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
Link To Document :
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