Making Activity Recognition Robust against Deceptive Behavior.

ABSTRACT: Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are physically active, based on the data collected from their activity tracking devices. Therefore, there is an increasing motivation for individuals to cheat, by making activity trackers detect activities that increase their benefits rather than the ones they actually do. In this study, we used a novel method to make activity recognition robust against deceptive behavior. We asked 14 subjects to attempt to trick our smartphone-based activity classifier by making it detect an activity other than the one they actually performed, for example by shak

SUBMITTER: Saeb S 

PROVIDER: S-EPMC4676610 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature