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Evaluation of Validity and Reliability of Inertial Measurement Unit-Based Gait Analysis Systems

  • Cho, Young-Shin (Department of Rehabilitation Medicine, Hanyang University College of Medicine) ;
  • Jang, Seong-Ho (Department of Rehabilitation Medicine, Hanyang University College of Medicine) ;
  • Cho, Jae-Sung (Department of Arts & Technology, School of Industrial Information Studies, Hanyang University) ;
  • Kim, Mi-Jung (Department of Rehabilitation Medicine, Hanyang University College of Medicine) ;
  • Lee, Hyeok Dong (Department of Rehabilitation Medicine, Hanyang University College of Medicine) ;
  • Lee, Sung Young (Department of Rehabilitation Medicine, Hanyang University College of Medicine) ;
  • Moon, Sang-Bok (Department of Rehabilitation Medicine, Hanyang University College of Medicine)
  • Received : 2018.06.14
  • Accepted : 2018.08.07
  • Published : 2018.12.31

Abstract

Objective To replace camera-based three-dimensional motion analyzers which are widely used to analyze body movements and gait but are also costly and require a large dedicated space, this study evaluates the validity and reliability of inertial measurement unit (IMU)-based systems by analyzing their spatio-temporal and kinematic measurement parameters. Methods The investigation was conducted in three separate hospitals with three healthy participants. IMUs were attached to the abdomen as well as the thigh, shank, and foot of both legs of each participant. Each participant then completed a 10-m gait course 10 times. During each gait cycle, the hips, knees, and ankle joints were observed from the sagittal, frontal, and transverse planes. The experiments were conducted with both a camera-based system and an IMU-based system. The measured gait analysis data were evaluated for validity and reliability using root mean square error (RMSE) and intraclass correlation coefficient (ICC) analyses. Results The differences between the RMSE values of the two systems determined through kinematic parameters ranged from a minimum of 1.83 to a maximum of 3.98 with a tolerance close to 1%. The results of this study also confirmed the reliability of the IMU-based system, and all of the variables showed a statistically high ICC. Conclusion These results confirmed that IMU-based systems can reliably replace camera-based systems for clinical body motion and gait analyses.

Keywords

Acknowledgement

Grant : Development of joint damage prediction algorithm through machine learning of gait analysis data, Development of AR sports training platform based recognition technology on smart glass

Supported by : Institute for Information & communications Technology Promotion

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