Quantitative analysis of wrist electrodermal activity during sleep - PubMed (original) (raw)

Quantitative analysis of wrist electrodermal activity during sleep

Akane Sano et al. Int J Psychophysiol. 2014 Dec.

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.

Keywords: Electrodermal activity; Galvanic skin response; Polysomnography; Qualitative analysis; Skin conductance; Skin temperature; Sleep.

Copyright © 2014 Elsevier B.V. All rights reserved.

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Figures

Fig. 1

Fig. 1

EDA peak detection (EDA amplitude and derivatives). The black asterisks show detected peaks and x shows a peak which is detected within 1 s after the previous one and counted as one peak.

Fig. 2

Fig. 2

2A: Filtered EDA data for one night in a healthy adult. 2B: detected EDA peaks in 30-s epochs. 2C: Zoom of region marked with a bar on 2A. 2D: # of EDA peaks in each 30-s epoch

Fig. 3

Fig. 3

Examples of wrist and palm EDA during sleep

Fig. 4

Fig. 4

EDA amplitude comparison between palm and wrist (56 nights, 357 hours)

Fig. 5

Fig. 5

# of EDA peaks comparison between palm and wrist (56 nights, 287 hours) Y-axis of the top figure: mean number of EDA peaks per 30s epoch containing ≥ 1 peak, not for all epochs.

Fig. 6

Fig. 6

Mean percentages of sleep stage epochs containing EDA peaks. (N=15, Error bars: s.e.m.)

Fig. 7

Fig. 7

Percentage of epochs with more than 1 EDA peak (threshold = 0.01 μS/s)

Fig. 8

Fig. 8

Example showing that changes in EDA are not always caused by changes in temperature (Skin temperature on the wrist was flat when EDA showed storms, and there are no storms when temperature climbs)

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