Abstract
There have been some studies of exoskeletal robots to support upper limb motion (especially for the physically weak). However, most robots don't completely support internal/external rotation, one of 3 DOF in the shoulder joint. This is because the internal/external rotation is performed by the activities of the rotator cuff, which consists of deep layer muscles. In other words, it is difficult to recognize the surface electromyogram (SEMG) signals, which are generated at muscles far from the skin. In this paper, our aim is to quantify the differences in the SEMG, between the surface layer and deep layer muscles and apply them to the discrimination of the external rotation under the experimental evaluation with twelve young subjects. Four kinds of parameters, such as Zero Crossing (ZC), were selected to express the characteristic of high frequency component in the EMG signal. Specifically, the classification was shown to be 97% successful by applying two features to the learning machine. Hence, it is almost possible to assume that either the deep or the surface muscle is active and discriminate the motions which their muscles involve.
| Original language | English |
|---|---|
| Title of host publication | 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006 |
| Pages | 1634-1639 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2006 |
| Event | 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006 - Kunming Duration: 2006 Dec 17 → 2006 Dec 20 |
Other
| Other | 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006 |
|---|---|
| City | Kunming |
| Period | 06/12/17 → 06/12/20 |
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Keywords
- EMG
- External rotation
- Rotator cuff
- Shoulder
ASJC Scopus subject areas
- Artificial Intelligence
- Electrical and Electronic Engineering
Cite this
Estimation of rotator cuff activity using a surface EMG during shoulder external rotation. / Ando, Takeshi; Nihei, Misato; Fujie, Masakatsu G.
2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006. 2006. p. 1634-1639 4142111.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Estimation of rotator cuff activity using a surface EMG during shoulder external rotation
AU - Ando, Takeshi
AU - Nihei, Misato
AU - Fujie, Masakatsu G.
PY - 2006
Y1 - 2006
N2 - There have been some studies of exoskeletal robots to support upper limb motion (especially for the physically weak). However, most robots don't completely support internal/external rotation, one of 3 DOF in the shoulder joint. This is because the internal/external rotation is performed by the activities of the rotator cuff, which consists of deep layer muscles. In other words, it is difficult to recognize the surface electromyogram (SEMG) signals, which are generated at muscles far from the skin. In this paper, our aim is to quantify the differences in the SEMG, between the surface layer and deep layer muscles and apply them to the discrimination of the external rotation under the experimental evaluation with twelve young subjects. Four kinds of parameters, such as Zero Crossing (ZC), were selected to express the characteristic of high frequency component in the EMG signal. Specifically, the classification was shown to be 97% successful by applying two features to the learning machine. Hence, it is almost possible to assume that either the deep or the surface muscle is active and discriminate the motions which their muscles involve.
AB - There have been some studies of exoskeletal robots to support upper limb motion (especially for the physically weak). However, most robots don't completely support internal/external rotation, one of 3 DOF in the shoulder joint. This is because the internal/external rotation is performed by the activities of the rotator cuff, which consists of deep layer muscles. In other words, it is difficult to recognize the surface electromyogram (SEMG) signals, which are generated at muscles far from the skin. In this paper, our aim is to quantify the differences in the SEMG, between the surface layer and deep layer muscles and apply them to the discrimination of the external rotation under the experimental evaluation with twelve young subjects. Four kinds of parameters, such as Zero Crossing (ZC), were selected to express the characteristic of high frequency component in the EMG signal. Specifically, the classification was shown to be 97% successful by applying two features to the learning machine. Hence, it is almost possible to assume that either the deep or the surface muscle is active and discriminate the motions which their muscles involve.
KW - EMG
KW - External rotation
KW - Rotator cuff
KW - Shoulder
UR - http://www.scopus.com/inward/record.url?scp=36349027831&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=36349027831&partnerID=8YFLogxK
U2 - 10.1109/ROBIO.2006.340189
DO - 10.1109/ROBIO.2006.340189
M3 - Conference contribution
AN - SCOPUS:36349027831
SN - 1424405718
SN - 9781424405718
SP - 1634
EP - 1639
BT - 2006 IEEE International Conference on Robotics and Biomimetics, ROBIO 2006
ER -