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Architecture and Design of a Wearable Robotic System for Body Posture Monitoring, Correction, and Rehabilitation Assist

  • Jun ZhangEmail author
  • Hui Zhang
  • Chengcheng Dong
  • Fanzhang Huang
  • Qi Liu
  • Aiguo Song
Article
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Abstract

With the heavy use of consumer electronic devices (CEDs) like smartphones, laptops, etc. in daily life, more and more people feel head, neck, and back pains because of long time poor body postures during the use of these devices. This paper presents a “patients–robots–doctors” architecture and designs a wearable robotic system for body postures monitoring, correction, and rehabilitation assist. The system mainly includes a wearable robotic device (WRD) and the CEDs. The WRD monitors the postures of body segments and reminds the user to correct bad postures. The posture data are sent to CEDs for processing and visualization. The data can also be uploaded to a cloud server for professional analysis by “doctors”. The human body posture is modeled and simulated to show that the different postures of the body segments have large effects on the torques and forces acting on the joints and muscles. A posture detection method is proposed and the WRD is designed. The basic functions of the architecture and system are verified by experiments including head–neck posture, back posture, sleeping posture, and leg posture monitoring and correction warning. The architecture and system can be utilized not only by the patients–doctors in telerehabilitation exercise assist but also by the parents–children in good sitting habits development, the athletes–coaches and bodybuilders–instructors in training efficiency improvement, etc.

Keywords

Wearable robotic device Body posture model Posture detection Posture correction Rehabilitation assist 

Notes

Acknowledgements

This work was supported in part by the Natural Science Foundation of China under Grant 61873066, Natural Science Foundation of Jiangsu Province under Grant BK20181270, and the Fundamental Research Funds for the Central Universities 2242018k10018.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Jun Zhang
    • 1
    Email author
  • Hui Zhang
    • 1
  • Chengcheng Dong
    • 1
  • Fanzhang Huang
    • 1
  • Qi Liu
    • 1
  • Aiguo Song
    • 1
  1. 1.The State Key Laboratory of Bioelectronics, Jiangsu Key Lab of Remote Measurement and Control, School of Instrument Science and EngineeringSoutheast UniversityNanjingChina

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