The quest for raw signals: a quality review of publicly available photoplethysmography datasets
Abstract
Photoplethysmography is an optical measurement principle which is present in most modern wearable devices such as fitness trackers and smartwatches. As the analysis of physiological signals requires reliable but energy-efficient algorithms, suitable datasets are essential for their development, evaluation, and benchmark. A broad variety of clinical datasets is available with recordings from medical pulse oximeters which traditionally apply transmission mode photoplethysmography at the fingertip or earlobe. However, only few publicly available datasets utilize recent reflective mode sensors which are typically worn at the wrist and whose signals show different characteristics. Moreover, the recordings are often advertised as raw, but then turn out to be preprocessed and filtered while the applied parameters are not stated. In this way, the heart rate and its variability can be extracted, but interesting secondary information from the non-stationary signal is often lost. Consequently, the test of novel signal processing approaches for wearable devices usually implies the gathering of own or the use of inappropriate data.
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There is high variance in PPG signal quality across different devices, such that a device-specific consideration seems appropriate.
“Naturally, the signal quality of PPG data in general is often discussed in other work as it is highly susceptible to motion artifacts57, however, there is also a high variance in PPG signal quality across different devices67, such that a device-specific consideration seems appropriate.”
From Data quality evaluation in wearable monitoring (2022) · cites this paper as [67]
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Data quality evaluation in wearable monitoring
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Self-citation
- Authors
- Wolling, F., & Van Laerhoven, K.
- Affiliations
- University of Siegen (DE)
- University of Siegen, Siegen, Germany
- ORCID
- Wolling, Florian
- Venue
- Proceedings of the Third Workshop on Data: Acquisition To Analysis
- Publisher
- ACM
- Published
- 2020-11-16
- Pages
- 14-19
- OpenAlex
- W3097572050
- Cited by
- 9
- References
- 34
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 1 · 2022: 2 · 2021: 2
- FWCI
- 2.27
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Workshop on Data: Acquisition To Analysis (DATA) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- photoplethysmography, wearable devices, pulse oximetry, heart rate variability, signal preprocessing, wrist-worn sensors, physiological signal analysis, energy-efficient algorithms
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