Wearable pulse monitoring system for evaluating cardiovascular parameters based on tapered no-core fiber

We developed a highly sensitive tapered no-core fiber (TNCF)-based cardiovascular monitoring system featuring a glycerol-filled polydimethylsiloxane (PDMS) sac design that minimizes alignment errors. The system achieves 0.339 dB/kPa vibration sensitivity, 0.17 kPa resolution, and 6.1/6.4 ms response/recovery times while maintaining excellent stability. It enables comprehensive vascular health assessment through: 1) pulse wave velocity measurement via synchronized chest-wrist waveform acquisition, 2) heart rate monitoring during rest/exercise, and 3) blood pressure prediction using random forest regression. The regression model is evaluated as follows: correlation coefficients of 0.95 and 0.94 for systolic blood pressure and diastolic blood pressure, mean absolute relative differences of 1.45% and 1.49%, and errors of 0.41 ± 1.98 mmHg and 0.08 ± 1.44 mmHg, respectively, compared with standard sphygmomanometric measurements.

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Publication Details

Journal
Optics Letters
Published
2025-07-14
DOI
https://doi.org/10.1364/ol.570612
Citations
1
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.67

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article

Wearable pulse monitoring system for evaluating cardiovascular parameters based on tapered no-core fiber

Yijie Lv, Honglian Guo, Min Lv, Lei Meng et al.
1 citations
Optics Letters
Non-Invasive Vital Sign Monitoring
0.67
article

Wearable pulse monitoring system for evaluating cardiovascular parameters based on tapered no-core fiber

Yijie Lv, Honglian Guo, Min Lv, Lei Meng, Wei Peng, Chuanbo Li, Qian Wen
article en
1 citations

Abstract

We developed a highly sensitive tapered no-core fiber (TNCF)-based cardiovascular monitoring system featuring a glycerol-filled polydimethylsiloxane (PDMS) sac design that minimizes alignment errors. The system achieves 0.339 dB/kPa vibration sensitivity, 0.17 kPa resolution, and 6.1/6.4 ms response/recovery times while maintaining excellent stability. It enables comprehensive vascular health assessment through: 1) pulse wave velocity measurement via synchronized chest-wrist waveform acquisition, 2) heart rate monitoring during rest/exercise, and 3) blood pressure prediction using random forest regression. The regression model is evaluated as follows: correlation coefficients of 0.95 and 0.94 for systolic blood pressure and diastolic blood pressure, mean absolute relative differences of 1.45% and 1.49%, and errors of 0.41 ± 1.98 mmHg and 0.08 ± 1.44 mmHg, respectively, compared with standard sphygmomanometric measurements.

Optics LettersVol. 50(16)
Minzu University of China (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 29%
Non-Invasive Vital Sign Monitoring
0.67
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