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Validating Measures of Electrodermal Activity and Heart Rate Variability Derived From the Empatica E4 Utilized in Research Settings That Involve Interactive Dyadic States
Open accessAbstract
Portable and wireless devices that collect physiological data are becoming more and more sought after in clinical and psychophysiological research as technology swiftly advances. These devices allow for data collection in interactive states, such as dyadic therapy, with reduced restraints compared to traditional laboratory devices. One such portable device is the Empatica E4 wristband (Empatica Srl, Milan, Italy) which allows quantifying cardiac interbeat intervals (IBIs), heart rate variability (HRV), and electro-dermal activity (EDA), as well as several other acceleration and temperature measures. In the current study, we aimed to assess IBI, HRV, and EDA measures, against the same data collected from the well-validated MindWare mobile impedance cardiograph device (MindWare Technology, Gahanna, OH, United States). We assessed the E4 strictly as a research instrument and not as a clinical tool. We were specifically interested in the wristbands' performance during naturalistic interactive face-to-face conversations which inherently involve more hand movements. We collected data from 30 participants, nested in 15 dyads, which were connected to both devices simultaneously, during rest and during a social conversation. After preprocessing and analyses, we found that mean IBIs obtained by the E4 and the MindWare device, were highly similar during rest and during conversation. Medium to high correlations were found between the devices with respect to several HRV measures, with higher correlations during rest compared to conversation. The E4 failed to produce reliable EDA data. We conclude by discussing the strengths and limitations of the E4 during seated conversational states and suggest optimal ways to collect and analyze data with the E4.
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“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 [42]
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“…a research-grade wearable device commonly used in ambulatory settings to record blood volume pulse (BVP), electrodermal activity (EDA), skin temperature (TEMP), and triaxial acceleration, together with heart rate (HR) estimates derived from the photoplethysmography (PPG)-based BVP signal [19,20].”
Thapa, S., & Sarkar, A. (2026) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv66570.2026.11623989
McNaboe, R. Q., Díaz, L. R. M., Faremi, B. E., & Posada-Quintero, H. F. (2026) · Signals · doi:10.3390/signals7040073
Xu, R., Cao, S., Barnett‐Cowan, M., Bülbül, G. B., Kearns, S. K., & Niechwiej‐Szwedo, E. (2026) · Frontiers in Neuroergonomics · doi:10.3389/fnrgo.2026.1911259
“…rows, and treat the frontal band powers as the device-level estimates that comparable consumer-EEG studies have validated (Krigolson et al., 2017; Cannard et al., 2021; Milstein and Gordon, 2020); dry frontal electrodes in a moving cockpit may nonetheless retain some non-neural contribution.”
Jiang, W., Mao, J., Quan, Z., Zhao, J., Xu, D., Long, Y., & Song, X. (2026) · Applied Spatial Analysis and Policy · doi:10.1007/s12061-026-09999-6
“Empatica E4 is easy to operate and has been applied in many studies (Campanella et al., 2023; Milstein & Gordon, 2020).”
Baquerizo-Sedano, M., Pedrazo, M. L., Martínez, M. M., Taype-Rondán, Á., Gómez, J. L. C., & Manzanares, M. C. S. (2026) · Healthcare · doi:10.3390/healthcare14182990
Valenzuela‐Pascual, C., Garriga, M., Borràs, R., Voltà-Solerdelcoll, R., Korniyenko, M., Mas, A., Escala, C., de Looff, P. C., Anmella, G., Benabarre, A., et al. (2026) · JMIR Mental Health · doi:10.2196/94737
“Wearable technologies enable continuous and real-world monitoring of digital biosignals such as electrodermal activity (EDA) and heart rate (HR), which have been proposed as potential digital biomarkers [5, 6].”
Haim, A., Thirion, A., Mulliez, B., Zhou, Y., Hahn, J. O., & Tap, H. (2026) · IEEE International Instrumentation and Measurement Technology Conference · doi:10.1109/i2mtc66907.2026.11694399
Em, P. P., & Teoh, T. S. (2026) · Sensors · doi:10.3390/s26196202
“The Empatica E4 wristband, which shares sensor hardware with the newer EmbracePlus, has been validated against research-grade equipment for electrodermal activity [69–71], cardiac and electrodermal measures jointly [72], and EDA/HRV in interactive settings [73].”
Next‐Generation Brain Health Monitoring Enabled by Integrated Wearable AI Infrastructure
Masrur, M. A., Khan, B., Khalid, R. T., Sumaira, & Abdullah, S. (2026) · Smart Medicine · doi:10.1002/smmd.70053
Metadata
- Authors
- Milstein, N., & Gordon, I.
- Affiliations
- Bar-Ilan University (IL)
- Corresponding author
- Gordon, Ilanit
- Venue
- Frontiers in Behavioral Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2020-08-18
- Volume
- 14
- Pages
- 148-148
- ISSN
- 1662-5153 (ISSN-L)
- OpenAlex
- W3058974884
- Cited by
- 180
- References
- 43
- Citations by year
- 2026: 28 · 2025: 29 · 2024: 32 · 2023: 44 · 2022: 29 · 2021: 17 · 2020: 1
- FWCI
- 14.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Behavioral Neuroscience (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Israel Science Foundation
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- Empatica E4, electrodermal activity, heart rate variability, RR interval, device validation, dyadic therapy, face-to-face communication, naturalistic interaction, psychophysiological measurement, measurement reliability
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