Validation of the Empatica E4 wristband
Abstract
A preliminary study into the signal quality of the Empatica's E4 portable photoplethysmogram device as validation for further research on using the device to detect the heart arrhythmia atrial fibrillation. In order to pursue this research, it was necessary to verify the quality of the data produced by the E4 device against a device currently used by clinicians to detect atrial fibrillation. This was done by having healthy volunteers wear both the Empatica E4 and the clinician standard device while following standard clinician procedure for atrial fibrillation diagnosis. The device was compared qualitatively against General Electric's SEER Light Extend Recorder holter portable electrocardiogram. The analysis was done by non-experts at varying academic levels. The primary reviewer's results showed similar data quality between both devices 85% of the time and the holter performed better 5% of the time.
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HRV time-domain metrics from the Empatica device have been validated against ECG in previous studies.
“HRV time-domain metrics from the Empatica device have been validated against ECG in previous studies.58–60”
From Investigating sources of inaccuracy in wearable optical heart rate sensors (2020) · cites this paper as [59]
The Empatica E4 is a research-grade wearable device capable of recording accelerometry (ACC), electrodermal activity (EDA), photoplethysmography (PPG), and skin temperature (TEMP) signals.
“The Empatica E4 (Empatica Inc, Boston, MA, USA) is a research-grade wearable device capable of recording accelerometry (ACC), electrodermal activity (EDA), photoplethysmography (PPG), and skin temperature (TEMP) signals24”
From Data quality evaluation in wearable monitoring (2022) · cites this paper as [24]
A complete loss of contact results in a 0-line for the EDA signal; motion artifacts without contact loss result in abrupt level changes or high amplitude fluctuations; and PPG shows considerable deviation from expected signal patterns.
“While a complete loss of contact results in a 0-line for the EDA signal, motion artifacts without contact loss result in abrupt level changes or high amplitude fluctuations, and PPG shows considerable deviation from expected signal patterns24,42.”
From Data quality evaluation in wearable monitoring (2022) · cites this paper as [24]
Cites
Secondary Peak Detection of PPG Signal for Continuous Cuffless Arterial Blood Pressure Measurement
He, X., Goubran, R. A., & Liu, X. P. (2014) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2014.2299524 · Cited by 146 · see citing works
Cohen, M. C., & Naccarelli, G. V. (2008) · Journal of Cardiovascular Electrophysiology · doi:10.1111/j.1540-8167.2008.01134.x · Cited by 29 · see citing works
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Investigating sources of inaccuracy in wearable optical heart rate sensors
Bent, B., Goldstein, B. A., Kibbe, W. A., & Dunn, J. P. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0226-6 · Cited by 673 · see citing works
Qiu, S., Zhao, H., Jiang, N., Wang, Z., Liu, L., An, Y., Zhao, H., Miao, X., Liu, R., & Fortino, G. (2022) · Information Fusion · doi:10.1016/j.inffus.2021.11.006 · Cited by 671 · see citing works
Wearable Photoplethysmography for Cardiovascular Monitoring
Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3149785 · Cited by 250 · see citing works
Milstein, N., & Gordon, I. (2020) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2020.00148 · Cited by 180 · see citing works
Stressing the accuracy: Wrist‐worn wearable sensor validation over different conditions
Menghini, L., Gianfranchi, E., Cellini, N., Patron, E., Tagliabue, M., & Sarlo, M. (2019) · Psychophysiology · doi:10.1111/psyp.13441 · Cited by 157 · see citing works
Taj-Eldin, M., Ryan, C., O’Flynn, B., & Galvin, P. (2018) · Sensors · doi:10.3390/s18124271 · Cited by 142 · see citing works
Data quality evaluation in wearable monitoring
Böttcher, S., Vieluf, S., Bruno, E., Joseph, B., Epitashvili, N., Biondi, A., Zabler, N., Glasstetter, M., Dümpelmann, M., Van Laerhoven, K., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-25949-x · Cited by 91 · see citing works
Evaluation of the signal quality of wrist-based photoplethysmography
Pradhan, N., Rajan, S., & Adler, A. (2019) · Physiological Measurement · doi:10.1088/1361-6579/ab225a · Cited by 50 · see citing works
Self-citationStress Monitoring System for Individuals with Autism Spectrum Disorders
Tomczak, M. T., Wojcikowski, M., Pankiewicz, B., Lubinski, J., Majchrowicz, J., Majchrowicz, D., Walasiewicz, A., Kilinski, T., & Szczerska, M. (2020) · IEEE Access · doi:10.1109/access.2020.3045633 · Cited by 50 · see citing works
Evaluating the accuracy of heart rate sensors based on photoplethysmography for in-the-wild analysis
Barrios, L., Oldrati, P., Santini, S., & Lutterotti, A. (2019) · Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare · doi:10.1145/3329189.3329215 · Cited by 43 · see citing works
Tomczak, M. T., Wójcikowski, M., Listewnik, P., Pankiewicz, B., Majchrowicz, D., & Jędrzejewska-Szczerska, M. (2018) · Sensors · doi:10.3390/s18103530 · Cited by 29 · see citing works
An investigation into the effectiveness of using acoustic touch to assist people who are blind
Zhu, H. Y., Hossain, S. N., Jin, C., Singh, A. K., Nguyen, M. T. D., Deverell, L., Nguyen, V., Gates, F. S., Fernandez, I. G., Melencio, M. V., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0290431 · Cited by 16 · see citing works
- Authors
- McCarthy, C., Pradhan, N., Redpath, C., & Adler, A.
- Affiliations
- Carleton University (CA)
- Ottawa Heart Institute (CA)
- Venue
- 2016 IEEE EMBS International Student Conference (ISC)
- Publisher
- IEEE
- Published
- 2016-05
- Pages
- 1-4
- OpenAlex
- W2465675980
- Cited by
- 235
- References
- 2
- Citations by year
- 2026: 13 · 2025: 20 · 2024: 31 · 2023: 38 · 2022: 22 · 2021: 26 · 2020: 34 · 2019: 31 · 2018: 14 · 2017: 4 · 2016: 1 · 2014: 1
- FWCI
- 33.35
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE EMBS International Student Conference (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Keywords
- Empatica E4, photoplethysmography, atrial fibrillation detection, wearable devices, device validation, signal quality, Holter electrocardiogram
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