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Cited by 141Heart Rate Variability and Autonomic ControlSleep and related disordersNon-Invasive Vital Sign Monitoring

Quantitative analysis of wrist electrodermal activity during sleep

Open access
Sano, Akane, Picard, Rosalind W., Stickgold, Robert·2014·International Journal of Psychophysiology
DOI 10.1016/j.ijpsycho.2014.09.011PMC PMC4335672
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Abstract

We present the first quantitative characterization of electrodermal activity (EDA) patterns on the wrists of healthy adults during sleep using dry electrodes. We compare the new results on the wrist to the prior findings on palmar or finger EDA by characterizing data measured from 80 nights of sleep consisting of 9 nights of wrist and palm EDA from 9 healthy adults sleeping at home, 56 nights of wrist and palm EDA from one healthy adult sleeping at home, and 15 nights of wrist EDA from 15 healthy adults in a sleep laboratory, with the latter compared to concurrent polysomnography. While high frequency patterns of EDA called "storms" were identified by eye in the 1960s, we systematically compare thresholds for automatically detecting EDA peaks and establish criteria for EDA storms. We found that more than 80% of the EDA peaks occurred in non-REM sleep, specifically during slow-wave sleep (SWS) and non-REM stage 2 sleep (NREM2). Also, EDA amplitude is higher in SWS than in other sleep stages. Longer EDA storms were more likely to occur in the first two quarters of sleep and during SWS and NREM2. We also found from the home studies (65 nights) that EDA levels were higher and the skin conductance peaks were larger and more frequent when measured on the wrist than when measured on the palm. These EDA high frequency peaks and high amplitude were sometimes associated with higher skin temperature, but more work is needed looking at neurological and other EDA elicitors in order to elucidate their complete behavior.

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Crossref · 10.1016/j.ijpsycho.2014.09.011

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  • SC reflects autonomic arousal during the day, providing a stress index during wakefulness.

    “SC reflects autonomic arousal during the day, providing a stress index during wakefulness; SC increases during sleep are highly likely to occur in either non-rapid eye movement (non-REM) stage 2 sleep or slow-wave sleep (SWS) [25].”

    From Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (2018) · cites this paper as [25]

    The Introduction (page not provided) says skin conductance measures sympathetic nervous system activity, and the Conclusion (page not provided) reports that about 80% of wrist EDA peaks occurred in SWS or NREM2 sleep. The paper does not establish skin conductance as a stress index during wakefulness; its measurements and findings concern sleep. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • SC increases during sleep are highly likely to occur in either non-REM stage 2 sleep or slow-wave sleep.

    “SC increases during sleep are highly likely to occur in either non-rapid eye movement (non-REM) stage 2 sleep or slow-wave sleep (SWS) [25].”

    From Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (2018) · cites this paper as [25]

  • One possible explanation of how low SC responses during sleep could be related to MCS scores is that there is a decrease in SWS in depression and other psychiatric disorders, and the largest SC responses during sleep are likely to occur during non-REM stage 2 and SWS.

    “One possible explanation of how low SC responses during sleep could be related to MCS scores is that there is a decrease in SWS in depression [60] and other psychiatric disorders [61], and the largest SC responses during sleep are likely to occur during non-REM stage 2 and SWS [25].”

    From Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study (2018) · cites this paper as [25]

  • Ambient artifacts include light artifacts interfering with the light of the PPG sensor, weather conditions such as high humidity which increases the moisture level of the skin surface and thus its conductivity, and coverage of the device for example by a blanket which increases the temperature and thereby potentially EDA levels.

    “Ambient artifacts are for example light artifacts interfering with the light of the PPG sensor43, weather conditions, such as high humidity which increases the moisture level of the skin surface and thus its conductivity44, as well as coverage of the device for example by a blanket which increases the temperature and thereby potentially EDA levels45.”

    From Data quality evaluation in wearable monitoring (2022) · cites this paper as [45]

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Research works printed but not linked: 1

  1. Van Dooren M de Vries JJGGJ Janssen JH 2012 Emotional sweating across the body: comparing 16 different skin conductance measurement locations Physiol Behav 106 298 304 22330325

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Authors
Sano, A., Picard, R. W., & Stickgold, R.
Affiliations
  • MIT Media Lab (US)
  • Beth Israel Deaconess Medical Center (US)
Corresponding author
Sano, Akane
ORCID
Venue
International Journal of Psychophysiology
Publisher
Elsevier BV
Published
2014-12
Volume
94
Issue
3
Pages
382-389
ISSN
0167-8760 (ISSN-L)
DOI
10.1016/j.ijpsycho.2014.09.011
PMC
PMC4335672
OpenAlex
W2087592512
Cited by
141
References
35
Citations by year
2026: 6 · 2025: 4 · 2024: 12 · 2023: 11 · 2022: 18 · 2021: 15 · 2020: 18 · 2019: 14 · 2018: 12 · 2017: 12 · 2016: 9 · 2015: 10
FWCI
7.08
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • International Journal of Psychophysiology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-nd)
  • PMC
Funders
  • MIT Media Lab Consortium
  • Samsung Electronics
  • NIH (1R01GM105018-01)
Topics
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
Keywords
electrodermal activity, wrist, skin conductance, sleep, slow-wave sleep, NREM sleep, dry electrodes, skin temperature, home sleep monitoring, polysomnography comparison
MeSH terms
Adolescent, Adult, Female, Galvanic Skin Response, Humans, Longitudinal Studies, Male, Microelectrodes, Sleep Stages, Wrist, Polysomnography, Young Adult, Wireless Technology

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