Proceedings of the Korea Contents Association Conference (한국콘텐츠학회:학술대회논문집)
- 2017.05a
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- Pages.257-258
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- 2017
Clustering Analysis on Heart Rate Variation in Daytime Work
- Hayashida, Yukuo (Saga Univ.) ;
- Kidou, Keiko (Saga Univ.) ;
- Mishima, Nobuo (Saga Univ.) ;
- Kitagawa, Keiko (Seitoku Univ.) ;
- Yoo, Jaesoo (Chungbuk National Univ.) ;
- Park, SunGyu (Mokwon Univ.) ;
- Oh, Yong-sun (Mokwon Univ.)
- Published : 2017.05.12
Abstract
Modern society tends to bring excessive labor to people and, therefore, further health management is required. In this paper, by using the clustering technique, one of machine learning methods, we try to bring out the measure of fatigue from heart rate (HR) variation during daytime work, helping people to get high-quality of healthy and calm life.
Keywords
- heart rate variation;
- clustering analysis;
- machine learning;
- degree of fatigue in a day;
- healthy life