An Improved Vital Signal Extraction Method Based on Laser Doppler Effect

The mixed signal of respiratory waveform and heartbeat waveform detected by the Laser-Doppler system is processed with an intermediate-frequency (IF) interference filtering method, an enhanced extraction method and a waveform-fixing method. To filter the IF interference signals and the noise scatters in the time-frequency graph, the filtering method based on coefficient of variation (CoV) values and the enhanced curve extraction method based on noise-scatter theory are utilized in vital signal analysis. To decouple the respiratory signal and the heartbeat signal in time domain, the waveform-fixing method based on second-order difference theory is utilized in signal decoupling. This method as an algorithm is applied in the computer simulation and laboratory environments. The results show that the above methods can extract the mixed waveforms and identify the respiratory rates and heart rates in real experimental data. The IF interference signal can be filtered adaptively, and the accuracy of the analyzed rates can be improved to about 95%.

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Publication Details

Journal
Sensors
Published
2024-10-31
DOI
https://doi.org/10.3390/s24217027
Citations
1
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.18
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An Improved Vital Signal Extraction Method Based on Laser Doppler Effect

Youzheng Qi, Si Chen, Bowen Zhang, Haiyang Zhang et al.
1 citations
Sensors
Non-Invasive Vital Sign Monitoring
0.18
article

An Improved Vital Signal Extraction Method Based on Laser Doppler Effect

Youzheng Qi, Si Chen, Bowen Zhang, Haiyang Zhang, Yu Li
article en
1 citations

Abstract

The mixed signal of respiratory waveform and heartbeat waveform detected by the Laser-Doppler system is processed with an intermediate-frequency (IF) interference filtering method, an enhanced extraction method and a waveform-fixing method. To filter the IF interference signals and the noise scatters in the time-frequency graph, the filtering method based on coefficient of variation (CoV) values and the enhanced curve extraction method based on noise-scatter theory are utilized in vital signal analysis. To decouple the respiratory signal and the heartbeat signal in time domain, the waveform-fixing method based on second-order difference theory is utilized in signal decoupling. This method as an algorithm is applied in the computer simulation and laboratory environments. The results show that the above methods can extract the mixed waveforms and identify the respiratory rates and heart rates in real experimental data. The IF interference signal can be filtered adaptively, and the accuracy of the analyzed rates can be improved to about 95%.

SensorsVol. 24(21)
Beijing Institute of Technology (CN)
Openalex Percentile: Top 51%
Non-Invasive Vital Sign Monitoring
0.18
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