Wearable-Based Human Activity Recognition Using an IoT Approach
AbstractThis paper presents a novel system based on the Internet of Things (IoT) to Human Activity Recognition (HAR) by monitoring vital signs remotely. We use machine learning algorithms to determine the activity done within four pre-established categories (lie, sit, walk and jog). Meanwhile, it is able to give feedback during and after the activity is performed, using a remote monitoring component with remote visualization and programmable alarms. This system was successfully implemented with a 95.83% success ratio. View Full-Text
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Castro, D.; Coral, W.; Rodriguez, C.; Cabra, J.; Colorado, J. Wearable-Based Human Activity Recognition Using an IoT Approach. J. Sens. Actuator Netw. 2017, 6, 28.
Castro D, Coral W, Rodriguez C, Cabra J, Colorado J. Wearable-Based Human Activity Recognition Using an IoT Approach. Journal of Sensor and Actuator Networks. 2017; 6(4):28.Chicago/Turabian Style
Castro, Diego; Coral, William; Rodriguez, Camilo; Cabra, Jose; Colorado, Julian. 2017. "Wearable-Based Human Activity Recognition Using an IoT Approach." J. Sens. Actuator Netw. 6, no. 4: 28.
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