Physical training gesture recognition using wristwatch wearable devices
- Authors
- 최재현; 박제원; Ahn, 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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