Recognition of Daily Human Activity Using an Artificial Neural Network and Smartwatch. (13th June 2018)

• Record Type: Journal Article
• Authors: Kwon, Min-Cheol; Choi, Sunwoong
• Other Names: Kim Dongkyun Academic Editor.
• Is Part Of: Wireless communications and mobile computing. Volume 2018(2018)
• Publication Date: 2018-06-13
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1155/2018/2618045
• Languages: English
• ISSNs: 1530-8669

Abstract

Abstract : Human activity recognition using wearable devices has been actively investigated in a wide range of applications. Most of them, however, either focus on simple activities wherein whole body movement is involved or require a variety of sensors to identify daily activities. In this study, we propose a human activity recognition system that collects data from an off-the-shelf smartwatch and uses an artificial neural network for classification. The proposed system is further enhanced using location information. We consider 11 activities, including both simple and daily activities. Experimental results show that various activities can be classified with an accuracy of 95%.