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Development of A Textile Capacitive Proximity Sensor and Gait Monitoring System for Smart Healthcare

  • Se Dong Min
  • Changwon Wang
  • Doo-Soon Park
  • Jong Hyuk Park
Mobile & Wireless Health
  • 221 Downloads
Part of the following topical collections:
  1. Convergence of Deep Machine Learning and Nature Inspired Computing Paradigms for Medical Informatics

Abstract

Gait is not only one of the most important functions and activities in daily life but is also a parameter to monitor one‘s health status. We propose a single channel capacitive proximity pressure sensor (TCPS) and gait monitoring system for smart healthcare. Insole-type TCPS (270 mm in length) was designed consisting of three layers including two shield layers and a sensor layer. Analyzing the step count and stride time are the basic indicators in gait analysis, thus they were selected as evaluation indicators. A total of 12 subjects participated in the experiment to evaluate the resolution of our TCPS. To evaluate the accuracy of TCPS, step count and its error rates were simultaneously detected by naked eye, ZIKTO Walk (ZIKTO Co., Korea), and HJ-203-K pedometer (Omron Co., Japan) as reference. Results showed that the error rate of 1.77% in TCPS was lower than those of other devices and correlation coefficient was 0.958 (p-value = 0.000). ZIKTO Walk and pedometer do not provide information on stride time, therefore it was detected by F-scan (Tekscan, USA) to evaluate the performance of TCPS. As a result, error rate of stride time measured by TCPS was found to be 1% and the correlation coefficient was 0.685 (p-value = 0.000). According to these results, our proposed system may be helpful in development of gait monitoring and measurement system as smart healthcare.

Keywords

Gait Situation Smart Healthcare Capacitive Proximity Sensor Conductive Textile 

Abbreviations

TCPS

Textile Capacitive Proximity Sensor

MCU

Microcontroller Unit

Notes

Acknowledgements

This research was supported by the Soonchunhyang University Research Fund.

Author’s contributions

Se Dong designed the framework of research and performed to anlyze gait data. And, Changwon assisted experiment for measuring gait data. Doo-Soon developed the gait monitoring application and Jong Hyuk contributed to verifying of proposed research method.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in this studyinvolving human participants were in accordance with the ethical standards of the Soonchunhyang University of Korea, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

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

Authors and Affiliations

  1. 1.1521, Department of Medical IT EngineeringSoonchunhyang UniversityAsanSouth Korea
  2. 2.M516, Department of Computer software EngineeringSoonchunhyang UniversityAsanSouth Korea
  3. 3.Department of Computer Science and EngineeringSeoul National University of Science and Technology (SeoulTech)SeoulSouth Korea

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