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Towards a mobile galvanic skin response measurement system for mentally disordered patients

Published: 30 September 2013 Publication History

Abstract

This paper outlines the design and implementation of a mobile galvanic skin response (GSR) measurement system applied to feet. The system comprises an off-the-shelf node featuring acceleration and GSR sensors with customized firmware and a mobile phone with a customized Android application. The app serves as graphical user interface (GUI) and remote control for the sensor node. The devices communicate wirelessly while implementing a power-saving strategy to limit the amount of communication. The technical feasibility of the system is demonstrated through data recording in a study comprising 28 measurements from 11 patients. In each measurement, two conditions are recorded. 12 statistically and highly significant GSR features for these two conditions are identified, with the number of maxima in the second derivate of the GSR signal being the most significant one.

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Cited By

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  • (2021)Measuring Quantitative Situated User Experience with a Mobile Galvanic Skin Response SensorProceedings of the XX Brazilian Symposium on Human Factors in Computing Systems10.1145/3472301.3484339(1-7)Online publication date: 18-Oct-2021
  • (2021)Heterogeneous Network Approach to Predict Individuals’ Mental HealthACM Transactions on Knowledge Discovery from Data10.1145/342944615:2(1-26)Online publication date: 9-Apr-2021

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    BodyNets '13: Proceedings of the 8th International Conference on Body Area Networks
    September 2013
    610 pages
    ISBN:9781936968893

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    ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)

    Brussels, Belgium

    Publication History

    Published: 30 September 2013

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    Author Tags

    1. electrodermal activity
    2. galvanic skin response
    3. mental disorder
    4. mobile measurements

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    • (2021)Measuring Quantitative Situated User Experience with a Mobile Galvanic Skin Response SensorProceedings of the XX Brazilian Symposium on Human Factors in Computing Systems10.1145/3472301.3484339(1-7)Online publication date: 18-Oct-2021
    • (2021)Heterogeneous Network Approach to Predict Individuals’ Mental HealthACM Transactions on Knowledge Discovery from Data10.1145/342944615:2(1-26)Online publication date: 9-Apr-2021

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