Contactless Arrhythmia Detection and Short-Term HRV Analysis Based on a Fiber Optic Sensor

Accurate detection of premature atrial contractions (PACs) is crucial for identifying life-threatening arrhythmias. Traditional electrocardiogram (ECG) devices, which require electrodes attached to the body, often cause discomfort and are unsuitable for long-term monitoring. This paper presents a non-contact ballistocardiogram (BCG) monitoring system utilizing a fiber optic sensor (FOS) for PAC identification and short-term heart rate variability (HRV) analysis. The system employs a Mach-Zehnder interferometer (MZI), which is simple and easy to replicate, consisting of only a 1×2 coupler and a 3×3 coupler. Tiny body vibrations caused by breathing and heartbeats lead to changes in the intensity of the interference light. By detecting these changes using three photodetectors (PDs), vital sign signals can be captured. To evaluate the robustness of the PAC detection algorithm, the study introduced fixed-speed breathing at two respiratory frequencies, increasing the range of interbeat interval (IBI) variations. The correlation coefficient between BCG-derived IBI and ECG-derived IBI in subjects with PAC was 0.9475. The proposed algorithm achieved an accuracy of 94.84% in PAC detection. Additionally, the time-domain and frequency-domain results of BCG-derived HRV and ECG-derived HRV showed high correlation at respiratory rates of 6 beats per minute (bpm) and 15 bpm. The FOS-based BCG signal not only accurately identifies PACs but also facilitates HRV analysis. This proposed system is suitable for long-term, non-contact vital sign monitoring in daily life.

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Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3602543
Citations
2
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
1.35

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article

Contactless Arrhythmia Detection and Short-Term HRV Analysis Based on a Fiber Optic Sensor

Weihao Yuan, Shuyang Chen, Qing Wang, Weimin Lyu et al.
2 citations
IEEE Transactions on Instrumentation and Measurement
Non-Invasive Vital Sign Monitoring
1.35
article

Contactless Arrhythmia Detection and Short-Term HRV Analysis Based on a Fiber Optic Sensor

Weihao Yuan, Shuyang Chen, Qing Wang, Weimin Lyu, Changyuan Yu, Yujian Li, Tianyu Chen
article en
2 citations

Abstract

Accurate detection of premature atrial contractions (PACs) is crucial for identifying life-threatening arrhythmias. Traditional electrocardiogram (ECG) devices, which require electrodes attached to the body, often cause discomfort and are unsuitable for long-term monitoring. This paper presents a non-contact ballistocardiogram (BCG) monitoring system utilizing a fiber optic sensor (FOS) for PAC identification and short-term heart rate variability (HRV) analysis. The system employs a Mach-Zehnder interferometer (MZI), which is simple and easy to replicate, consisting of only a 1×2 coupler and a 3×3 coupler. Tiny body vibrations caused by breathing and heartbeats lead to changes in the intensity of the interference light. By detecting these changes using three photodetectors (PDs), vital sign signals can be captured. To evaluate the robustness of the PAC detection algorithm, the study introduced fixed-speed breathing at two respiratory frequencies, increasing the range of interbeat interval (IBI) variations. The correlation coefficient between BCG-derived IBI and ECG-derived IBI in subjects with PAC was 0.9475. The proposed algorithm achieved an accuracy of 94.84% in PAC detection. Additionally, the time-domain and frequency-domain results of BCG-derived HRV and ECG-derived HRV showed high correlation at respiratory rates of 6 beats per minute (bpm) and 15 bpm. The FOS-based BCG signal not only accurately identifies PACs but also facilitates HRV analysis. This proposed system is suitable for long-term, non-contact vital sign monitoring in daily life.

IEEE Transactions on Instrumentation and MeasurementVol. 74
Hong Kong Polytechnic University (HK), Nanjing University of Aeronautics and Astronautics (CN)
National Natural Science Foundation of China, Hong Kong Polytechnic University
Openalex Percentile: Top 18%
Non-Invasive Vital Sign Monitoring
1.35
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