Development of Joint Activity Angle Measurement and Cloud Data Storage System

Chiu Ching Tuan, Yi Chao Wu, Wen Ling Yeh, Chun Chieh Wang, Chi Heng Lu, Shao Wei Wang, Jack Yang, Tsair Fwu Lee, Hsuan Kai Kao*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

6 Scopus citations

Abstract

In this study, we developed a range of motion sensing system (ROMSS) to simulate the function of the elbow joint, with errors less than 0.76 degrees and 0.87 degrees in static and dynamic verification by the swinging and angle recognition modules, respectively. In the simulation process, the ɣ correlation coefficient of the Pearson difference between the ROMSS and the universal goniometer was 0.90, the standard deviations of the general goniometer measurements were between ± 2 degrees and ± 2.6 degrees, and the standard deviations between the ROMSS measurements were between ± 0.5 degrees and ± 1.6 degrees. With the ROMSS, a cloud database was also established; the data measured by the sensor could be uploaded to the cloud database in real-time to provide timely patient information for healthcare professionals. We also developed a mobile app for smartphones to enable patients and healthcare providers to easily trace the data in real-time. Historical data sets with joint activity angles could be retrieved to observe the progress or effectiveness of disease recovery so the quality of care could be properly assessed and maintained.

Original languageEnglish
Article number4684
JournalSensors
Volume22
Issue number13
DOIs
StatePublished - 01 07 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Kalman filter
  • cloud database
  • elbow range of motion (ROM)
  • extremities rehabilitation
  • goniometer
  • weighted moving average filter (WMAF)

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