کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11005564 | 1487407 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Effect of shoulder angle variation on sEMG-based elbow joint angle estimation
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
For the decade now, surface electromyogram (sEMG) signal has been extensively applied in joint angle estimation to control the prostheses and exoskeleton systems. However, the sEMG signal patterns can be severely affected by shoulder angle variations, which restricts its applications to a practical use. In our study, we evaluate the effect of shoulder angle variations on elbow angle estimation performance. This adverse effect increases mean root mean square (RMS) error by 14.85â in our experiment. Then, four estimation methods are proposed to solve this problem: (1) using a training set including all shoulder angles' training data to train model; (2) adding two shoulder muscles' sEMG as additional inputs; (3) a two-step method using arm muscles' sEMG and two shoulder muscles' sEMG; and (4) a two-step method using arm muscles' sEMG and measured shoulder angle value by a motion sensor. 13 subjects are employed in this study. The experimental results demonstrate that the mean RMS error is reduced from 21.36â to 12.85â in method one, 9.84â in method two, 7.67â in method three, and 6.93â in method four, respectively. These results show that our methods are effective to eliminate the adverse effect of shoulder angle variations and achieve a better elbow angle estimation performance. Furthermore, this study is helpful to develop a natural and stable control system for prostheses and exoskeleton systems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Industrial Ergonomics - Volume 68, November 2018, Pages 280-289
Journal: International Journal of Industrial Ergonomics - Volume 68, November 2018, Pages 280-289
نویسندگان
Zhichuan Tang, Hongchun Yang, Lekai Zhang, Pengcheng Liu,