Electrodermal Activity Sensor for Classification of Calm/Distress Condition

Abstract

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.

Estimation of Mental Distress from Photoplethysmography

“…Negative stress (or distress) is one of the most important mental states due to its significant effects in health [1][2][3]. Distress is considered cause and consequence of failure and difficulties in a wide variety of daily situations.…”

“…Mental distress can result in negative views of the environment, others, and the self. This is why it is important to investigate on devices and environments capable of recognizing and/or regulating negative emotions [1][2][3][4][5]. Sadness, anxiety, distraction, and symptoms of mental illness are manifestations of psychological distress.…”

Body Area Networks in Healthcare: A Brief State of the Art

“…More tests are needed to verify the accuracy of this solution. A couple of recent papers have introduced the estimation of mental distress from photoplethysmography [41] and electrodermal activity [42].…”

Film mood induction and emotion classification using physiological signals for health and wellness promotion in older adults living alone

“…Different physiological variables and biopotentials captured from the human body are measured using wearables. Electrodermal activity (EDA), heart rate variability (HRV)—through processing photoplethysmography (PPG) signals—electromyography, and skin temperature are only some examples (Zangróniz, Martínez‐Rodrigo, López, Pastor, & Fernández‐Caballero, ; Zangróniz, Martínez‐Rodrigo, Pastor, López, & Fernández‐Caballero, ). EDA and HRV complementary physiological variables are linked to the central nervous system through sympathetic and parasympathetic components (Malik et al, ).…”

“…EDA and HRV complementary physiological variables are linked to the central nervous system through sympathetic and parasympathetic components (Malik et al, ). It has been reported that EDA is exclusively linked to the sympathetic component and, therefore, with the level of alert (Zangróniz et al, ; Martínez‐Rodrigo, Fernández‐Caballero, Silva, & Novais, ; Martínez‐Rodrigo, Zangróniz, Pastor, & Fernández‐Caballero, ). On the other hand, HRV seems to be related to the parasympathetic component (Zangróniz et al, ).…”