Signal Filtering Apparatus for Wearable Biosignal Noise Reduction
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Solution Overview
Problem
Wearable medical devices face challenges in maintaining a high signal-to-noise ratio (SNR) due to limitations in sensor performance, power usage, and device size, requiring low complexity noise signal processing methods to effectively filter biosignals.
Innovation Solution
A signal processing method involving a low frequency band pass filter and a subtractor to remove unnecessary signals, with compensation for time delay and DC offset, determines whether DC offset compensation is needed based on the target signal's frequency, using an infinite impulse response (IIR) filter to minimize calculation complexity and signal distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex filtering methods are used to improve noise removal, then signal-to-noise ratio improves, but device complexity and power consumption increase
Solution Approach 1:
The filtering process is divided into two distinct stages: first extracting the noise signal through a band-pass filter, then subtracting it from the original biosignal. This segmentation allows each stage to be optimized independently, reducing overall complexity while maintaining effective noise removal.
Solution Approach 2:
The noise signal is extracted separately using a band-pass filter tuned to the noise frequency range, then removed from the original signal through subtraction. This extraction approach isolates the noise component, enabling targeted removal without requiring complex multi-parameter filtering algorithms.
2Measurement precision
If high performance filtering is implemented, then signal quality improves, but power consumption increases
Solution Approach 1:
The patent uses computationally inexpensive filtering operations (band-pass filtering and subtraction) that can be executed quickly and efficiently on mobile devices. These simpler operations consume less power compared to complex adaptive filtering algorithms, enabling sustained operation in battery-powered wearable devices.
3Device complexity
If simple filtering methods are used, then device complexity is reduced, but noise removal effectiveness deteriorates
Solution Approach 1:
A band-pass filter acts as an intermediary component that selectively extracts the noise signal from the mixed biosignal. This intermediary filtering stage prepares the noise component for subsequent subtraction, achieving effective noise removal through a two-step process that balances simplicity and effectiveness.
4Measurement precision
If real-time noise subtraction is performed, then signal accuracy improves, but processing time increases
Solution Approach 1:
The noise signal is extracted and prepared in advance through band-pass filtering before the subtraction operation. This preliminary preparation of the noise component enables faster real-time processing during actual signal filtering, as the complex extraction computation is performed separately and efficiently.
Data Source
AI summary
A signal processing method, a signal filtering apparatus, and a signal processing apparatus are provided. An input signal may be input into a filter having a passband, a superfluous signal of the passband may be output from the filter, and a target signal may be obtained by subtracting the superfluous signal from the input signal.