Pulse Rate Measurement Using Sliding Time Windows
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Solution Overview
Problem
Current methods for measuring pulse rate, such as frequency domain and time domain methods, face challenges including long measurement times and low accuracy due to interference and poor signal quality, necessitating an improvement in pulse wave signal processing.
Innovation Solution
An electronic device method that uses green light to obtain an AC signal, filters it, and employs sliding time windows to dynamically adjust the length of a second window based on the maximum peak position in the frequency domain, allowing for accurate and fast pulse rate measurement, while also using adaptive filtering for red and infrared signals to improve blood oxygen saturation level accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency domain method is used to calculate pulse rate through Fourier transform, then measurement accuracy is improved, but measurement time increases
Solution Approach 1:
The patent divides the pulse wave signal processing into multiple time windows (first time window for initial signal acquisition, second time window for peak detection, third time window for validation). This segmentation allows the system to process signals in smaller, manageable segments rather than requiring long continuous data collection, thus reducing measurement time while maintaining accuracy through systematic analysis of each segment.
Solution Approach 2:
The patent performs preliminary filtering and signal conditioning in the first time window before main analysis. By pre-processing the signal (removing noise, identifying AC components) before the main pulse rate calculation, the system reduces the complexity of subsequent analysis and enables faster processing in later stages without sacrificing measurement accuracy.
2Productivity
If time domain method is used for pulse rate measurement, then measurement speed is improved, but measurement accuracy deteriorates due to interference and poor signal quality
Solution Approach 1:
The patent introduces frequency domain analysis as an intermediary step between raw signal acquisition and final pulse rate determination in the second time window. By converting the signal to frequency domain temporarily to identify peak positions accurately, then returning to time domain for final calculation, the system combines the speed of time domain processing with the accuracy of frequency domain analysis, overcoming the limitations of pure time domain methods.
3Measurement precision
If signal filtering is applied to remove noise from red and infrared signals, then blood oxygen saturation measurement accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent combines the filtering operations for red and infrared signals into a unified processing framework using the same AC signal from green light as reference. By merging the filtering logic and using a common reference signal, the system reduces redundant processing steps and complexity while still achieving effective noise removal and accurate blood oxygen saturation measurement from both wavelength channels.
Data Source
AI summary
A method for method for measuring human pulse and blood oxygen saturation levels by irradiating with green and red light obtains a pulse wave data in a first time window. The length of a second time window is determined according to the pulse wave data and the second time window slides on the pulse wave data in the first time window. A peak position within the first time window is determined and the pulse rate is revealed according to difference in peak position and a sampling frequency of the pulse wave data. An electronic device applying such method is also disclosed.