Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm
This paper deals with the statistical analysis and pattern classification of electromyographic signals from the biceps of a person with amputation below the humerus. Such signals collected from an amputation simulator are synergistically generated to produce discrete elbow movements. The purpose of...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2006-01-01
|
| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1533/abbi.2005.0039 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832551906224898048 |
|---|---|
| author | M. José H. Erazo Macias S. Alejandro Vega |
| author_facet | M. José H. Erazo Macias S. Alejandro Vega |
| author_sort | M. José H. Erazo Macias |
| collection | DOAJ |
| description | This paper deals with the statistical analysis and pattern classification of electromyographic signals from the biceps of a person with amputation below the humerus. Such signals collected from an amputation simulator are synergistically generated to produce discrete elbow movements. The purpose of this study is to utilise these signals to control an electrically driven prosthetic or orthotic elbow with minimum extra mental effort on the part of the subject. The results show very good separability of classes of movements when a learning pattern classification scheme is used, and a superposition of any composite motion to the three basic primitive motions—humeral rotation in and out, flexion and extension, and pronation and supination. Since no synergy was detected for the wrist movement, different inputs have to be provided for a grip. In addition, the method described is not limited by the location of the electrodes. For amputees with shorter stumps, synergistic signals could be obtained from the shoulder muscles. However, the presentation in this paper is limited to biceps signal classification only. |
| format | Article |
| id | doaj-art-ce6c0b899f5a4a08a663546bec3a4161 |
| institution | Kabale University |
| issn | 1176-2322 1754-2103 |
| language | English |
| publishDate | 2006-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-ce6c0b899f5a4a08a663546bec3a41612025-02-03T06:00:14ZengWileyApplied Bionics and Biomechanics1176-23221754-21032006-01-013211311910.1533/abbi.2005.0039Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic ArmM. José H. Erazo Macias0S. Alejandro Vega1Department of Electric and Electronic Engineering, Technological Institute of Reynosa, Reynosa Tamaulipas, MexicoTechnological Institute of Superior Studies of Monterrey, Campus Queretaro, Queretaro, MexicoThis paper deals with the statistical analysis and pattern classification of electromyographic signals from the biceps of a person with amputation below the humerus. Such signals collected from an amputation simulator are synergistically generated to produce discrete elbow movements. The purpose of this study is to utilise these signals to control an electrically driven prosthetic or orthotic elbow with minimum extra mental effort on the part of the subject. The results show very good separability of classes of movements when a learning pattern classification scheme is used, and a superposition of any composite motion to the three basic primitive motions—humeral rotation in and out, flexion and extension, and pronation and supination. Since no synergy was detected for the wrist movement, different inputs have to be provided for a grip. In addition, the method described is not limited by the location of the electrodes. For amputees with shorter stumps, synergistic signals could be obtained from the shoulder muscles. However, the presentation in this paper is limited to biceps signal classification only.http://dx.doi.org/10.1533/abbi.2005.0039 |
| spellingShingle | M. José H. Erazo Macias S. Alejandro Vega Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm Applied Bionics and Biomechanics |
| title | Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm |
| title_full | Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm |
| title_fullStr | Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm |
| title_full_unstemmed | Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm |
| title_short | Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm |
| title_sort | electromyographic pattern analysis and classification for a robotic prosthetic arm |
| url | http://dx.doi.org/10.1533/abbi.2005.0039 |
| work_keys_str_mv | AT mjoseherazomacias electromyographicpatternanalysisandclassificationforaroboticprostheticarm AT salejandrovega electromyographicpatternanalysisandclassificationforaroboticprostheticarm |