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An Analysis of Intrinsic and Extrinsic Hand Muscle EMG for Improved Pattern Recognition Control

Published on Apr 1, 2016in IEEE Transactions on Neural Systems and Rehabilitation Engineering3.48
· DOI :10.1109/TNSRE.2015.2424371
Adenike A. Adewuyi4
Estimated H-index: 4
(Rehabilitation Institute of Chicago),
Levi J. Hargrove29
Estimated H-index: 29
(Rehabilitation Institute of Chicago),
Todd A. Kuiken40
Estimated H-index: 40
(Rehabilitation Institute of Chicago)
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Abstract
Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.
  • References (37)
  • Citations (27)
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References37
Newest
Published on Aug 1, 2014 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
Eric J. Earley1
Estimated H-index: 1
(Rehabilitation Institute of Chicago),
Adenike A. Adewuyi4
Estimated H-index: 4
(Rehabilitation Institute of Chicago),
Levi J. Hargrove29
Estimated H-index: 29
(Rehabilitation Institute of Chicago)
Partial-hand amputees often retain good residual wrist motion, which is essential for functional activities involving use of the hand. Thus, a crucial design criterion for a myoelectric, partial-hand prosthesis control scheme is that it allows the user to retain residual wrist motion. Pattern recognition (PR) of electromyographic (EMG) signals is a well-studied method of controlling myoelectric prostheses. However, wrist motion degrades a PR system’s ability to correctly predict hand-grasp patte...
Published on Jan 20, 2014
Ravi Balasubramanian12
Estimated H-index: 12
,
Veronica J. Santos1
Estimated H-index: 1
The Human Hand as an Inspiration for Robot Hand Development presents an edited collection of authoritative contributions in the area of robot hands. The results described in the volume are expected to lead to more robust, dependable, and inexpensive distributed systems such as those endowed with complex and advanced sensing, actuation, computation, and communication capabilities. The twenty-four chapters discuss the field of robotic grasping and manipulation viewed in light of the human hands ca...
Published on Jan 1, 2014
Ravi Balasubramanian12
Estimated H-index: 12
(OSU: Oregon State University),
Ling Xu3
Estimated H-index: 3
(CMU: Carnegie Mellon University)
+ 2 AuthorsYoky Matsuoka17
Estimated H-index: 17
(UW: University of Washington)
Published on Nov 1, 2013
Adenike A. Adewuyi4
Estimated H-index: 4
(Rehabilitation Institute of Chicago),
Levi J. Hargrove29
Estimated H-index: 29
(Rehabilitation Institute of Chicago),
Todd A. Kuiken40
Estimated H-index: 40
(Rehabilitation Institute of Chicago)
Pattern-recognition-based control using surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for providing control of multiple prosthetic functions. However, it is not clear how these systems will perform when the user possesses a functional wrist; an attribute unique to the population of partial-hand amputees. Fortunately, partial-hand amputees may have remaining intrinsic hand muscles, from which additional information-rich EMG data may be extracted and used f...
Published on May 1, 2013in IEEE Journal of Biomedical and Health Informatics4.22
Ali H. Al-Timemy7
Estimated H-index: 7
(PSU: Plymouth State University),
Guido Bugmann18
Estimated H-index: 18
(PSU: Plymouth State University)
+ 1 AuthorsNicholas Outram6
Estimated H-index: 6
(PSU: Plymouth State University)
A method for the classification of finger movements for dexterous control of prosthetic hands is proposed. Previous research was mainly devoted to identify hand movements as these actions generate strong electromyography (EMG) signals recorded from the forearm. In contrast, in this paper, we assess the use of multichannel surface electromyography (sEMG) to classify individual and combined finger movements for dexterous prosthetic control. sEMG channels were recorded from ten intact-limbed and si...
Published on Feb 1, 2013in Medical & Biological Engineering & Computing2.04
Ning Jiang27
Estimated H-index: 27
(GAU: University of Göttingen),
Silvia Muceli18
Estimated H-index: 18
(GAU: University of Göttingen)
+ 1 AuthorsDario Farina70
Estimated H-index: 70
(GAU: University of Göttingen)
Myoelectric control has been extensively applied in multi-function hand/wrist prostheses. The performance of this type of control is however, influenced by several practical factors that still limit its clinical applicability. One of these factors is the change in arm posture during the daily use of prostheses. In this study, we investigate the effect of arm position on the performance of a simultaneous and proportional myoelectric control algorithm, both on trans-radial amputees and able-bodied...
Published on Sep 1, 2012in Expert Systems With Applications4.29
Rami N. Khushaba17
Estimated H-index: 17
(UTS: University of Technology, Sydney),
Sarath Kodagoda15
Estimated H-index: 15
(UTS: University of Technology, Sydney)
+ 1 AuthorsGamini Dissanayake34
Estimated H-index: 34
(UTS: University of Technology, Sydney)
A fundamental component of many modern prostheses is the myoelectric control system, which uses the electromyogram (EMG) signals from an individual's muscles to control the prosthesis movements. Despite the extensive research focus on the myoelectric control of arm and gross hand movements, more dexterous individual and combined fingers control has not received the same attention. The main contribution of this paper is an investigation into accurately discriminating between individual and combin...
