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Study on body area network of smart clothing for physiological monitoring

Author

Listed:
  • Shen Lei
  • Ren Xiangfang
  • Wu Jianbin
  • Chen Han
  • Ouyang Jianyong

Abstract

With the popularity of the concept of big health and the important role of wearable devices in medical health, users pay more attention to the collection and acquisition of physiological data, but wearable devices attached to human users are independent, and the degree of data sharing is low. Improving the data sharing, accuracy, and reliability of wearable device monitoring is a problem that the article needs to study and solve. Specifically, the researcher summarizes the characteristics of the physiological monitoring smart clothing, and the basic physiological data parameters of human body, and analyzes the collection of three basic signals of electrocardiogram, body temperature, and human movement. This article summarizes the requirements and key technologies of body area network transmission of smart clothing, and studies the body area network node design, energy consumption optimization mode, and network architecture of physiological monitoring smart clothing. At the same time, based on the previous research, the multi-interaction process of smart clothing is formed, and then the standard evaluation system of smart clothing body domain network for evaluation is proposed. The results show that the optimized structure of the body area network of smart clothing proposed by the researchers is efficient, convenient, and mobile, and meets the characteristics of safety, reliability, low power consumption, and portability of smart clothing, especially in the field of physiological monitoring. The standard evaluation system of smart clothing body area network provides a practice-oriented theoretical reference for the current research of smart clothing body area network.

Suggested Citation

  • Shen Lei & Ren Xiangfang & Wu Jianbin & Chen Han & Ouyang Jianyong, 2022. "Study on body area network of smart clothing for physiological monitoring," International Journal of Distributed Sensor Networks, , vol. 18(2), pages 15501477211, February.
    • Handle: RePEc:sae:intdis:v:18:y:2022:i:2:p:15501477211061251
    DOI: 10.1177/15501477211061251
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    References listed on IDEAS

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    1. Zhu, Fengzeng & Liu, Xu & Peng, Li, 2021. "Adaptive consensus-based distributed H∞ filtering with switching topology subject to partial information on transition probabilities," Applied Mathematics and Computation, Elsevier, vol. 411(C).
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