Speckleplethysmographic (SPG) estimation of heart rate variability
June 2-6, 2019
Heart rate variability (HRV), a class of metrics derived from variability in R-R intervals typically measured using electrocardiography (ECG), has implications for cardiovascular and neurological health1. Recently, HRV was used to track the recovery of athletes after exercise training due to its ability to noninvasively monitor the autonomic nervous system (ANS)2. Exercise training generally has a positive impact on the ANS by reducing resting heart rate and increasing cardiac vagal tone at rest3. However, overexertion from excessive workout sessions can counteract the benefits of regular exercise and reduce HRV4.
Unfortunately, routine, remote ECG HRV monitoring is limited due to portability, cost, and loss of accuracy. Various groups have attempted to address the limitations of ECG monitored HRV by estimating HRV with simpler photoplethysmography (PPG) technology5. Transmittance PPG, the signal used in pulse oximetry, measures changes in intensity due to light absorption caused by the dilation and constriction of arteries and arterioles in the finger due to pulsatile blood flow. Alas, HRV approximated from PPG finger measurements loses accuracy due to significant peak time delays related to various factors such as arterial stiffness, vascular tone, and height6.
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Cody E. Dunn; Derek C. Monroe,; Christian Crouzet; James W. Hicks; and Bernard Choi, "Speckleplethysmographic (SPG) estimation of heart rate variability" in "Advances in Optics for Biotechnology, Medicine and Surgery XVI", Erin Buckley, Emory University/Georgia Institute of Technology, USA Christophe Moser, Polytechnique Fédérale de Lausanne (EPFL), Switzerland Brian Pogue, Dartmouth College, USA David Sampson, University of Western Australia, Australia Eds, ECI Symposium Series, (2019). https://dc.engconfintl.org/biotech_med_xvi/21