Neural network classifier for hand motion detection from EMG signal
EMG signal based research is ongoing for the development of simple, robust, user friendly, efficient interfacing devices/systems for the disabled. The advancement can be observed in the area of robotic devices, prosthesis limb, exoskeleton, wearable computer, I/O for virtual reality games and p...
| Main Authors: | , |
|---|---|
| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer Berlin Heidelberg
2011
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/5998/ http://irep.iium.edu.my/5998/ http://irep.iium.edu.my/5998/1/Neural_Network_2011.pdf |
| id |
iium-5998 |
|---|---|
| recordtype |
eprints |
| spelling |
iium-59982012-05-13T10:32:15Z http://irep.iium.edu.my/5998/ Neural network classifier for hand motion detection from EMG signal Ibrahimy, Muhammad Ibn Khalifa, Othman Omran TK7885 Computer engineering EMG signal based research is ongoing for the development of simple, robust, user friendly, efficient interfacing devices/systems for the disabled. The advancement can be observed in the area of robotic devices, prosthesis limb, exoskeleton, wearable computer, I/O for virtual reality games and physical exercise equipments. Additionally, electromyography (EMG) signals can also be applied in the field of human computer interaction (HCI) system. This paper represents the detection of different predefined hand motions (left, right, up and down) using artificial neural network (ANN). A backpropagation (BP) network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. The conventional and most effective time and timefrequency based feature set is utilized for the training of neural network. The obtained results show that the designed network is able to recognize hand movements with satisfied classification efficiency in average of 88.4%. Furthermore, when the trained network tested on unknown data set, it successfully identify the movement types. Springer Berlin Heidelberg 2011-06 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/5998/1/Neural_Network_2011.pdf Ibrahimy, Muhammad Ibn and Khalifa, Othman Omran (2011) Neural network classifier for hand motion detection from EMG signal. In: IFMBE Proceedings. Springer Berlin Heidelberg, pp. 536-541. http://www.springerlink.com/ |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| language |
English |
| topic |
TK7885 Computer engineering |
| spellingShingle |
TK7885 Computer engineering Ibrahimy, Muhammad Ibn Khalifa, Othman Omran Neural network classifier for hand motion detection from EMG signal |
| description |
EMG signal based research is ongoing for the
development of simple, robust, user friendly, efficient interfacing
devices/systems for the disabled. The advancement can be
observed in the area of robotic devices, prosthesis limb, exoskeleton,
wearable computer, I/O for virtual reality games and
physical exercise equipments. Additionally, electromyography
(EMG) signals can also be applied in the field of human computer
interaction (HCI) system. This paper represents the
detection of different predefined hand motions (left, right, up
and down) using artificial neural network (ANN). A backpropagation
(BP) network with Levenberg-Marquardt training
algorithm has been utilized for the classification of EMG
signals. The conventional and most effective time and timefrequency
based feature set is utilized for the training of neural
network. The obtained results show that the designed network
is able to recognize hand movements with satisfied classification
efficiency in average of 88.4%. Furthermore, when the
trained network tested on unknown data set, it successfully
identify the movement types. |
| format |
Book Chapter |
| author |
Ibrahimy, Muhammad Ibn Khalifa, Othman Omran |
| author_facet |
Ibrahimy, Muhammad Ibn Khalifa, Othman Omran |
| author_sort |
Ibrahimy, Muhammad Ibn |
| title |
Neural network classifier for hand motion detection from EMG signal |
| title_short |
Neural network classifier for hand motion detection from EMG signal |
| title_full |
Neural network classifier for hand motion detection from EMG signal |
| title_fullStr |
Neural network classifier for hand motion detection from EMG signal |
| title_full_unstemmed |
Neural network classifier for hand motion detection from EMG signal |
| title_sort |
neural network classifier for hand motion detection from emg signal |
| publisher |
Springer Berlin Heidelberg |
| publishDate |
2011 |
| url |
http://irep.iium.edu.my/5998/ http://irep.iium.edu.my/5998/ http://irep.iium.edu.my/5998/1/Neural_Network_2011.pdf |
| first_indexed |
2023-09-18T20:14:50Z |
| last_indexed |
2023-09-18T20:14:50Z |
| _version_ |
1777407717581783040 |