Simultaneous and proportional control of 2D wrist movements with myoelectric signals

Previous approaches for extracting real-time proportional control information simultaneously for multiple degree of Freedom(DoF) from the electromyogram (EMG) often used non-linear methods such as the multilayer perceptron (MLP). In this pilot study we show that robust control is also possible with...

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Bibliographic Details
Published in2012 IEEE International Workshop on Machine Learning for Signal Processing pp. 1 - 6
Main Authors Hahne, J. M., Rehbaum, H., Biessmann, F., Meinecke, F. C., Muller, K., Jiang, N., Farina, D., Parra, L. C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2012
Subjects
Electromyography
Electromyography (EMG)
Estimation
Joints
Linear regression
myoelectric control
Proportional control
simultaneous control
Trajectory
upper limb prosthesis
Wrist
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ISBN1467310247
9781467310246
ISSN1551-2541
DOI10.1109/MLSP.2012.6349712

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Summary:Previous approaches for extracting real-time proportional control information simultaneously for multiple degree of Freedom(DoF) from the electromyogram (EMG) often used non-linear methods such as the multilayer perceptron (MLP). In this pilot study we show that robust control is also possible with conventional linear regression if EMG power measures are available for a large number of electrodes. In particular, we show that it is possible to linearize the problem with simple nonlinear transformations of band-pass power. Because of its simplicity the method scales well to high dimensions, is easily regularized when insufficient training data is available, and is particularly well suited for real-time control as well as on-line optimization.
ISBN:1467310247
9781467310246
ISSN:1551-2541
DOI:10.1109/MLSP.2012.6349712