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Anthropomorphic Control of a Dexterous Artificial Hand via Task Dependent Temporally Synchronized Synergies
Authors:Benjamin A Kcnt  John Lavery  Erik D Engeberg
Institution:[1]Department of Mechanical Engineering, University of Akron, Akron, OH 44325, USA [2]Department of Biomedical Engineering, University of Akron, Akron, OH 44325, USA
Abstract:Despite the recent influx of increasingly dexterous prostheses, there remains a lack of sufficiently intuitive control methods to fully utilize this dexterity. As a solution to this problem, a control framework is proposed which allows the control of an arbitrary number of Degrees of Freedom (DOF) through a single electromyogram (EMG) control input. Initially, the joint motions of nine test subjects were recorded while grasping and catching a cylinder. Inherent differences emerged depending upon whether the cylinder was grasped or caught. These data were used to form a distinct synergy for each task, described as the families of parametric functions of time that share a mutual time vector. These two Temporally Synchronized Synergies (TSS) were derived to reflect the task dependent control strategies adopted by the initial participants. These synergies were then mapped to a dexterous artificial hand that was subsequently controlled by two subjects with transradial amputations. The EMG signals from these subjects were used to replace the time vector shared by the synergies, enabling the subjects to perform both tasks with a dexterous artificial hand using only a single EMG input. After a ten minute training period, the subjects learned to use the dexterous artificial hand to grasp and catch the cylinder with 100.0% and 65.0% average success rates, respectively.
Keywords:electromyogram  dexterous hands  grasp synergy  prosthetics  sliding mode control
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