• DocumentCode
    628339
  • Title

    Wearable sensors can assist in PTSD diagnosis

  • Author

    Webb, Andrea K ; Vincent, Ashley L. ; Jin, Alvin ; Pollack, Mark H.

  • Author_Institution
    The Charles Stark Draper Laboratory, Cambridge, MA, USA
  • fYear
    2013
  • fDate
    6-9 May 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Post-traumatic stress disorder (PTSD) currently is diagnosed via subjective reports of experiences related to the traumatic event. More objective measures are needed to assist clinicians in diagnosis. Physiological activity was recorded from 58 participants. Participants in the No Trauma/No PTSD group had no trauma exposure and no PTSD diagnosis. Trauma Exposed/No PTSD participants had experienced a traumatic event but did not have PTSD. PTSD participants had experienced a traumatic event and had PTSD. Baseline and emotionally evocative stimulus-related sensor data were collected. Features were extracted from each sensor stream and submitted to statistical analysis. Significant group differences were present during the viewing of two virtual reality videos. Features were submitted to discriminant function analysis to assess classification accuracy. Classification accuracy was between 89 and 92%. The results from this study suggest the utility of objective physiological measures obtained from wearable sensors in assisting with PTSD diagnosis.
  • Keywords
    Accuracy; Heart rate; Physiology; Skin; Stress; Videos; Virtual reality; PTSD; classification accuracy; feature extraction; physiological sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Body Sensor Networks (BSN), 2013 IEEE International Conference on
  • Conference_Location
    Cambridge, MA, USA
  • ISSN
    2325-1425
  • Print_ISBN
    978-1-4799-0331-3
  • Type

    conf

  • DOI
    10.1109/BSN.2013.6575525
  • Filename
    6575525