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Methods Inf Med 2016; 55(05): 463-472
DOI: 10.3414/ME16-01-0026
Original Articles
Schattauer GmbH

Optimizing Estimates of Instantaneous Heart Rate from Pulse Wave Signals with the Synchrosqueezing Transform

Hau-Tieng Wu
1   Department of Mathematics, University of Toronto, Toronto, Ontario, Canada
,
Gregory F. Lewis
2   Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
,
Maria I. Davila
2   Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
,
Ingrid Daubechies
3   Department of Mathematics and the Information Initiative at Duke, Duke University, Durham, NC, USA
,
Stephen W. Porges
2   Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
4   Kinsey Institute, Indiana University, Bloomington, IN, USA
› Author Affiliations FundingsData collection and further development of the PhysioCam supported by DARPA contract number W911NF-14–1–0158. Hau-tieng Wu’s research is partially supported by Sloan Research Fellow FR-2015–65363.
Further Information

Publication History

Received 02 March 2016

Accepted in revised form: 16 June 2016

Publication Date:
08 January 2018 (online)

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Summary

Background: With recent advances in sensor and computer technologies, the ability to monitor peripheral pulse activity is no longer limited to the laboratory and clinic. Now inexpensive sensors, which interface with smartphones or other computer-based devices, are expanding into the consumer market. When appropriate algorithms are applied, these new technologies enable ambulatory monitoring of dynamic physiological responses outside the clinic in a variety of applications including monitoring fatigue, health, workload, fitness, and rehabilitation. Several of these applications rely upon meas -ures derived from peripheral pulse waves measured via contact or non-contact pho -toplethysmography (PPG). As technologies move from contact to non-contact PPG, there are new challenges. The technology neces sary to estimate average heart rate over a few seconds from a noncontact PPG is available. However, a technology to precisely measure instantaneous heat rate (IHR) from non-contact sensors, on a beat-to-beat basis, is more challenging. Objectives: The objective of this paper is to develop an algorithm with the ability to accurately monitor IHR from peripheral pulse waves, which provides an opportunity to measure the neural regulation of the heart from the beat-to-beat heart rate pattern (i.e., heart rate variability). Methods: The adaptive harmonic model is applied to model the contact or non-contact PPG signals, and a new methodology, the Synchrosqueezing Transform (SST), is applied to extract IHR. The body sway rhythm inherited in the non-contact PPG signal is modeled and handled by the notion of wave-shape function. Results: The SST optimizes the extraction of IHR from the PPG signals and the technique functions well even during periods of poor signal to noise. We contrast the contact and non-contact indices of PPG derived heart rate with a criterion electrocardiogram (ECG). ECG and PPG signals were monitored in 21 healthy subjects performing tasks with different physical demands. The root mean square error of IHR estimated by SST is significantly better than commonly applied methods such as autoregressive (AR) method. In the walking situation, while AR method fails, SST still provides a reasonably good result. Conclusions: The SST processed PPG data provided an accurate estimate of the ECG derived IHR and consistently performed better than commonly applied methods such as autoregressive method.

Keywords

Instantaneous heart rate - synchrosqueezing transform - heart rate variability - PhysioCam - photoplethysmography
 

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