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Physical training gesture recognition using wristwatch wearable devices

Authors
최재현박제원Ahn, T.
Issue Date
Jun-2016
Publisher
Science and Engineering Research Support Society
Keywords
Accelometer; Machine learning; Motion recognition; Wearable device
Citation
International Journal of Multimedia and Ubiquitous Engineering, v.11, no.6, pp.427 - 434
Journal Title
International Journal of Multimedia and Ubiquitous Engineering
Volume
11
Number
6
Start Page
427
End Page
434
URI
http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/5678
DOI
10.14257/ijmue.2016.11.6.38
ISSN
1975-0080
Abstract
Lately, many companies have launched smart watch products with their own strong points, drawing consumers’ attention. A smart watch has changed our life and made it more convenient, offering some different experiences compared to existing smart phones. More importantly, health care using this device has increasingly been the subject of people’s attention and studies. Most of the existing studies have explored mobile devices and multiple sensors recognizing activities related to the routine such as walking, running, and going up and down the stairs. This study has focused on the use in physical training. We made a wearable device with some features of a smart watch, and studied how to make it recognize the activity the user is performing with the built-in accelometer and gyroscope. It is expected to be helpful for the individuals to manage their own exercise systematically and be practical in the health care industry. © 2016 SERSC.
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