Abstract Decoding using Bayesian Muscle Activation Estimators

Matthew Dyson; Kianoush Nazarpour

doi:10.1109/EMBC.2018.8512663

Abstract Decoding using Bayesian Muscle Activation Estimators

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

Abstract

Two recursive Bayesian muscle activation estimators were compared against standard linear filtering during use of a myoelectric abstract decoder. The decoder was controlled by intrinsic muscles of the hand. In both experiments the linear filter outperformed the Bayesian methods in terms of general score. The Bayesian muscle decoders were faster to respond to changes in muscle activity and show promise for significantly enhancing overall decoder communication rate.

Original language	English
Title of host publication	2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	2112-2115
Number of pages	4
ISBN (Electronic)	978-1-5386-3646-6
ISBN (Print)	978-1-5386-3647-3
DOIs	https://doi.org/10.1109/EMBC.2018.8512663
Publication status	Published - 29 Oct 2018
Event	40th International Conference of the IEEE Engineering in Medicine and Biology Society - Honolulu, United States Duration: 17 Jul 2018 → 21 Jul 2018 https://embc.embs.org/2018/

Publication series

Name
Publisher	IEEE
ISSN (Print)	1557-170X
ISSN (Electronic)	1558-4615

Conference

Conference	40th International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated title	EMBC 2018
Country/Territory	United States
City	Honolulu
Period	17/07/18 → 21/07/18
Internet address	https://embc.embs.org/2018/

Access to Document

10.1109/EMBC.2018.8512663Licence: All Rights Reserved

https://ieeexplore.ieee.org/abstract/document/8512663Licence: All Rights Reserved

Sensorimotor learning for control of prosthetic limbs
Nazarpour, K.
1/02/18 → 31/01/23
Project: Research

Cite this

@inproceedings{b61c265c92684491ac1fef82dc559f35,

title = "Abstract Decoding using Bayesian Muscle Activation Estimators",

abstract = "Two recursive Bayesian muscle activation estimators were compared against standard linear filtering during use of a myoelectric abstract decoder. The decoder was controlled by intrinsic muscles of the hand. In both experiments the linear filter outperformed the Bayesian methods in terms of general score. The Bayesian muscle decoders were faster to respond to changes in muscle activity and show promise for significantly enhancing overall decoder communication rate.",

author = "Matthew Dyson and Kianoush Nazarpour",

year = "2018",

month = oct,

day = "29",

doi = "10.1109/EMBC.2018.8512663",

language = "English",

isbn = "978-1-5386-3647-3",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "2112--2115",

booktitle = "2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)",

address = "United States",

note = "40th International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 ; Conference date: 17-07-2018 Through 21-07-2018",

url = "https://embc.embs.org/2018/",

}

Dyson, M & Nazarpour, K 2018, Abstract Decoding using Bayesian Muscle Activation Estimators. in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Institute of Electrical and Electronics Engineers (IEEE), pp. 2112-2115, 40th International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, Hawaii, United States, 17/07/18. https://doi.org/10.1109/EMBC.2018.8512663

Abstract Decoding using Bayesian Muscle Activation Estimators. / Dyson, Matthew; Nazarpour, Kianoush.

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 2112-2115.

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

TY - GEN

T1 - Abstract Decoding using Bayesian Muscle Activation Estimators

AU - Dyson, Matthew

AU - Nazarpour, Kianoush

PY - 2018/10/29

Y1 - 2018/10/29

N2 - Two recursive Bayesian muscle activation estimators were compared against standard linear filtering during use of a myoelectric abstract decoder. The decoder was controlled by intrinsic muscles of the hand. In both experiments the linear filter outperformed the Bayesian methods in terms of general score. The Bayesian muscle decoders were faster to respond to changes in muscle activity and show promise for significantly enhancing overall decoder communication rate.

AB - Two recursive Bayesian muscle activation estimators were compared against standard linear filtering during use of a myoelectric abstract decoder. The decoder was controlled by intrinsic muscles of the hand. In both experiments the linear filter outperformed the Bayesian methods in terms of general score. The Bayesian muscle decoders were faster to respond to changes in muscle activity and show promise for significantly enhancing overall decoder communication rate.

U2 - 10.1109/EMBC.2018.8512663

DO - 10.1109/EMBC.2018.8512663

M3 - Conference contribution

SN - 978-1-5386-3647-3

SP - 2112

EP - 2115

BT - 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 40th International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 17 July 2018 through 21 July 2018

ER -

Abstract Decoding using Bayesian Muscle Activation Estimators

Abstract

Publication series

Conference

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Projects

Sensorimotor learning for control of prosthetic limbs

Cite this