Physiological Signal Noise Filtering via Synchronous Vibration Detection
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Solution Overview
Problem
Conventional wearable devices struggle with accurately processing physiological signals like PPG signals due to noise and movement artifacts, requiring time-consuming and complex digital signal processing that is not suitable for real-time analysis, especially in dynamic environments like vehicle driving.
Innovation Solution
A physiological signal processing system that synchronously detects physiological and vibrational signals, using a noise determination algorithm and a filtering algorithm to identify and remove noise in real-time, thereby enhancing signal accuracy and reducing computation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional digital signal processing techniques (Kalman filter, Fourier analysis, ICA) are used to remove motion artifacts from PPG signals, then measurement precision is improved, but processing time increases significantly making real-time analysis impossible
Solution Approach 1:
The patent extracts only the essential noise components from PPG signals using a simplified filtering approach that identifies and removes motion artifacts without performing complete spectral analysis. This selective extraction maintains signal accuracy while avoiding the computational burden of comprehensive digital signal processing techniques.
Solution Approach 2:
The patent employs a lightweight, computationally inexpensive filtering algorithm that processes signals quickly and discards processed data, replacing it with new measurements. This approach sacrifices the thoroughness of complex algorithms like ICA or Kalman filtering in favor of rapid, repeatable processing that enables real-time monitoring.
2Measurement precision
If comprehensive digital signal processing is applied to PPG signals to ensure high accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the signal processing task into distinct stages: raw signal acquisition, noise identification based on motion detection, selective filtering of artifact-contaminated segments, and physiological parameter extraction. This segmentation allows each stage to use appropriately simplified methods rather than applying complex processing to the entire signal chain.
Solution Approach 2:
The patent applies filtering selectively only to portions of the PPG signal that contain motion artifacts, identified through motion sensor correlation. Rather than uniformly applying complex processing to all signal segments, the system adapts the processing intensity to local signal quality requirements, reducing overall computational complexity.
3Productivity
If real-time noise filtering is implemented in wearable devices, then productivity is improved, but device complexity increases due to additional processing requirements
Solution Approach 1:
The patent merges the PPG signal processing with motion sensor data analysis into a unified filtering framework. By combining information from both sensors, the system achieves real-time noise rejection without requiring separate complex processing chains, as the motion data provides direct guidance for what to filter from the PPG signal.
Solution Approach 2:
The patent introduces motion sensor data as an intermediary that mediates between raw PPG signals and physiological parameter extraction. This intermediary provides real-time information about motion artifacts, enabling the system to adjust filtering parameters dynamically without requiring complex real-time analysis of the PPG signal itself.
Data Source
AI summary
A physiological signal processing method for filtering noise generated by a physiological signal processing system is performed by a physiological signal processing system having a sensing device and a filtering device in connection with the sensing device. The method comprises steps of synchronously receiving a physiological signal and a vibrational signal detected by the sensing device, performing a noise determination algorithm to acquire information in multiple time periods with noises occurring in corresponding time periods according to the vibrational signal, performing a physiological signal filtering algorithm to filter the noises in corresponding time periods of the physiological signal and compensate the filtered physiological signal, and estimating a physiological parameter according to a result of the signal compensation to generate the physiological parameter with accuracy.