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Fuzzy C-Means Clustering Analysis of the EMG Patterns of Six Major Hand Grasps

Fuzzy C-Means Clustering Analysis of the EMG Patterns of Six Major Hand Grasps. A. Bolu Ajiboye, Northwestern University, Chicago, IL, USA Richard F. ff. Weir, Northwestern University, Chicago, IL, USA. FCM clustering allows for quantification of overlap between hand grasp patterns

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Fuzzy C-Means Clustering Analysis of the EMG Patterns of Six Major Hand Grasps

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  1. Fuzzy C-Means Clustering Analysis of the EMG Patterns of Six Major Hand Grasps A. Bolu Ajiboye, Northwestern University, Chicago, IL, USARichard F. ff. Weir, Northwestern University, Chicago, IL, USA • FCM clustering allows for quantification of overlap between hand grasp patterns • EMGs were recorded from ten extrinsic wrist and hand actuators • No grasp pattern exhibited unity self-membership • EMG pattern overlap suggests overlap in neural control mechanisms • Further analysis on amputees may give insight into prosthesis control paradigms that capitalize on overlap FCM clustering results of six hand grasp patterns for one subject. Membership overlap is observed in all grasp patterns. WeB01.6

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