pulse wave measurer to measure pulse waves at specific arterial bifurcations, comparing the time-series signal of brain waves with pulse waves as a reference signal to reduce noise through filtering and lock-in amplification processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are placed on all head and neck muscles to sense myoelectric potential, then noise from muscle movements can be reduced, but device complexity and cost increase significantly
Solution Approach 1:
The patent introduces pulse wave signals as an intermediary reference signal to represent muscle movement noise. Instead of placing sensors on all muscles, the system uses pulse wave measurements (which reflect overall muscle activity) as a mediator to subtract noise from brain wave signals, thereby achieving noise reduction without requiring comprehensive muscle sensor coverage
Solution Approach 2:
The patent creates a copy of the noise signal through pulse wave measurement. The pulse wave signal serves as a representative copy of muscle movement noise, allowing the system to model and subtract noise characteristics without directly measuring every muscle's electrical activity through multiple sensors
2Measurement precision
If myoelectric noise is not reduced, then brain wave signals can be measured directly, but signal-to-noise ratio deteriorates
Solution Approach 1:
The patent converts the harmful myoelectric noise into a useful reference signal. By measuring pulse waves that reflect muscle movement, the system transforms the noise characteristic into a beneficial reference that can be used to subtract noise from brain wave signals, thereby improving signal-to-noise ratio
Solution Approach 2:
The patent implements a feedback mechanism where pulse wave signals are continuously measured and used to generate noise estimates that are fed back into the brain wave signal processing. This feedback loop allows for dynamic noise subtraction, continuously improving the signal-to-noise ratio as the system adapts to changing muscle activity levels
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves a significant improvement in signal-to-noise ratio by reducing noise in brain waves using pulse waves as a reference, effectively filtering and amplifying brain wave signals in various frequency bands.
Implementation Method 1
filtering the measured brain waves and the measured pulse waves with at least one frequency band
Implementation Method 2
performing a lock-in amplification process
Data Source
AI summary
A brain wave detection system according to the present embodiment includes: a brain wave measurer that measures brain waves; a pulse wave measurer that measures pulse waves; and a noise reduction processing device that performs a process of reducing noise in the measured brain waves by comparing a time-series signal of the measured brain waves, as a measurement signal, with a time-series signal of the measured pulse waves, as a reference signal, the time-series signal of the pulse waves being measured in a measurement time slot corresponding to a measurement time slot of the time-series signal of the brain waves.