Electromyography-signal-based muscle fatigue assessment for knee rehabilitation monitoring systems.
10.1007/s13534-018-0078-z
- Author:
Hyeonseok KIM
1
;
Jongho LEE
;
Jaehyo KIM
Author Information
1. Department of Information and Communications Engineering, Tokyo Institute of Technology, Yokohama, Japan.
- Publication Type:Original Article
- Keywords:
Muscle fatigue;
Knee rehabilitation;
EMG signals
- MeSH:
Exercise;
Healthy Volunteers;
Joints;
Knee*;
Leg;
Methods;
Muscle Fatigue*;
Muscle Tonus;
Quadriceps Muscle;
Rehabilitation*
- From:
Biomedical Engineering Letters
2018;8(4):345-353
- CountryRepublic of Korea
- Language:English
-
Abstract:
This study suggested a new EMG-signal-based evaluation method for knee rehabilitation that provides not only fragmentary information like muscle power but also in-depth information like muscle fatigue in the field of rehabilitation which it has not been applied to. In our experiment, nine healthy subjects performed straight leg raise exercises which are widely performed for knee rehabilitation. During the exercises, we recorded the joint angle of the leg andEMGsignals from four prime movers of the leg: rectus femoris (RFM), vastus lateralis, vastus medialis, and biceps femoris (BFLH). We extracted two parameters to estimate muscle fatigue from the EMG signals, the zero-crossing rate (ZCR) and amplitude of muscle tension (AMT) that can quantitatively assess muscle fatigue from EMG signals. We found a decrease in the ZCR for the RFM and the BFLH in the muscle fatigue condition for most of the subjects. Also, we found increases in theAMT for the RFM and the BFLH. Based on the results, we quantitatively confirmed that in the state of muscle fatigue, the ZCR shows a decreasing trend whereas theAMT shows an increasing trend. Our results show that both the ZCR and AMT are useful parameters for characterizing the EMG signals in the muscle fatigue condition. In addition, our proposed methods are expected to be useful for developing a navigation system for knee rehabilitation exercises by evaluating the two parameters in two-dimensional parameter space.
