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