무선 보행 분석을 위한 블루투스 기반 관성 측정 장치의 활용 타당성 분석
Validation on the Application of Bluetooth-based Inertial Measurement Unit for Wireless Gait Analysis
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초록
The purpose of this paper is to review the validation on the application of low frequency IMU(Inertial Measurement Unit) sensors by replacing high frequency motion analysis systems. Using an infrared-based 3D motion analysis system and IMU sensors (22 Hz) simultaneously, the gait cycle and knee flexion angle were measured. And the accuracy of each gait parameter was compared according to the statistical analysis method. The Bland-Altman plot analysis method was used to verify whether proper accuracy can be obtained when extracting gait parameters with low frequency sensors. As a result of the study, the use of the new gait assessment system was able to identify adequate accuracy in the measurement of cadence and stance phase. In addition, if the number of gait cycles is increased and the results of body anthropometric measurements are reflected in the gait analysis algorithm, is expected to improve accuracy in step length, walking speed, and range of motion measurements. The suggested gait assessment system is expected to make gait analysis more convenient. Furthermore, it will provide patients more accurate assessment and customized rehabilitation program through the quantitative data driven results.
Abstract
The purpose of this paper is to review the validation on the application of low frequency IMU(Inertial Measurement Unit) sensors by replacing high frequency motion analysis systems. Using an infrared-based 3D motion analysis system and IMU sensors (22 Hz) simultaneously, the gait cycle and knee flexion angle were measured. And the accuracy of each gait parameter was compared according to the statistical analysis method. The Bland-Altman plot analysis method was used to verify whether proper accuracy can be obtained when extracting gait parameters with low frequency sensors. As a result of the study, the use of the new gait assessment system was able to identify adequate accuracy in the measurement of cadence and stance phase. In addition, if the number of gait cycles is increased and the results of body anthropometric measurements are reflected in the gait analysis algorithm, is expected to improve accuracy in step length, walking speed, and range of motion measurements. The suggested gait assessment system is expected to make gait analysis more convenient. Furthermore, it will provide patients more accurate assessment and customized rehabilitation program through the quantitative data driven results.
참고문헌 (18)
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