Robust Cardiac Timing Detection Technique With Vectors Analytic Demodulation in Doppler Cardiogram Sensing

Robust contactless Doppler cardiogram (DCG) detection in practical scenarios encounters challenges arising from radar hardware performance limitations and signal processing effectiveness. In this work, through an analysis of IQ mismatch signals, we proposed a novel vectors analytic demodulation (VAD...

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Bibliographic Details
Published inIEEE transactions on microwave theory and techniques Vol. 72; no. 8; pp. 4866 - 4877
Main Authors Dong, Shuqin, Li, Yuchen, Gu, Changzhan, Mao, Junfa
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:Robust contactless Doppler cardiogram (DCG) detection in practical scenarios encounters challenges arising from radar hardware performance limitations and signal processing effectiveness. In this work, through an analysis of IQ mismatch signals, we proposed a novel vectors analytic demodulation (VAD) method, which employing the original radar signal to generate four basis vector signals, to linearly obtain the target's differential displacement signal. Simulation experiments confirm the efficacy of VAD algorithm in achieving efficient linear phase demodulation under IQ mismatch and time-varying dc offset, surpassing the performance of existing linear demodulation algorithms. Subsequently, based on the demodulated differential displacement signal, we develop a DCG-based QRS and T wave (DCG-RT) detector to enhance the characteristic waveforms corresponding to QRS- and T-wave for automatic cardiac timing like QRS-wave to QRS-wave (RR) interval and QRS-wave to T-wave (RT) interval calculation. This algorithm achieves easily identifiable cardiac feature waveforms with minimal computational resources. Using a 24-GHz Doppler radar and medical device, the synchronous acquisition experiments were conducted on five subjects. The comparative analysis of the enhanced signals extracted by the algorithm with PCG, ECG, and other signals reveals a remarkable 98% accuracy in cardiac timing detection.
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ISSN:0018-9480
1557-9670
DOI:10.1109/TMTT.2024.3360469