Timed up & go quantification algorithm using IMU and sEMG signal. (February 2023)

• Record Type: Journal Article
• Authors: Lee, Jun-Woo; Park, Dong-Jun; Kim, Min-Kyu; Shin, Myung-Jun; Park, Jong-Hwan; Lee, Byeong-Ju; Lee, Eun-Lee; Jeong, Joon-Soo; Ahn, Se-Jin
• Is Part Of: Biomedical signal processing and control. Volume 80(2023)Part 1
• Publication Date: 2023-02
• Subjects: Timed Up and Go (TUG) -- Surface EMG -- IMU -- Gait analysis -- Quantification algorithm; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2022.104309
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: TUG test is divided into 6 phases though building algorithm using EMG and IMU signals. Quantitative parameters are also calculated by identifying leg movement and muscle contraction through an inertial sensor and an EMG sensor. ICC is 0.9 or higher between TUG times obtained by algorithm and by video as gold standard. Several parameters were confirmed to show significant difference according to age. Abstract: The physical function of the elderly is important in an aging society. Among various physical function tests that are available, Timed Up & Go (TUG) is simple, although it includes various phases, and it's widely used in the medical field. In the TUG test, only the total execution time is manually evaluated. Therefore, during the test, it's not possible to check the physical function according to each movement in detail. In this study, an algorithm is presented for calculating TUG phase and quantitative parameters by identifying leg movement and muscle contraction through an inertial and an electromyography sensor. TUG test was performed on 127 subjects, and the algorithm was verified using the resulting data. TUG times obtained by Algorithm and by Stopwatch were compared with Video TUG time, which was the accurate value. The time obtained by Algorithm was 0.09 s different from the accurate value, while Stopwatch was 0.37 s different. The statistical analysis confirmed that the algorithm was more accurate by 0.28 s, which was found to be a significant result. TUG phases obtained by Algorithm was compared with TUG phases confirmed by Video. The time difference in all phases was within 0.1 s, and the ICC between two methods was 0.9 or higher. It was confirmed whether quantitative parameters showed significant difference according to age, and several parameters was confirmed to show significant difference. Through TUG phases and quantitative parameters, the deviation is eliminated and precise evaluation becomes possible.