Validating Measures of Electrodermal Activity and Heart Rate Variability Derived From the Empatica E4 Utilized in Research Settings That Involve Interactive Dyadic States

Frontiers in Behavioral Neuroscience

Nir Milstein¹  Ilanit Gordon² 

[1] Department of Psychology, Bar-Ilan University, Ramat Gan, Israel;The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel;

关键词: Empatica E4;    MindWare mobile impedance cardiograph;    interbeat intervals;    heart rate variability;    electro-dermal activity;    dyadic research;   

DOI  :  10.3389/fnbeh.2020.00148

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown