Elimination of ECG artifacts from myoelectric prosthesis control signals developed by targeted muscle reinnervation

Zhou Ping; Madeleine M. Lowery; Richard F. Weir; Todd A Kuiken

Elimination of ECG artifacts from myoelectric prosthesis control signals developed by targeted muscle reinnervation

Zhou Ping^*, Madeleine M. Lowery, Richard F. Weir, Todd A Kuiken

^*Corresponding author for this work

Physical Medicine and Rehabilitation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Scopus citations

Abstract

We investigated elimination of electrocardiogram (ECG) artifacts from the myoelectric prosthesis control signals, taken from the reinnervated pectoralis muscles of a patient with bilateral amputations at shoulder disarticulation level. The performance of various ECG artifact removal methods including high pass filtering, spike clipping, template subtracting, wavelet thresholding and adaptive filtering was presented. In particular, considering the clinical requirements and memory limitation of commercial prosthesis controllers, we further explored suitable means of ECG artifact removal for clinical application.

Original language	English (US)
Title of host publication	Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages	5276-5279
Number of pages	4
Volume	7 VOLS
State	Published - Dec 1 2005
Event	2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China Duration: Sep 1 2005 → Sep 4 2005

Other

Other	2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country	China
City	Shanghai
Period	9/1/05 → 9/4/05

ASJC Scopus subject areas

Bioengineering

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title = "Elimination of ECG artifacts from myoelectric prosthesis control signals developed by targeted muscle reinnervation",

abstract = "We investigated elimination of electrocardiogram (ECG) artifacts from the myoelectric prosthesis control signals, taken from the reinnervated pectoralis muscles of a patient with bilateral amputations at shoulder disarticulation level. The performance of various ECG artifact removal methods including high pass filtering, spike clipping, template subtracting, wavelet thresholding and adaptive filtering was presented. In particular, considering the clinical requirements and memory limitation of commercial prosthesis controllers, we further explored suitable means of ECG artifact removal for clinical application.",

author = "Zhou Ping and Lowery, {Madeleine M.} and Weir, {Richard F.} and Kuiken, {Todd A}",

year = "2005",

month = dec,

day = "1",

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volume = "7 VOLS",

pages = "5276--5279",

booktitle = "Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005",

note = "2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 ; Conference date: 01-09-2005 Through 04-09-2005",

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Ping, Z, Lowery, MM, Weir, RF & Kuiken, TA 2005, Elimination of ECG artifacts from myoelectric prosthesis control signals developed by targeted muscle reinnervation. in Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005. vol. 7 VOLS, 1615670, pp. 5276-5279, 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005, Shanghai, China, 9/1/05.

Elimination of ECG artifacts from myoelectric prosthesis control signals developed by targeted muscle reinnervation. / Ping, Zhou; Lowery, Madeleine M.; Weir, Richard F.; Kuiken, Todd A.

Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005. Vol. 7 VOLS 2005. p. 5276-5279 1615670.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - We investigated elimination of electrocardiogram (ECG) artifacts from the myoelectric prosthesis control signals, taken from the reinnervated pectoralis muscles of a patient with bilateral amputations at shoulder disarticulation level. The performance of various ECG artifact removal methods including high pass filtering, spike clipping, template subtracting, wavelet thresholding and adaptive filtering was presented. In particular, considering the clinical requirements and memory limitation of commercial prosthesis controllers, we further explored suitable means of ECG artifact removal for clinical application.

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