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Photoplethysmography sampling frequency: pilot assessment of how low can we go to analyze pulse rate variability with reliability?
Open accessAbstract
Pulse rate variability (PRV) analysis appears as the first alternative to heart rate variability analysis for wearable devices; however, there is a constraint on computational load and energy consumption for the limited system resources available to the devices. Considering that adjustment of the sampling frequency is one of the strategies for reducing computational load and power consumption, this study aimed to investigate the influence of sampling frequency ( f s ) on PRV analysis and to find the minimum sampling frequency while maintaining reliability. We generated 5000, 2500, 1000, 500, 250, 100, 50, 25, 20, 15, 10, 5 Hz down-sampled photoplethysmograms from 10 kHz-sampled PPGs and derived time- and frequency-domain variables of the PRV. These included AVNN, SDNN, SDSD, RMSSD, NN50, pNN50, total power, VLF, LF, HF, LF/HF, nLF and nHF for each down-sampled signal. Derived variables were compared with heart rate variability of the 10 kHz-sampled electrocardiograms, and then statistically investigated using one-way ANOVA test and Bland–Altman analysis. As a result, significant differences ( P < 0.05) were found for SDNN, SDSD, RMSSD, NN50, pNN50, TP, HF, LF/HF, nLF and nHF, but not for AVNN, VLF and LF. Based on the post hoc tests, it was found that the NN50 and pNN50, SDSD and RMSSD, LF/HF and nHF, SDNN, TP and nLF analysis had significant differences at f s ⩽ 20 Hz, f s ⩽ 15 Hz, f s ⩽10 Hz; f s = 5 Hz, respectively. In other words, a significant difference was not seen for any variable if the f s was greater than 25 Hz. Consequently, our pilot study suggests that analysis of variability in the time and frequency domain from pulse rate obtained through PPG may be potentially as reliable as that derived from the analysis of the electrocardiogram, provided that f s ⩾25 Hz sampling frequency is used.
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“Rapid irregularly conducted AF may produce variable pulse pressures that challenge detection (Choi 2017).”
From 2021 ISHNE/HRS/EHRA/APHRS Expert Collaborative Statement on mHealth in Arrhythmia Management: Digital Medical Tools for Heart Rhythm Professionals: From the International Society for Holter and Noninvasive Electrocardiology/Heart Rhythm Society/European Heart Rhythm Association/Asia-Pacific Heart Rhythm Society (2021) · cites this paper as Choi 2017
Experimental — accuracy not yet measuredIn the citing paper
“Second, the PPG can be interpolated to increase performance [130], [131].”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [130]
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“First, the PPG sampling rate should be sufficiently high (at least 25 Hz [130]).”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [130]
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Reducing Pulse Rate Variability Computational Error from a 30 Hz Photoplethysmography Recording
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Estimating heart rate variability using facial video photoplethysmography: a pilot validation study
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Metadata
- Authors
- Choi, A., & Shin, H.
- Affiliations
- Gachon University (KR)
- Chonnam National University (KR)
- Corresponding author
- Choi, A
- Shin, H
- Venue
- Physiological Measurement
- Publisher
- IOP Publishing
- Published
- 2017-02-23
- Volume
- 38
- Issue
- 3
- Pages
- 586-600
- ISSN
- 0967-3334 (ISSN-L)
- 1361-6579
- OpenAlex
- W2586184806
- Cited by
- 116
- References
- 25
- Citations by year
- 2026: 8 · 2025: 5 · 2024: 8 · 2023: 12 · 2022: 23 · 2021: 24 · 2020: 14 · 2019: 11 · 2018: 6 · 2017: 5
- FWCI
- 4.44
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Physiological Measurement (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Ministry of Science, ICT & Future Planning (NRF-2015R1C1A1A02036535)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- photoplethysmography, pulse rate variability, sampling frequency, downsampling, wearable devices, heart rate variability, signal reliability, power consumption, computational load, time and frequency domain analysis, electrocardiogram comparison
- MeSH terms
- Female, Heart Rate, Humans, Male, Pilot Projects, Signal Processing, Computer-Assisted, Photoplethysmography, Young Adult
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