@inproceedings{06ee4a758a1d46158a7ce2a128c81dce,
title = "Automatic grasp selection using a camera in a hand prosthesis",
abstract = "In this paper, we demonstrate how automatic grasp selection can be achieved by placing a camera in the palm of a prosthetic hand and training a convolutional neural network on images of objects with corresponding grasp labels. Our labeled dataset is built from common graspable objects curated from the ImageNet dataset and from images captured from our own camera that is placed in the hand. We achieve a grasp classification accuracy of 93.2% and show through realtime grasp selection that using a camera to augment current electromyography controlled prosthetic hands may be useful.",
author = "Joseph Degol and Aadeel Akhtar and Bhargava Manja and Timothy Bretl",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 ; Conference date: 16-08-2016 Through 20-08-2016",
year = "2016",
month = oct,
day = "13",
doi = "10.1109/EMBC.2016.7590732",
language = "English (US)",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "431--434",
booktitle = "2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016",
address = "United States",
}