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dc.contributor.advisorPatton, Jamesen_US
dc.contributor.authorGajendran, Rudhramen_US
dc.date.accessioned2013-10-24T21:16:23Z
dc.date.available2013-10-24T21:16:23Z
dc.date.available2015-10-25T09:30:15Z
dc.date.created2013-08en_US
dc.date.issued2013-10-24
dc.date.submitted2013-08en_US
dc.identifier.urihttp://hdl.handle.net/10027/10297
dc.description.abstractControl of myoelectric prosthesis can be achieved in two ways, direct control involving measuring the amplitude of the myoelectric signal or through pattern recognition (PR). PR has the potential to provide a more intuitive control for multi-functional myoelectric prosthesis compared to direct control. Accuracy of PR systems has been shown to improve with increasing number of EMG channels. However, increasing the number of channels requires placing additional electrodes which is not feasible due to space constraints on the residual limb or incorporating multiple hardware components which poses a drawback of increased weight, cost and complexity of the prosthesis. This thesis presents the concept and design of a novel EMG acquisition system to acquire larger number of channels without increasing the number of electrodes placed or the complexity of the signal acquisition system within the prosthetic device. A prototype system was developed and tested to validate performance. Experiments were performed on able-bodied subjects to evaluate system performance in EMG pattern recognition. Subjects were requested to perform nine different hand movements while EMG data was collected into training and test groups. Test results indicate a 15% improvement in classification accuracy with the new system when compared to conventional systems.en_US
dc.language.isoenen_US
dc.rightsen_US
dc.rightsCopyright 2013 Rudhram Gajendranen_US
dc.subjectMyoelectric Prosthesisen_US
dc.subjectEMGen_US
dc.subjectCrosspoint Switchen_US
dc.subjectPattern Recognitionen_US
dc.titleCrosspoint Switch Based EMG Frontend for Pattern Recognition Myoelectric Controlen_US
thesis.degree.departmentBioengineeringen_US
thesis.degree.disciplineBioengineeringen_US
thesis.degree.grantorUniversity of Illinois at Chicagoen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMS, Master of Scienceen_US
dc.type.genrethesisen_US
dc.contributor.committeeMemberRoyston, Thomasen_US
dc.contributor.committeeMemberHargrove, Levien_US
dc.type.materialtexten_US


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