DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Kyoobin | ko |
dc.contributor.author | Kwon, Dong-Soo | ko |
dc.date.accessioned | 2007-12-17T07:34:31Z | - |
dc.date.available | 2007-12-17T07:34:31Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2000-11 | - |
dc.identifier.citation | ARTIFICIAL LIFE AND ROBOTICS, v.4, no.4, pp.182 - 187 | - |
dc.identifier.issn | 1433-5298 | - |
dc.identifier.uri | http://hdl.handle.net/10203/2494 | - |
dc.description.abstract | This paper describes a wearable master device for people with a spinal injury who can move their neck and shoulders but cannot move their leg and arms. A device that measures the movements of their neck or shoulder can help them to drive a wheelchair. The sensors of such a wearable master device must be light weight, small, and easily attached to cloth. Therefore, optical fiber curvatures sensors are used to measure the human body motion. For a previously developed wearable master device, two calibration and mapping methods with the sensors are proposed to extract 2-DOF human shoulder motions. One is constructed with simple geometric equations. The other is constructed with a multilayered artificial neural network. The two methods are compared. Experimental results show that the wearable master device can be used effectively for a 2-DOF input device for handicapped persons. It was also shown that a subject can control a mobile robot with the wearable master device. that measures the movements of their neck or shoulder can help them to drive a wheelchair. The sensors of such a wearable master device must be lightweight,small, and easily attached to cloth. Therefore, optical fiber curvature sensors are used to measure the human body motion. For a previously developed wearable master device, two calibration and mapping methods with, the sensors are proposed to extract 2-DOF human shoulder motions. One is constructed with simple geometric equations. The other is constructed with a multilayered artificial neural network. The two methods are compared. Experimental results show that the wear- able master device can be used effectively for a 2-DOF input device for handicapped persons. It was also shown that a subject can control a mobile robot with the wearable master device. | - |
dc.language | English | - |
dc.language.iso | en_US | en |
dc.publisher | Springer Verleg | - |
dc.title | Wearable master device for spinal injured persons as a control device for otorized wheelchairs | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 4 | - |
dc.citation.issue | 4 | - |
dc.citation.beginningpage | 182 | - |
dc.citation.endingpage | 187 | - |
dc.citation.publicationname | ARTIFICIAL LIFE AND ROBOTICS | - |
dc.embargo.liftdate | 9999-12-31 | - |
dc.embargo.terms | 9999-12-31 | - |
dc.contributor.localauthor | Kwon, Dong-Soo | - |
dc.contributor.nonIdAuthor | Lee, Kyoobin | - |
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