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Associations Between Physiological Signals Captured Using Wearable Sensors and Self-reported Outcomes Among Adults in Alcohol Use Disorder Recovery: Development and Usability Study.

Parastoo AliniaRamesh Kumar SahMichael Gerard McDonellPatricia PendrySara ParentHassan GhasemzadehMichael John Cleveland
Published in: JMIR formative research (2021)
The results demonstrated that the physiological data collected via an Empatica E4 wearable sensor device were consistent with previous literature in terms of the quality of the data and that features of these physiological signals were significantly associated with several self-reported outcomes among a sample of adults diagnosed with alcohol use disorder. These results suggest that ambulatory assessment of stress is feasible and can be used to develop tailored mobile health interventions to enhance sustained recovery from alcohol use disorder.
Keyphrases
  • alcohol use disorder
  • electronic health record
  • heart rate
  • big data
  • blood pressure
  • systematic review
  • physical activity
  • healthcare
  • type diabetes
  • machine learning
  • adipose tissue
  • data analysis
  • social media