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Is Accurate Mapping of EMG Signals on Kinematics Needed for Precise Online Myoelectric Control

Published on May 1, 2014in IEEE Transactions on Neural Systems and Rehabilitation Engineering3.48
· DOI :10.1109/TNSRE.2013.2287383
Ning Jiang27
Estimated H-index: 27
(GAU: University of Göttingen),
Ivan Vujaklija9
Estimated H-index: 9
+ 2 AuthorsDario Farina70
Estimated H-index: 70
(GAU: University of Göttingen)
Abstract
In this paper, we present a systematic analysis of the relationship between the accuracy of the mapping between EMG and hand kinematics and the control performance in goal-oriented tasks of three simultaneous and proportional myoelectric control algorithms: nonnegative matrix factorization (NMF), linear regression (LR), and artificial neural networks (ANN). The purpose was to investigate the impact of the precision of the kinematics estimation by a myoelectric controller for accurately complete goal-directed tasks. Nine naive subjects performed a series of goal-directed myoelectric control tasks using the three algorithms, and their online performance was characterized by 6 indexes. The results showed that, although the three algorithms' mapping accuracies were significantly different, their online performance was similar. Moreover, for LR and ANN, the offline performance was not correlated to any of the online performance indexes, and only a weak correlation was found with three of them for NMF . We conclude that for reliable simultaneous and proportional myoelectric control, it is not necessary to achieve high accuracy in the mapping between EMG and kinematics. Rather, good online myoelectric control is achieved by the continuous interaction and adaptation of the user with the myoelectric controller through feedback (visual in the current study). Control signals generated by EMG with rather poor association with kinematic variables can still be fully exploited by the user for precise control. This conclusion explains the possibility of accurate simultaneous and proportional control over multiple degrees of freedom when using unsupervised algorithms, such as NMF.
  • References (28)
  • Citations (81)
References28
Newest
#1Max Jair Ortiz-Catalan (Chalmers University of Technology)H-Index: 9
#2Rickard Brånemark (Sahlgrenska University Hospital)H-Index: 33
Last.Bo Håkansson (Chalmers University of Technology)H-Index: 28
view all 3 authors...
#1Minas V. Liarokapis (UoA: National and Kapodistrian University of Athens)H-Index: 10
#2Panagiotis K. Artemiadis (ASU: Arizona State University)H-Index: 19
Last.Kostas J. Kyriakopoulos (UoA: National and Kapodistrian University of Athens)H-Index: 35
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#1Aaron J. Young (Rehabilitation Institute of Chicago)H-Index: 19
#2Lauren H. Smith (NU: Northwestern University)H-Index: 11
Last.Levi J. Hargrove (NU: Northwestern University)H-Index: 29
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#1Janne M. HahneH-Index: 7
#2Hubertus Rehbaum (GAU: University of Göttingen)H-Index: 8
Last.Lucas C. Parra (CCNY: City College of New York)H-Index: 46
view all 8 authors...
Aug 1, 2012 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Hubertus Rehbaum (GAU: University of Göttingen)H-Index: 8
#2Ning JiangH-Index: 27
Last.Dario Farina (GAU: University of Göttingen)H-Index: 70
view all 6 authors...
Cited By81
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#2Yuta Murai (University of Electro-Communications)
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#1Wing-Kin Tam (UMN: University of Minnesota)H-Index: 5
#2Tong Wu (UMN: University of Minnesota)H-Index: 5
Last.Zhi Yang (UMN: University of Minnesota)H-Index: 15
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#1Agamemnon Krasoulis (Edin.: University of Edinburgh)H-Index: 4
#2Sethu Vijayakumar (Edin.: University of Edinburgh)H-Index: 33
Last.Kianoush Nazarpour (Newcastle University)H-Index: 16
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#1Agamemnon Krasoulis (Newcastle University)H-Index: 4
#2Sethu Vijayakumar (Edin.: University of Edinburgh)H-Index: 33
Last.Kianoush Nazarpour (Newcastle University)H-Index: 16
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2019 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Bo Lv (SJTU: Shanghai Jiao Tong University)H-Index: 2
#2Xinjun Sheng (SJTU: Shanghai Jiao Tong University)H-Index: 15
Last.Xiangyang Zhu (SJTU: Shanghai Jiao Tong University)H-Index: 21
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