2004
DOI: 10.1109/tfuzz.2004.832525
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Neuro-Fuzzy Control of a Robotic Exoskeleton With EMG Signals

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Cited by 324 publications
(173 citation statements)
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“…Another important aspect of an EMG based control method is signal classification. Generally, accuracy of EMG based control method highly depends on method of classification and which helps to identify muscles to generate the required output from the EMG based control method [18]. Different robots use different techniques for signal classification and many of them are based on neuro-fuzzy, fuzzy logic and neural network.…”
Section: Review Of Emg Based Control Methods Of Assistive Robotsmentioning
confidence: 99%
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“…Another important aspect of an EMG based control method is signal classification. Generally, accuracy of EMG based control method highly depends on method of classification and which helps to identify muscles to generate the required output from the EMG based control method [18]. Different robots use different techniques for signal classification and many of them are based on neuro-fuzzy, fuzzy logic and neural network.…”
Section: Review Of Emg Based Control Methods Of Assistive Robotsmentioning
confidence: 99%
“…Feature selection: Due to the large number of inputs and randomness of the signal, it is impractical to feed the EMG signal directly to the classifier [6,18]. Therefore, it is necessary to create the feature vector, where sequence is mapped into a smaller dimension vector.…”
Section: Data Segmentationmentioning
confidence: 99%
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“…Mobility aids [5], manipulation aids [6], therapeutic aids [7], surgical robots [8], physical and mental 1 C. Jayawardena, N. Baghaei, K. Ganeshan, and A. Sarrafzadeh are with the Department of Computing, Unitec Institute of Technology, New Zealand cjayawardena at unitec.ac.nz rehabilitation robots [9] [10], medication reminding robots [11] and elder-care robots [12] are some examples . Among these solutions, 'socially assistive robots' belong to a distinct category.…”
Section: Introductionmentioning
confidence: 99%