{"title":"An evaluation of wearable activity monitoring devices","authors":"Fangfang Guo, Yu Li, M. Kankanhalli, M. S. Brown","doi":"10.1145/2509352.2512882","DOIUrl":null,"url":null,"abstract":"This paper examines an increasingly relevant topic in the multimedia community of wearable devices that record the physical activity of a user throughout a day. While activity and other accelerometry-based data has been shown effective in various multimedia applications -- from context-aware music retrieval to approximating carbon footprint -- the most promising role of these target application for healthcare and personal fitness. Recently, several low-cost devices have become available to consumers. In this paper, we perform an evaluation on the most popular devices available on the market (in particular Fitbit and Nike+) and report our findings in terms of accuracy, type of data provided, available APIs, and user experience. This information is useful for researchers considering incorporating these activity-based data streams into their research and for getting a better idea of the reliability and accuracy for use in life-logging and other multimedia applications.","PeriodicalId":173211,"journal":{"name":"PDM '13","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"91","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PDM '13","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2509352.2512882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 91
Abstract
This paper examines an increasingly relevant topic in the multimedia community of wearable devices that record the physical activity of a user throughout a day. While activity and other accelerometry-based data has been shown effective in various multimedia applications -- from context-aware music retrieval to approximating carbon footprint -- the most promising role of these target application for healthcare and personal fitness. Recently, several low-cost devices have become available to consumers. In this paper, we perform an evaluation on the most popular devices available on the market (in particular Fitbit and Nike+) and report our findings in terms of accuracy, type of data provided, available APIs, and user experience. This information is useful for researchers considering incorporating these activity-based data streams into their research and for getting a better idea of the reliability and accuracy for use in life-logging and other multimedia applications.