Intelligent Wearable Occupational Health Safety Assurance System of Power Operation.

To improve the capacity of emergency control over on-site operation risk and effectively guarantee safety of operators in a complicated environment, a wearable safety assurance system framework for power operation is proposed. The framework centres on a wearable information processing gateway for si...

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Publicado en:Journal of Medical Systems Vol. 43; no. 1; pp. 1 - 2
Autores principales: Xie, Xiaona, Chang, Zhengwei
Formato: pictorial tables/charts Journal Article
Publicado: Springer Nature 2019
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2019
      vid: 43
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-018-1122-3
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        atl: Intelligent Wearable Occupational Health Safety Assurance System of Power Operation.
      aug:
        au:
          Xie, Xiaona
          Chang, Zhengwei
        affil: School of Control Science and Engineering, Chengdu University of Information Technology, Chengdu, China
      sug:
        subj:
          Occupational Health
          Occupational Safety
          Wearable Sensors
          Monitoring, Physiologic Equipment and Supplies
          Artificial Intelligence
          Systems Design
          Blue Collar Workers
          Vital Signs
          Heart Rate
          Body Temperature
          Blood Pressure
          Machine Learning
          Power Plants
          Power Sources
          Wireless Communications
          Health Status
          Autonomic Nervous System Physiology
          User-Computer Interface
      ab: To improve the capacity of emergency control over on-site operation risk and effectively guarantee safety of operators in a complicated environment, a wearable safety assurance system framework for power operation is proposed. The framework centres on a wearable information processing gateway for single man and provides standardized access for vital signs monitoring, human-machine interaction and other equipment in a form of wireless ad hoc network. Using wearable vital signs monitoring equipment, the physiological parameters such as heart rate, body temperature and blood pressure can be monitored in real time. By extracting physiological parameters and SVM machine learning method, the operator's health condition is judged. Practical application shows that the wearable safety assurance system can evaluate the life status of workers in complex environment in real time, and can detect the risk of personal safety accidents caused by abnormal physical condition in the process of operation in advance.
      pubtype: Academic Journal
      doctype:
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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