Accuracy of Wearable Cameras to Track Social Interactions in Stroke Survivors

Amar Dhand, Alexandra E. Dalton, Douglas A. Luke, Brian F. Gage, Jin Moo Lee

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Background Social isolation after a stroke is related to poor outcomes. However, a full study of social networks on stroke outcomes is limited by the current metrics available. Typical measures of social networks rely on self-report, which is vulnerable to response bias and measurement error. We aimed to test the accuracy of an objective measure—wearable cameras—to capture face-to-face social interactions in stroke survivors. If accurate and usable in real-world settings, this technology would allow improved examination of social factors on stroke outcomes. Methods In this prospective study, 10 stroke survivors each wore 2 wearable cameras: Autographer (OMG Life Limited, Oxford, United Kingdom) and Narrative Clip (Narrative, Linköping, Sweden). Each camera automatically took a picture every 20-30 seconds. Patients mingled with healthy controls for 5 minutes of 1-on-1 interactions followed by 5 minutes of no interaction for 2 hours. After the event, 2 blinded judges assessed whether photograph sequences identified interactions or noninteractions. Diagnostic accuracy statistics were calculated. Results A total of 8776 photographs were taken and adjudicated. In distinguishing interactions, the Autographer's sensitivity was 1.00 and specificity was .98. The Narrative Clip's sensitivity was .58 and specificity was 1.00. The receiver operating characteristic curves of the 2 devices were statistically different (Z = 8.26, P < .001). Conclusions Wearable cameras can accurately detect social interactions of stroke survivors. Likely because of its large field of view, the Autographer was more sensitive than the Narrative Clip for this purpose.

Original languageEnglish
Pages (from-to)2907-2910
Number of pages4
JournalJournal of Stroke and Cerebrovascular Diseases
Issue number12
StatePublished - Dec 1 2016


  • Stroke
  • computers
  • handheld
  • health behavior
  • interpersonal relations
  • photography/instrumentation
  • rehabilitation


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