When Your Wearables Become Your Fitness Mate

dc.contributor.authorGuo, Xiaonan
dc.contributor.authorLiu, Jian
dc.contributor.authorChen, Yingying
dc.contributor.departmentComputer Information and Graphics Technology, School of Engineering and Technologyen_US
dc.date.accessioned2021-01-28T22:12:01Z
dc.date.available2021-01-28T22:12:01Z
dc.date.issued2020-05
dc.description.abstractAcknowledging the powerful sensors on wearables and smartphones enabling various applications to improve users' life styles and qualities (e.g., sleep monitoring and running rhythm tracking), this paper takes one step forward developing FitCoach, a virtual fitness coach leveraging users' wearable mobile devices (including wrist-worn wearables and arm-mounted smartphones) to assess dynamic postures (movement patterns & positions) in workouts. FitCoach aims to help the user to achieve effective workout and prevent injury by dynamically depicting the short-term and long-term picture of a user's workout based on various sensors in wearable mobile devices. In particular, FitCoach recognizes different types of exercises and interprets fine-grained fitness data (i.e., motion strength and speed) to an easy-to-understand exercise review score, which provides a comprehensive workout performance evaluation and recommendation. Our system further enables contactless device control during workouts (e.g., gesture to pick up an incoming call) through distinguishing customized gestures from regular exercise movement. In addition, FitCoach has the ability to align the sensor readings from wearable devices to the human coordinate system, ensuring the accuracy and robustness of the system. Extensive experiments with over 5000 repetitions of 12 types of exercises involve 12 participants doing both anaerobic and aerobic exercises in indoors as well as outdoors. Our results demonstrate that FitCoach can provide meaningful review and recommendations to users by accurately measure their workout performance and achieve and accuracy for workout analysis and customized control gesture recognition, respectively.en_US
dc.eprint.versionAuthor's manuscripten_US
dc.identifier.citationGuo, X., Liu, J., & Chen, Y. (2020). When your wearables become your fitness mate. Smart Health, 16, 100114. https://doi.org/10.1016/j.smhl.2020.100114en_US
dc.identifier.urihttps://hdl.handle.net/1805/25056
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.isversionof10.1016/j.smhl.2020.100114en_US
dc.relation.journalSmart Healthen_US
dc.rightsPublisher Policyen_US
dc.sourceAuthoren_US
dc.subjectmobile healthen_US
dc.subjectwearable devicesen_US
dc.subjectexercise recognitionen_US
dc.titleWhen Your Wearables Become Your Fitness Mateen_US
dc.typeArticleen_US
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