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Journal of Medical Systems

, 43:16 | Cite as

Intelligent Wearable Occupational Health Safety Assurance System of Power Operation

  • Xiaona Xie
  • Zhengwei ChangEmail author
Mobile & Wireless Health
  • 42 Downloads
Part of the following topical collections:
  1. Artificial Intelligence Application in Health Informatics

Abstract

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.

Keywords

Wearable vital signs monitoring SVM life status assessment method Portable information processing gateway Occupational health safety 

Notes

Funding

This study was funded by the Key R&D Projects of Sichuan Province (No. 2017GZ0068), Application of Basic Research Projects of Sichuan Province (No. 2017JY0338), and a project of State Grid Sichuan Electric Power Corporation (No.52199716002P).

Compliance with Ethical Standards

Conflict of Interest

Xiaona Xie declares that she has no conflict of interest. Zhengwei Chang declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants performed by any of the authors.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Control Science and EngineeringChengdu University of Information TechnologyChengduChina
  2. 2.State Grid Sichuan Electric Power Research InstituteChengduChina

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