HeartPy: A novel heart rate algorithm for the analysis of noisy signals

Research output: Contribution to journalArticleScientificpeer-review

12 Downloads (Pure)

Abstract

Heart rate data are often collected in human factors studies, including those into vehicle automation. Advances in open hardware platforms and off-the-shelf photoplethysmogram (PPG) sensors allow the non-intrusive collection of heart rate data at very low cost. However, the signal is not trivial to analyse, since the morphology of PPG waveforms differs from electrocardiogram (ECG) waveforms and shows different noise patterns. Few validated open source available algorithms exist that handle PPG data well, as most of these algorithms are specifically designed for ECG data.

In this paper we present the validation of a novel algorithm named HeartPy, useful for the analysis of heart rate data collected in noisy settings, such as when driving a car or when in a simulator. We benchmark the performance on two types of datasets and show that the developed algorithm performs well. Further research steps are discussed.
Original languageEnglish
Pages (from-to)368-378
Number of pages11
JournalTransportation Research Part F: Traffic Psychology and Behaviour
Volume66
DOIs
Publication statusPublished - 2019

Keywords

  • Heart rate analysis
  • Human factors
  • Open source
  • Physiological signals
  • Signal analysis

Fingerprint Dive into the research topics of 'HeartPy: A novel heart rate algorithm for the analysis of noisy signals'. Together they form a unique fingerprint.

  • Cite this