On the Minimal Adequate Sampling Frequency of the Photoplethysmogram for Pulse Rate Monitoring and Heart Rate Variability Analysis in Mobile and Wearable Technology
Author:
Béres Szabolcs1, Holczer Lőrinc1, Hejjel László1
Affiliation:
1. Heart Institute, Medical Faculty , University of Pécs , Ifjúság str., 13, H-7624 , Pécs , Hungary
Abstract
Abstract
Recently there has been great interest in photoplethysmogram signal processing. However, its minimally necessary sampling frequency for accurate heart rate variability parameters is ambiguous. In the present paper frequency-modulated 1.067 Hz cosine wave modelled the variable PPG in silico. The five-minute-long, 1 ms resolution master-signals were decimated (D) at 2-500 ms, then cubic spline interpolated (I) back to 1 ms resolution. The mean pulse rate, standard deviation, root mean square of successive pulse rate differences (RMSSD), and spectral components were computed by Varian 2.3 and compared to the master-series via relative accuracy error. Also Poincaré-plot morphology was assessed. Mean pulse rate is accurate down to 303 ms (D) and 400 ms (I). In low-variability series standard deviation required at least 5 ms (D) and 100 ms (I). RMSSD needed 10 ms (D), and 303 ms (I) in normal, whereas 2 ms (D) and 100 ms (I) in low- variability series. In the frequency domain 5 ms (D) and 100 ms (I) are required. 2 ms (D) and 100 ms (I) preserved the Poincaré-plot morphology. The minimal sampling frequency of PPG for accurate HRV analysis is higher than expected from the signal bandwidth and sampling theorem. Interpolation improves accuracy. The ratio of sampling error and expected variability should be considered besides the inherent sensitivity of the given parameter, the interpolation technique, and the pulse rate detection method.
Publisher
Walter de Gruyter GmbH
Subject
Instrumentation,Biomedical Engineering,Control and Systems Engineering
Reference31 articles.
1. [1] Bunn, J.A., Navalta, J.W, Fountaine, C.J., Reece, J.D. (2018). Current state of commercial wearable technology in physical activity monitoring 2015-2017. International Journal of Exercise Science, 11 (7), 503-515. 2. [2] Liu, Y., Wang, H., Zhao, W., Zhang, M., Qin, H., Xie, Y. (2018). Flexible, stretchable sensors for wearable health monitoring: Sensing mechanisms, materials, fabrication strategies and features. Sensors (Basel), 18 (2), 645.10.3390/s18020645 3. [3] Kumar, A., Komaragiri, R., Kumar, M. (2018). From pacemaker to wearable: Techniques for ECG detection systems. Journal of Medical Systems, 42 (2), 34.10.1007/s10916-017-0886-1 4. [4] Pinheiro, E., Postolache, O. (2008). A wireless monitoring system for health care applications. In The Sixth IASTED International Conference on Biomedical Engineering, 13-15 February 2008, Innsbruck, Austria. Acta Press, 372-377. 5. [5] Pollonini, L., Rajan, N.O., Xu, S., Madala, S., Dacso, C.C. (2010). A novel handheld device for use in remote patient monitoring of heart failure patients—design and preliminary validation on healthy subjects. Journal of Medical Systems, 36 (2), 653-659.
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