There exist multiple activity recognition solutions offering good results under controlled conditions. However, little attention has been given to the development of functional systems operating in realistic settings. In that vein, this work aims at presenting the complete process for the design, implementation and evaluation of a real-time activity recognition system. The proposed recognition system consists of three wearable inertial sensors used to register the user body motion, and a mobile application to collect and process the sensory data for the recognition of the user activity. The system not only shows good recognition capabilities after offline evaluation but also after analysis at runtime. In view of the obtained results, this system may serve for the recognition of some of the most frequent daily physical activities.
Activity recognition Wearable sensors mHealth
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Work supported by the ICTD Program (10049079, Development of mining core technology exploiting personal big data) funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea). This work was also supported by the Junta de Andalucia Project P12-TIC-2082.
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