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Stimulation Artifact Removal Algorithm for Real-Time Surface EMG Applications


T. Keller, M.R. Popovic

International Workshop on Functional Electrical Stimulation, Vienna, Austria, no. 7, pp. 118-121

A direct and intuitive method to control a neuroprosthesis for grasping is to use surface EMG (SEMG) activity of muscles that subjects can voluntary control, e.g. in the case of C5 or C6 SCI subjects the deltoid muscles. The measured voluntary SEMG activity in such applications is contaminated with stimulation artifacts (SA) that are much higher in amplitude compared to raw SEMG signals. Hence, to be able to use SEMG signals for control purposes one has to remove the SA from the measured SEMG signal. In closed-loop applications the SA can produce a positive feedback, which further stresses the importance of removing the SA from the measured signal in close-loop SEMG control applications. Well-established SA removal techniques are artifact blanking and filtering methods. Real-time SA blanking methods, either hardware built sample-hold circuits or software blanking routines in digital processed SEMG signals loose all EMG information during the blanking period. Especially with current controlled stimulators, which have a very high output impedance, the electrode-tissue impedance can cause a SA of several milliseconds. Most of the SEMG SA filtering techniques are not viable in case of current stimulators using surface stimulation electrodes, since the long lasting SA tail overlaps in frequency and time domain with the voluntary SEMG activity. A new method that encounters the randomness and stationarity of voluntarily generated EMG is presented. An ensemble averaged SA with exponential forgetting was subtracted from the recorded SEMG and an almost artifact free SEMG signal was obtained. Measurements with multi-channel stimulation patterns showed fast convergence of the algorithm. The algorithm was significantly less sensitive to changes of the stimulation pulse amplitude than to changes of the stimulation pulse width. The method can be implemented in real-time applications and requires a low computational power.

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% Autogenerated BibTeX entry
@InProceedings { KelPop:2001:IFA_226,
    author={T. Keller and M.R. Popovic},
    title={{Stimulation Artifact Removal Algorithm for Real-Time
	  Surface EMG Applications}},
    booktitle={International Workshop on Functional Electrical Stimulation},
    address={Vienna, Austria},
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