Abstract
This paper describes the functioning and development of a heart rate analysis toolkit 20 designed for photoplethysmogram (PPG) data. Most openly available algorithms 21 focus on electrocardiogram (ECG) data, which has very different signal properties 22 and morphology, creating a problem with analysis. ECG-based algorithms generally 23 don’t function well on PPG data, especially noisy PPG data collected in experimental 24 studies. To counter this, we developed a noise-resistant algorithm that handles PPG 25 data well. It has been implemented in Python and C. Arduino IDE sketches for 26 popular boards (Arduino, Teensy) are available. This provides both pc-based and 27 wearable implementations of the software, which allows rapid reuse by researchers 28 looking for a validated heart rate analysis toolkit for use in human factors studies.
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