Cognitive Based Neural Prosthetics. Andersen, R. A., Musallam, S., Burdick, J. W., & Cham, J. G. In Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on, pages 1908 - 1913, april, 2005. ![Cognitive Based Neural Prosthetics [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper doi abstract bibtex 1 download Intense activity in neural prosthetic research has recently demonstrated the possibility of robotic interfaces that respond directly to the nervous system. The question remains of how the flow of information between the patient and the prosthetic device should be designed to provide a safe, effective system that maximizes the patient #8217;s access to the outside world. Much recent work by other investigators has focused on using decoded neural signals as low-level commands to directly control the trajectory of screen cursors or robotic end-effectors. Here we review results that show that high-level, or cognitive, signals can be decoded from planned arm movements. These results, coupled with fundamental limitations in signal recording technology, motivate an approach in which cognitive neural signals play a larger role in the neural interface. This proposed paradigm predicates that neural signals should be used to instruct external devices, rather than control their detailed movement. This approach will reduce the effort required of the patient and will take advantage of established and on-going robotics research in intelligent systems and human-robot interfaces.
@INPROCEEDINGS{1570392,
author={ Andersen, R. A. and Musallam, Sam and Burdick, J. W. and Cham, J. G.},
booktitle={Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on},
title={Cognitive Based Neural Prosthetics},
year={2005},
month={april},
volume={},
number={},
pages={ 1908 - 1913},
abstract={ Intense activity in neural prosthetic research has recently demonstrated the possibility of robotic interfaces that respond directly to the nervous system. The question remains of how the flow of information between the patient and the prosthetic device should be designed to provide a safe, effective system that maximizes the patient #8217;s access to the outside world. Much recent work by other investigators has focused on using decoded neural signals as low-level commands to directly control the trajectory of screen cursors or robotic end-effectors. Here we review results that show that high-level, or cognitive, signals can be decoded from planned arm movements. These results, coupled with fundamental limitations in signal recording technology, motivate an approach in which cognitive neural signals play a larger role in the neural interface. This proposed paradigm predicates that neural signals should be used to instruct external devices, rather than control their detailed movement. This approach will reduce the effort required of the patient and will take advantage of established and on-going robotics research in intelligent systems and human-robot interfaces. },
keywords={ Neural prosthetics ; brain-machine interfaces;},
doi={10.1109/ROBOT.2005.1570392},
URL ={http://npl.mcgill.ca/Papers/cognitivebasedneuralprosthetics.pdf},
ISSN={},
}
Downloads: 1
{"_id":{"_str":"53422007ecd21cdc070005f8"},"__v":83,"authorIDs":["3APtrXiH9D6Sugg5S","5456e6c28b01c8193000003d","5457d0222abc8e9f3700076f","546213948a9aab071c000268","5de6ee04eab4b7de010000b8","5df85284a0ca62df01000155","5dfbfd85b371afde01000035","5e038868d6cccbdf010000a9","5e03f786ee776fdf01000092","5e044647705486df01000072","5e044c4c705486df010000a8","5e0d4034ae5827df01000034","5e16c634dc7739de0100018b","5e1f735de8f5ddde01000218","5e282ccce6485dde0100005e","5e2fdca34e91a9df01000040","5e3248d5e45eb5df01000098","5e38fec9dc5b8ade01000075","5e3cce3e5cd237de01000015","5e449674ec14b3de0100013e","5e47c30a6c5c7ede010000c5","5e4c85cf5cc521f20100002b","5e4f26b3aa67a8de0100001d","5e5519660096f9de0100004d","5e5aaa3c6ec9eadf010000fc","5e65ab90d92058de01000012","5uANKngwQNgDBJk48","63rnshvzHwPkccxCf","67Qb7nkpgYzGmWAw6","7XMCNhjvTzuQqoZDu","DfNkEqhogCcLbR5RZ","J72QG3kPqnsB5TNzn","KZXG3SLgMFcG2YjRt","N3CLXkjiZrQL56j2a","N4Zn2xfmMtrdXCWqi","NjdfgtcJmCo8qxJAu","QyiqKQyXiaQD8k8Zw","RZc9oSG6uEs9KJzBq","S3snNRagphP9JnhgM","Sh2NJyfRbYhDGzm5L","X8T8fzH4bgF6Paikt","X8mHogWqn7f4r9Fn3","YB8dtNxzhSvqQdPQN","aAB2maSnND2hLoWsS","aNsvE4ywwuxv3qKYG","dnHFuQZPga8cmyBgQ","imSFWwhPTSKo9C7qC","jBerWPDjJqaKYgAbF","nL6XK8skXzQuJx74W","qFxLc4SHtkrxviF4m","qNnPZGcibfD4WfsvM","qpkyYRmkY9AAZQ7jp","sWf3nFEZ3ueLQQEou","sgkCP3aEkHRYDEgic","tCaQuQGCLsWwe5Yaw","uE9esaoKnfDqXKvnq","uKcmsym9Db5Rg5k7x","urAPRxM9nDukL2izo"],"author_short":["Andersen, R. A.","Musallam, S.","Burdick, J. W.","Cham, J. G."],"bibbaseid":"andersen-musallam-burdick-cham-cognitivebasedneuralprosthetics-2005","bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"propositions":[],"lastnames":["Andersen"],"firstnames":["R.","A."],"suffixes":[]},{"propositions":[],"lastnames":["Musallam"],"firstnames":["Sam"],"suffixes":[]},{"propositions":[],"lastnames":["Burdick"],"firstnames":["J.","W."],"suffixes":[]},{"propositions":[],"lastnames":["Cham"],"firstnames":["J.","G."],"suffixes":[]}],"booktitle":"Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on","title":"Cognitive