Journal ArticleDOI
Myoelectric control systems—A survey
TLDR
This paper reviews recent research and development in pattern recognition- and non-pattern recognition-based myoelectric control, and presents state-of-the-art achievements in terms of their type, structure, and potential application.About:
This article is published in Biomedical Signal Processing and Control.The article was published on 2007-10-01. It has received 1111 citations till now. The article focuses on the topics: Proportional myoelectric control.read more
Citations
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Journal ArticleDOI
Feature reduction and selection for EMG signal classification
TL;DR: In this study, most complete and up-to-date thirty-seven time domain and frequency domain features have been proposed and it is indicated that most time domain features are superfluity and redundancy.
Journal ArticleDOI
The Extraction of Neural Information from the Surface EMG for the Control of Upper-Limb Prostheses: Emerging Avenues and Challenges
Dario Farina,Ning Jiang,Hubertus Rehbaum,Ales Holobar,Bernhard Graimann,Hans Dietl,Oskar C. Aszmann +6 more
TL;DR: The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness.
Journal ArticleDOI
Smart wearable systems: Current status and future challenges
TL;DR: The current research in wearable is examined to serve as references for researchers and provide perspectives for future research, focusing on multi-parameter physiological sensor systems and activity and mobility measurement system designs that reliably measure mobility or vital signs and integrate real-time decision support processing for disease prevention, symptom detection, and diagnosis.
Journal ArticleDOI
Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb
TL;DR: This work presents a method to adjust SVM parameters before classification, and examines overlapped segmentation and majority voting as two techniques to improve controller performance.
Journal ArticleDOI
Surface Electromyography Signal Processing and Classification Techniques
Rubana H. Chowdhury,Mamun Bin Ibne Reaz,Mohd Alauddin Mohd Ali,Ahmad Ashrif A Bakar,Kalaivani Chellappan,Tae G. Chang +5 more
TL;DR: This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG messages.
References
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Journal ArticleDOI
A new strategy for multifunction myoelectric control
TL;DR: A novel approach to the control of a multifunction prosthesis based on the classification of myoelectric patterns is described, which increases the number of functions which can be controlled by a single channel of myOElectric signal but does so in a way which does not increase the effort required by the amputee.
Journal ArticleDOI
A robust, real-time control scheme for multifunction myoelectric control
Kevin Englehart,B. Hudgins +1 more
TL;DR: It is shown that, by exploiting the processing power inherent in current computing systems, substantial gains in classifier accuracy and response time are possible and other important characteristics for prosthetic control systems are met.
Journal ArticleDOI
A wavelet-based continuous classification scheme for multifunction myoelectric control
TL;DR: It is shown that four channels of myoelectric data greatly improve the classification accuracy, as compared to one or two channels, and a robust online classifier is constructed, which produces class decisions on a continuous stream of data.
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Classification of the myoelectric signal using time-frequency based representations
TL;DR: It is shown that feature sets based upon the short-time Fourier transform, the wavelets transform, and the wavelet packet transform provide an effective representation for classification, provided that they are subject to an appropriate form of dimensionality reduction.
Journal ArticleDOI
A Gaussian mixture model based classification scheme for myoelectric control of powered upper limb prostheses
TL;DR: The GMM-based limb motion classification system demonstrates exceptional classification accuracy and results in a robust method of motion classification with low computational load.
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A robust, real-time control scheme for multifunction myoelectric control
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