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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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Cites
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“As measuring HRV does not require particularly invasive testing, it is extensively acquired in psychological science and is considered a reliable estimate of autonomic nervous system modulation, via the vagus nerve, of sinus node cardiac activity (Blascovich et al., 2011; Kaufmann et al., 2011; Shaffer et al., 2014).”
BackgroundMethodInfluentialKARDIA: A Matlab software for the analysis of cardiac interbeat intervals
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“Scholars are calling for group physiological synchrony research, since groups are inherent part of our life, during the entire life span (Gordon et al., 2014).”
BackgroundSelf-citationAN OPEN SOURCE TOOL FOR HEART RATE VARIABILITY WAVELET-BASED SPECTRAL ANALYSIS
Martínez, C. A. G., Otero, A., Vila, X. A., & Lado, M. J. (2012) · International Conference on Bio-inspired Systems and Signal Processing · doi:10.5220/0003725002060211 · Cited by 3 · cited 1×
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Method
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Cited by
Sorted by citations
Vos, G., Trinh, K., Sarnyai, Z., & Azghadi, M. R. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.105026 · Cited by 200
“In [77], the authors found the Empatica E4 to be suitable for psychotherapy research focused on Inter-Beat Interval (IBI) and specific HRV measures, but failed to produce reliable EDA data and produced missing IBI data, especially when a subject is being more dynamic.”
BackgroundData 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
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“This device is certified as CE Medical class 2a [66] and has been validated in many works [67,68].”
Methodvan der Mee, D. J., Gevonden, M. J., Westerink, J. H. D. M., & de Geus, E. J. C. (2021) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2021.08.003 · Cited by 70
“14%), although both were modest in keeping with findings for SCL from previous studies (Milstein and Gordon, 2020; Menghini et al., 2019).”
MethodResultXue, T., Ali, A. E., Zhang, T., Ding, G., & Cesar, P. S. (2021) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2021.3124080 · Cited by 77
“(6) We captured participants’ physiological signals through the Empatica E4 wristband6 worn on the non-dominant hand [44], as shown in Fig.”
Background
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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