The Effect of ECG Interference on Pattern-Recognition-Based Myoelectric Control for Targeted Muscle Reinnervated Patients | IEEE Journals & Magazine | IEEE Xplore

The Effect of ECG Interference on Pattern-Recognition-Based Myoelectric Control for Targeted Muscle Reinnervated Patients


Abstract:

Targeted muscle reinnervation has been introduced as an effective neural machine interface. In the case of a shoulder disarticulation patient, an effective site for a ner...Show More

Abstract:

Targeted muscle reinnervation has been introduced as an effective neural machine interface. In the case of a shoulder disarticulation patient, an effective site for a nerve transfer involves the pectoralis muscles, as these perform little useful function with a missing limb. Consequently, the myoelectric signals measured from the reinnervated muscles may be corrupted by a large amount of ECG interference. This paper investigates the effect of ECG upon the accuracy of a pattern-classification-based scheme for myoelectric control of powered upper limb prostheses. The results suggest that ECG interference, at levels typically encountered in a clinical measurement, has little effect upon classification accuracy, but can affect the estimate of myoelectric activity used to convey the velocity of motion (commonly referred to as proportional control). High-pass filtering at approximately 100 Hz appears to effectively mitigate the effect of ECG interference.
Published in: IEEE Transactions on Biomedical Engineering ( Volume: 56, Issue: 9, September 2009)
Page(s): 2197 - 2201
Date of Publication: 02 December 2008

ISSN Information:

PubMed ID: 19692302

References

References is not available for this document.