Heart rate data are collected often in human factors studies. Advances in open hardware platforms and offtheshelf photoplethysmogram (PPG) sensors allow the nonintrusive 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. PPG is often preferable because it can be collected less intrusively. However, few validated open source available algorithms exist that handle PPG data well, as most of these algorithms are specifically designed for ECG data. We have developed a novel algorithm specifically for PPG data collected in noisy fieldor simulatorbased settings. The main aim of this paper is to present the validation of a novel algorithm on a PPG dataset collected in a recent driving simulator experiment. The dataset was manually annotated, and performance of the algorithm compared to two other popular open source available algorithms. We show that the algorithm performs well and displays superior performance on the PPG dataset. Implications and further steps are discussed.
Original languageEnglish
Title of host publicationProceedings of
Subtitle of host publicationThe 6th HUMMANIST Conference, June 13 and 14, 2018, The Hague, NL
EditorsNicole Van Nes , Charlotte Voegelé
Place of Publication Lyon
PublisherHUMANIST publications
Number of pages6
ISBN (Print) 978-2-9531712-5-9
Publication statusPublished - 2018
Event6th Humanist Conference - The Hague, Netherlands
Duration: 13 Jun 201814 Jun 2018
Conference number: 6


Conference6th Humanist Conference
CityThe Hague
Internet address

    Research areas

  • Human factors, heart rate analysis, physiological signals, signal analysis, open source

ID: 45761926