Adaptive Filters for Muscle Response Suppression

Søren Sennels; Fin Biering-Soerensen; Steffen Duus Hansen; Ole Trier Andersen

doi:10.1109/IEMBS.1996.651844

Adaptive Filters for Muscle Response Suppression

Søren Sennels, Fin Biering-Soerensen, Steffen Duus Hansen, Ole Trier Andersen

Rigshospitalet

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

To be able to use the voluntary EMG-signal from an electrically stimulated muscle as control signal for FES-applications, it is necessary to eliminate the muscle response evoked by the stimulation. The muscle response is a non-stationary signal, therefore a set of linear adaptive prediction filters are proposed, based on the observation that the shape of the muscle responses only exhibits moderate changes during a time window of up to 300 ms. The filters are derived and compared with a conventional fixed comb filter on both simulated and real data. For variations in amplitude of the muscle responses the performance of the adaptive filters are independent of the filter length, whereas for variations in the shape the performance is increased with the filter length. Using the adaptive filters it is possible to obtain a signal-to-noise ratio, which enables the EMG from a partly paralysed muscle to be used as control signal for stimulation of the same muscle

Original language	English
Title of host publication	Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology
Volume	Volume 2
Publisher	IEEE
Publication date	1996
Pages	518-520
ISBN (Print)	07-80-33811-1
DOIs	https://doi.org/10.1109/IEMBS.1996.651844
Publication status	Published - 1996
Event	18th Annual International Conference of the IEEE Engineering in Medicine and Biology - Amsterdam, Netherlands Duration: 31 Oct 1996 → 3 Nov 1996 Conference number: 18

Conference

Conference	18th Annual International Conference of the IEEE Engineering in Medicine and Biology
Number	18
Country/Territory	Netherlands
City	Amsterdam
Period	31/10/1996 → 03/11/1996

Bibliographical note

Copyright 1996 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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title = "Adaptive Filters for Muscle Response Suppression",

abstract = "To be able to use the voluntary EMG-signal from an electrically stimulated muscle as control signal for FES-applications, it is necessary to eliminate the muscle response evoked by the stimulation. The muscle response is a non-stationary signal, therefore a set of linear adaptive prediction filters are proposed, based on the observation that the shape of the muscle responses only exhibits moderate changes during a time window of up to 300 ms. The filters are derived and compared with a conventional fixed comb filter on both simulated and real data. For variations in amplitude of the muscle responses the performance of the adaptive filters are independent of the filter length, whereas for variations in the shape the performance is increased with the filter length. Using the adaptive filters it is possible to obtain a signal-to-noise ratio, which enables the EMG from a partly paralysed muscle to be used as control signal for stimulation of the same muscle",

author = "S{\o}ren Sennels and Fin Biering-Soerensen and Hansen, {Steffen Duus} and Andersen, {Ole Trier}",

note = "Copyright 1996 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.; 18th Annual International Conference of the IEEE Engineering in Medicine and Biology, EMBC 1996 ; Conference date: 31-10-1996 Through 03-11-1996",

year = "1996",

doi = "10.1109/IEMBS.1996.651844",

language = "English",

isbn = "07-80-33811-1",

volume = "Volume 2",

pages = "518--520",

booktitle = "Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology",

publisher = "IEEE",

address = "United States",

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Sennels, S, Biering-Soerensen, F, Hansen, SD & Andersen, OT 1996, Adaptive Filters for Muscle Response Suppression. in Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology. vol. Volume 2, IEEE, pp. 518-520, 18th Annual International Conference of the IEEE Engineering in Medicine and Biology, Amsterdam, Netherlands, 31/10/1996. https://doi.org/10.1109/IEMBS.1996.651844

Adaptive Filters for Muscle Response Suppression. / Sennels, Søren; Biering-Soerensen, Fin; Hansen, Steffen Duus et al.
Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology. Vol. Volume 2 IEEE, 1996. p. 518-520.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Adaptive Filters for Muscle Response Suppression

AU - Sennels, Søren

AU - Biering-Soerensen, Fin

AU - Hansen, Steffen Duus

AU - Andersen, Ole Trier

N1 - Conference code: 18

PY - 1996

Y1 - 1996

N2 - To be able to use the voluntary EMG-signal from an electrically stimulated muscle as control signal for FES-applications, it is necessary to eliminate the muscle response evoked by the stimulation. The muscle response is a non-stationary signal, therefore a set of linear adaptive prediction filters are proposed, based on the observation that the shape of the muscle responses only exhibits moderate changes during a time window of up to 300 ms. The filters are derived and compared with a conventional fixed comb filter on both simulated and real data. For variations in amplitude of the muscle responses the performance of the adaptive filters are independent of the filter length, whereas for variations in the shape the performance is increased with the filter length. Using the adaptive filters it is possible to obtain a signal-to-noise ratio, which enables the EMG from a partly paralysed muscle to be used as control signal for stimulation of the same muscle

AB - To be able to use the voluntary EMG-signal from an electrically stimulated muscle as control signal for FES-applications, it is necessary to eliminate the muscle response evoked by the stimulation. The muscle response is a non-stationary signal, therefore a set of linear adaptive prediction filters are proposed, based on the observation that the shape of the muscle responses only exhibits moderate changes during a time window of up to 300 ms. The filters are derived and compared with a conventional fixed comb filter on both simulated and real data. For variations in amplitude of the muscle responses the performance of the adaptive filters are independent of the filter length, whereas for variations in the shape the performance is increased with the filter length. Using the adaptive filters it is possible to obtain a signal-to-noise ratio, which enables the EMG from a partly paralysed muscle to be used as control signal for stimulation of the same muscle

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M3 - Article in proceedings

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BT - Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology

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T2 - 18th Annual International Conference of the IEEE Engineering in Medicine and Biology

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ER -

Adaptive Filters for Muscle Response Suppression

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