A wearable device based solely on electrodermal activity signal processing achieved around 89% accuracy in distinguishing calm from distress conditions.
50 participants in a control experiment to validate a wearable electrodermal activity device for calm/distress classification.
Wearable electrodermal activity (EDA) device
Calm/distress condition classification accuracy
This article introduces a new and unobtrusive wearable monitoring device based on electrodermal activity (EDA) to be used in health-related computing systems. This paper introduces the description of the wearable device capable of acquiring the EDA of a subject in order to detect his/her calm/distress condition from the acquired physiological signals. The lightweight wearable device is placed in the wrist of the subject to allow continuous physiological measurements. With the aim of validating the correct operation of the wearable EDA device, pictures from the International Affective Picture System are used in a control experiment involving fifty participants. The collected signals are processed, features are extracted and a statistical analysis is performed on the calm/distress condition classification. The results show that the wearable device solely based on EDA signal processing reports around 89% accuracy when distinguishing calm condition from distress condition.
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Roberto Zangróniz
University of Castilla-La Mancha
Arturo Martínez‐Rodrigo
University of Castilla-La Mancha
J.M. Pastor
Universidad de Oviedo
Sensors
University of Castilla-La Mancha
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Zangróniz et al. (Thu,) conducted a other in Calm/distress condition (n=50). Wearable electrodermal activity (EDA) device was evaluated on Calm/distress condition classification accuracy. A wearable device based solely on electrodermal activity signal processing achieved around 89% accuracy in distinguishing calm from distress conditions.
synapsesocial.com/papers/6a21e01552bf599176dd8e8b — DOI: https://doi.org/10.3390/s17102324