Analysing Noisy Driver Physiology Real-Time Using Off-the-Shelf Sensors

Title

Analysing Noisy Driver Physiology Real-Time Using Off-the-Shelf Sensors: Heart Rate Analysis Software from the Taking the Fast Lane Project.

 Author

van Gent, P. (TU Delft Transport and Planning) ORCID 0000-0002-8590-9533
Farah, H. (TU Delft Transport and Planning) ORCID 0000-0002-2919-0253
van Nes, N. (SWOV Institute for Road Safety Research)
van Arem, B. (TU Delft Transport and Planning) ORCID 0000-0001-8316-7794

 Date

2019

 Abstract

This paper describes the functioning and development of HeartPy: a heart rate analysis toolkit designed for photoplethysmogram (PPG) data. Most openly available algorithms focus on electrocardiogram (ECG) data, which has very different signal properties and morphology, creating a problem with analysis. ECG-based algorithms generally don’t function well on PPG data, especially noisy PPG data collected in experimental studies. To counter this, we developed HeartPy to be a noise-resistant algorithm that handles PPG data well. It has been implemented in Python and C. Arduino IDE sketches for popular boards (Arduino, Teensy) are available to enable data collection as well. This provides both pc-based and wearable implementations of the software, which allows rapid reuse by researchers looking for a validated heart rate analysis toolkit for use in human factors studies.

 Subject

Heart rate analysis
Human factors
PPG
Python
Arduino
OA-Fund TU Delft

 To reference this document use:

http://resolver.tudelft.nl/uuid:99d0b507-0575-4bf5-935b-c248b82e379e

 DOI

https://doi.org/10.5334/jors.241

 ISSN

2047-9647

 Source

Journal of Open Research Software, 7 (1), 1-9

 Part of collection

Institutional Repository

 Document type

journal article

 Rights

© 2019 P. van Gent, H. Farah, N. van Nes, B. van Arem
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