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dc.contributor.author Kuniholm, J.
dc.contributor.author Clark, R.L.
dc.date.accessioned 2010-07-28T20:23:43Z
dc.date.available 2010-07-28T20:23:43Z
dc.date.issued 2008
dc.identifier.citation Proceedings of the MEC’08 conference, UNB; 2008. en_US
dc.identifier.uri http://hdl.handle.net/10161/2789
dc.description.abstract Pattern recognition strategies have been explored for prosthetic hand control for over 20 years, but have not been commercially implemented. [1] Articulated research hands now rival human hand articulation, presenting new control challenges. Because no methods of pro- cessing signals of any source (cortical, peripheral nerve or myoelectric) are currently capable of delivering joint angle intent, the information content of user intent must be expanded. Control information for the 15 to 20 joints of a highly articulated hand must be derived from a single variable of grasp information. Two strategies are proposed for augmenting intent to control these hands. First, an array of grasp endpoints composed of the joint angles desired is created for each grasp, and the linear path to the desired endpoint constantly updated. Finger collisions are supervised by the user. Second, a larger set of grasp control parameters are explored. Using additional parameters allows more precise control of the arrangement of the ngers than whole hand grasps, a greater degree of intuitive control over the arrangement of the ngers, and the possibility of dextrous manipulation. en_US
dc.language.iso en_US en_US
dc.publisher Myoelectric Symposium en_US
dc.subject hand control en_US
dc.title SOFTWARE UNDERACTUACTION FOR REDUCED INPUT CONTROL OF LARGE DEGREE OF FREEDOM STRUCTURES: DEVELOPMENT OF A HAND CONTROL STRATEGY FOR ADVANCED UPPER EXTREMITY PROSTHETICS en_US
dc.type Article en_US

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