8th International Conference on Body Area Networks

Research Article

Towards a Mobile Galvanic Skin Response Measurement System for Mentally Disordered Patients

  • @INPROCEEDINGS{10.4108/icst.bodynets.2013.253684,
        author={Franz Gravenhorst and Amir Muaremi and Agnes Gruenerbl and Bert Arnrich and Gerhard Troester},
        title={Towards a Mobile Galvanic Skin Response Measurement System  for Mentally Disordered Patients},
        proceedings={8th International Conference on Body Area Networks},
        publisher={ICST},
        proceedings_a={BODYNETS},
        year={2013},
        month={10},
        keywords={galvanic skin response electrodermal activity mental disorder mobile measurements},
        doi={10.4108/icst.bodynets.2013.253684}
    }
    
  • Franz Gravenhorst
    Amir Muaremi
    Agnes Gruenerbl
    Bert Arnrich
    Gerhard Troester
    Year: 2013
    Towards a Mobile Galvanic Skin Response Measurement System for Mentally Disordered Patients
    BODYNETS
    ACM
    DOI: 10.4108/icst.bodynets.2013.253684
Franz Gravenhorst1,*, Amir Muaremi1, Agnes Gruenerbl2, Bert Arnrich3, Gerhard Troester1
  • 1: Wearable Computing Lab., ETH Zurich
  • 2: DFKI GmbH, Embedded Intelligence
  • 3: Computer Engineering Department, Bogazici University
*Contact email: gravenhorst@ife.ee.ethz.ch

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.