Alcohol abuse causes 1 in 10 deaths among adults in the United States aged 20-64 years [11]. An effort to motivate health-related behavioral changes in e-health industry could be seen before, but it was never done in mobile (m-health) context. Technologically, current applications in smartphone domain, emphasize on a manual way of measuring intoxication levels for users such as logging BAC values, taking cognitive tests; but none of them passively infer user’s intoxication level [1]. ‘Alcogait’ is a smartphone app that infers a smartphone user’s intoxication level from their gait by classifying motion data gathered from the smartphone’s accelerometer and gyroscope by Aiello et al [1]. This study is part of a Master’s thesis to build an intervention system around Alcogait’s functionality and explore the effects of gamification and avatar (for feedback) using Alcogait’s inferred intoxication level. Creation of user engagement is examined, in order to continue future study using gamification along with Alcogait’s functionality. The Alcogait system is not intended to either encourage or discourage abstinence. Its goal is to incentivize responsible transportation choices made by a person or their peers after that person is detected to be intoxicated in order to potentially mitigate DUI situations.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1688 |
| Date | 03 May 2018 |
| Creators | Nimkar, Chaitany |
| Contributors | Emmanuel O. Agu, Advisor, Brian J. Moriarty, Reader, Gillian Smith, Reader |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses (All Theses, All Years) |
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