Data Analytics of a Wearable Device for Heat Stroke Detection

Autor: Shih-Sung Lin, Chien-Wu Lan, Hao-Yen Hsu, Sheng-Tao Chen
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Sensors, Vol 18, Iss 12, p 4347 (2018)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s18124347
Popis: When exercising in a high-temperature environment, heat stroke can cause great harm to the human body. However, runners may ignore important physiological warnings and are not usually aware that a heat stroke is occurring. To solve this problem, this study evaluates a runner’s risk of heat stroke injury by using a wearable heat stroke detection device (WHDD), which we developed previously. Furthermore, some filtering algorithms are designed to correct the physiological parameters acquired by the WHDD. To verify the effectiveness of the WHDD and investigate the features of these physiological parameters, several people were chosen to wear the WHDD while conducting the exercise experiment. The experimental results show that the WHDD can identify high-risk trends for heat stroke successfully from runner feedback of the uncomfortable statute and can effectively predict the occurrence of a heat stroke, thus ensuring safety.
Databáze: Directory of Open Access Journals
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