2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2016
DOI: 10.1109/embc.2016.7591347
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Can PPG be used for HRV analysis?

Abstract: Heart rate variability (HRV) represents one of the most promising markers of the autonomic nervous system (ANS) regulation. However, it requires the acquisition of the ECG signal in order to reliably detect the RR intervals, which is not always easily and comfortably available in personal health applications. Additionally, due to progress in single spot optical sensors, photoplethysmography (PPG) is an interesting alternative for heartbeat interval measurements, since it is a more convenient and a less intrusi… Show more

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Cited by 114 publications
(83 citation statements)
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“…As such, PPG can be used to measure HR without the need for an ECG device. Furthermore, the HR derived from the PPG signal can be used in a series of calculations to determine the heart rate variability (HRV) [9]. …”
Section: Introductionmentioning
confidence: 99%
“…As such, PPG can be used to measure HR without the need for an ECG device. Furthermore, the HR derived from the PPG signal can be used in a series of calculations to determine the heart rate variability (HRV) [9]. …”
Section: Introductionmentioning
confidence: 99%
“…Finger tips have also been used as a measuring site but only in stationary conditions: it has been shown that HRV derived from fi ngertip PPG had an excellent correlation to ECG in stationary conditions. 38 However, a comparative study of fi nger derived PRV and HRV in healthy subjects 40 using a stationary equipment found a poor correlation and suggested that fi nger derived PRV might not be suitable to substitute ECG derived HRV, as has been mentioned by other authors, too 41 .…”
Section: Hrv Fundamentalsmentioning
confidence: 95%
“…Brandenberger, 2004). Pulse-rate variability via photoplethysmography (PPG) recordings at the wrist has been demonstrated to be a valid method for measurement of R-R intervals via electrocardiogram whilst at rest (Bolanos, Nazeran, & Haltiwanger, 2006;Lu, Yang, Taylor, & Stein, 2009;Pinheiro et al, 2016). (2017).…”
Section: Sleep and Recovery Assessmentmentioning
confidence: 99%