TY - GEN
T1 - An exploratory study on the use of convolutional neural networks for object grasp classification
AU - Ghazaei, G.
AU - Alameer, A.
AU - Degenaar, P.
AU - Morgan, G.
AU - Nazarpour, K.
PY - 2015/12/1
Y1 - 2015/12/1
N2 - The loss of hand profoundly affects an individual's quality of life. Prosthetic hands can provide a route to functional rehabilitation by allowing the amputees to undertake their daily activities. However, the performance of current artificial hands falls well short of the dexterity that natural hands offer. The aim of this study is to test whether an intelligent vision system could be used to enhance the grip functionality of prosthetic hands. To this end, a convolutional neural network (CNN) deep learning architecture was implemented to classify the objects in the COIL100 database in four basic grasp groups: tripod, pinch, palmar and palmar with wrist rotation. Our preliminary, yet promising, results suggest that the additional machine vision system can provide prosthetic hands with the ability to detect object and propose the user an appropriate grasp.
AB - The loss of hand profoundly affects an individual's quality of life. Prosthetic hands can provide a route to functional rehabilitation by allowing the amputees to undertake their daily activities. However, the performance of current artificial hands falls well short of the dexterity that natural hands offer. The aim of this study is to test whether an intelligent vision system could be used to enhance the grip functionality of prosthetic hands. To this end, a convolutional neural network (CNN) deep learning architecture was implemented to classify the objects in the COIL100 database in four basic grasp groups: tripod, pinch, palmar and palmar with wrist rotation. Our preliminary, yet promising, results suggest that the additional machine vision system can provide prosthetic hands with the ability to detect object and propose the user an appropriate grasp.
KW - Machine Learning
KW - Machine Vision
KW - Deep Learning
KW - Deep Convolution Network
KW - Artificial Intelligence
U2 - 10.1049/cp.2015.1760
DO - 10.1049/cp.2015.1760
M3 - Conference contribution
T3 - IET International Conference on Intelligent Signal Processing (ISP): Proceedings
BT - 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP): Proceedings
T2 - 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP)
Y2 - 1 December 2015 through 2 December 2015
ER -