Based Neural Prosthetics","year":"2005","month":"april","volume":"","number":"","pages":"1908 - 1913","abstract":"Intense activity in neural prosthetic research has recently demonstrated the possibility of robotic interfaces that respond directly to the nervous system. The question remains of how the flow of information between the patient and the prosthetic device should be designed to provide a safe, effective system that maximizes the patient #8217;s access to the outside world. Much recent work by other investigators has focused on using decoded neural signals as low-level commands to directly control the trajectory of screen cursors or robotic end-effectors. Here we review results that show that high-level, or cognitive, signals can be decoded from planned arm movements. These results, coupled with fundamental limitations in signal recording technology, motivate an approach in which cognitive neural signals play a larger role in the neural interface. This proposed paradigm predicates that neural signals should be used to instruct external devices, rather than control their detailed movement. This approach will reduce the effort required of the patient and will take advantage of established and on-going robotics research in intelligent systems and human-robot interfaces. ","keywords":"Neural prosthetics ; brain-machine interfaces;","doi":"10.1109/ROBOT.2005.1570392","url":"http://npl.mcgill.ca/Papers/cognitivebasedneuralprosthetics.pdf","issn":"","bibtex":"@INPROCEEDINGS{1570392,\r\nauthor={ Andersen, R. A. and Musallam, Sam and Burdick, J. W. and Cham, J. G.},\r\nbooktitle={Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on}, \r\ntitle={Cognitive Based Neural Prosthetics},\r\nyear={2005},\r\nmonth={april},\r\nvolume={},\r\nnumber={},\r\npages={ 1908 - 1913},\r\nabstract={ Intense activity in neural prosthetic research has recently demonstrated the possibility of robotic interfaces that respond directly to the nervous system. The question remains of how the flow of information between the patient and the prosthetic device should be designed to provide a safe, effective system that maximizes the patient #8217;s access to the outside world. Much recent work by other investigators has focused on using decoded neural signals as low-level commands to directly control the trajectory of screen cursors or robotic end-effectors. Here we review results that show that high-level, or cognitive, signals can be decoded from planned arm movements. These results, coupled with fundamental limitations in signal recording technology, motivate an approach in which cognitive neural signals play a larger role in the neural interface. This proposed paradigm predicates that neural signals should be used to instruct external devices, rather than control their detailed movement. This approach will reduce the effort required of the patient and will take advantage of established and on-going robotics research in intelligent systems and human-robot interfaces. },\r\nkeywords={ Neural prosthetics ; brain-machine interfaces;},\r\ndoi={10.1109/ROBOT.2005.1570392},\r\nURL ={http://npl.mcgill.ca/Papers/cognitivebasedneuralprosthetics.pdf},\r\nISSN={},\r\n}\r\n\r\n","author_short":["Andersen, R. A.","Musallam, S.","Burdick, J. W.","Cham, J. G."],"key":"1570392","id":"1570392","bibbaseid":"andersen-musallam-burdick-cham-cognitivebasedneuralprosthetics-2005","role":"author","urls":{"Paper":"http://npl.mcgill.ca/Papers/cognitivebasedneuralprosthetics.pdf"},"keyword":["Neural prosthetics ; brain-machine interfaces;"],"downloads":1,"html":""},"bibtype":"inproceedings","biburl":"http://npl.mcgill.ca/npl_pub.bib","downloads":1,"keywords":["neural prosthetics ; brain-machine interfaces;","dblp"],"search_terms":["cognitive","based","neural","prosthetics","andersen","musallam","burdick","cham"],"title":"Cognitive Based Neural Prosthetics","year":2005,"dataSources":["2uX35iRShYyWRpd2E"]}