Sparse Sensor Array Layout for Brain Signal Spatial Detection
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Solution Overview
Problem
Existing brain activity detection methods face challenges in accurately measuring spatial information with high accuracy while considering the convenience of the signal generating unit, as they often rely on electrode arrangements that adhere to the Nyquist-Shannon sampling theorem, limiting sensor density and spatial resolution.
Innovation Solution
A signal detection device with a first detection sensor set arranged in a sparse array, sparser than the minimum density required by the Nyquist-Shannon sampling theorem, combined with a second detection sensor set positioned in free space, allowing for higher accuracy and reduced measurement costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detection sensors are arranged according to the Nyquist-Shannon sampling theorem with minimum sensor array density, then spatial information can be measured, but measurement precision and spatial resolution are limited
Solution Approach 1:
The patent introduces a vertical dimension by arranging detection sensors at multiple heights (first height and second height) rather than only on a single plane. This three-dimensional sparse array configuration enables accurate spatial information measurement with fewer sensors by utilizing the vertical dimension for signal differentiation, thereby resolving the contradiction between measurement precision and sensor quantity.
Solution Approach 2:
The patent applies different detection sensor configurations at different locations and heights. The first detection sensor set is arranged at a first height with specific spacing, while the second detection sensor set is arranged at a second height with different spacing. This local differentiation allows each sensor set to optimize for its specific spatial region, improving overall measurement precision while maintaining sparse sensor distribution.
2Measurement precision
If more detection sensors are used to improve spatial resolution, then measurement precision improves, but device complexity and measurement costs increase
Solution Approach 1:
The patent divides the detection sensor system into multiple discrete sets (first detection sensor set and second detection sensor set) positioned at different heights. Each set is independently arranged with specific spacing according to the Nyquist-Shannon sampling theorem for its layer. This segmentation allows the system to achieve high spatial resolution through coordinated operation of multiple simple, regularly-spaced sensor sets rather than one complex dense array.
3Measurement precision
If detection sensors are densely arranged to ensure high accuracy, then spatial information is measured accurately, but convenience of signal acquisition is reduced
Solution Approach 1:
By utilizing the vertical dimension with sensors at multiple heights, the patent achieves accurate spatial information measurement with a sparse three-dimensional distribution of sensors. This eliminates the need for dense two-dimensional sensor arrangements, thereby maintaining signal acquisition convenience while ensuring measurement precision through the added vertical dimension.
Data Source
AI summary
Disclosed is a signal detection device, which includes a first detection sensor set that detects input signals generated from a signal generator and reconstructs output signals based on the input signals, and the first detection sensor set includes a plurality of detection sensors, and at least some of the plurality of detection sensors are arranged in a sparse array having a sparser number of sensors than a minimum value of a density of a sensor array based on a Nyquist-Shannon sampling theorem.