Published on Feb 1, 2012in Hand Clinics1.24
Steve K. Lee22
Estimated H-index: 22
(Cornell University),
Jamie R. Wisser1
Estimated H-index: 1
(Princeton University)
Published on Feb 1, 2012in Hand Clinics1.24
Frederic E. Liss1
Estimated H-index: 1
The interosseous muscles of the hand can be thought of as the cornerstone of hand function, as they provide a “foundation” for all intrinsic and extrinsic hand movements. Innervated by the ulnar nerve and organized in dorsal and palmar layers, these pivotal muscles have small excursion yet great impact on finger balance, grip, and pinch function, particularly when impaired by denervation and/or contracture. This article gives an overview of the functional anatomy and pathologic dysfunction of th...
Cited By27
Newest
Published on Jan 1, 2020in Biomedical Signal Processing and Control2.94
Omkar S. Powar1
Estimated H-index: 1
(KREC: National Institute of Technology, Karnataka),
Krishnan Chemmangat3
Estimated H-index: 3
(KREC: National Institute of Technology, Karnataka)
Abstract For upper limb prostheses, research carried out earlier mainly focused on increasing the classification accuracy of the hand movements; but there exist a little work done on factors affecting it in real-time control such as wrist variation. Amputees with functional wrist use their prostheses in multiple wrist positions. Since the Electromyography (EMG) data is taken while the subject is performing the motion in different wrist position, it can degrade the performance of the Pattern Reco...
Published on Jul 1, 2019
This paper proposes a motion classification with electromyogram for twisting manipulation, which is composed of flexion/expansion and pronation/supination. Instead of attaching a set of electrodes at the surfaces on each target muscle, we adopt a commercial arm-band-type electrodes array with focusing on wearability. A typical signal processing, Integrated Electromyogram, and a classifier, Support Vector Machine, are employed to analyze eight channels of electromyogram for six hand actions. We e...
Yu Meng Zhou (Wyss Institute for Biologically Inspired Engineering), Diana Wagner3
Estimated H-index: 3
(Wyss Institute for Biologically Inspired Engineering)
+ 7 AuthorsSabrina Paganoni13
Estimated H-index: 13
(Spaulding Rehabilitation Hospital)
Published on Apr 30, 2019in Frontiers in Neurology2.63
Zhiyuan Lu2
Estimated H-index: 2
(University of Texas Health Science Center at Houston),
Zhiyuan Lu + -1 AuthorsPing Zhou
Patients with no or limited hand function usually have difficulty in using conventional input devices such as a mouse or a touch screen. Having the ability of manipulating electronic devices can give patients full access to the digital world, thereby increasing their independence and confidence, and enriching their lives. In this study, a hands-free human-computer interface was developed in order to help patients manipulate computers using facial movements. Five facial movement patterns were det...
Published on Mar 15, 2019in bioRxiv
Agamemnon Krasoulis4
Estimated H-index: 4
(Newcastle University),
Sethu Vijayakumar33
Estimated H-index: 33
(Edin.: University of Edinburgh),
Kianoush Nazarpour16
Estimated H-index: 16
(Newcastle University)
In the field of upper-limb myoelectric prosthesis control, the use of statistical and machine learning methods has been long proposed as a means of enabling intuitive grip selection and activation; yet, clinical adoption remains rather limited. One of the main causes hindering clinical translation of machine learning-based prosthesis control is the requirement for a large number of electromyography (EMG) sensors. Here, we propose an end-to-end strategy for multi-grip, classification-based prosth...
Published on Feb 1, 2019in Experimental Brain Research1.88
Dapeng Yang10
Estimated H-index: 10
(HIT: Harbin Institute of Technology),
Yikun Gu5
Estimated H-index: 5
(HIT: Harbin Institute of Technology)
+ 1 AuthorsHong Liu13
Estimated H-index: 13
(HIT: Harbin Institute of Technology)
The development of advanced and effective human–machine interfaces, especially for amputees to control their prostheses, is very high priority and a very active area of research. An intuitive control method should retain an adequate level of functionality for dexterous operation, provide robustness against confounding factors, and supply adaptability for diverse long-term usage, all of which are current problems being tackled by researchers. This paper reviews the state-of-the-art, as well as, t...
Published on Dec 1, 2018in Scientific Reports4.01
Andreea Ioana Sburlea5
Estimated H-index: 5
(Graz University of Technology),
Gernot R. Müller-Putz45
Estimated H-index: 45
(Graz University of Technology)
Movement covariates, such as electromyographic or kinematic activity, have been proposed as candidates for the neural representation of hand control. However, it remains unclear how these movement covariates are reflected in electroencephalographic (EEG) activity during different stages of grasping movements. In this exploratory study, we simultaneously acquired EEG, kinematic and electromyographic recordings of human subjects performing 33 types of grasps, yielding the largest such dataset to d...
Published on Dec 1, 2018
Sagar Dakua (Independent University, Bangladesh), Alamgir Kabir Rusad (Independent University, Bangladesh)+ 2 AuthorsMd. Kafiul Islam8
Estimated H-index: 8
(Independent University, Bangladesh)
Recently, Human Machine Interface (HMI) has become an important part of medical technology where different bio-signals such as EOG, EMG, and EEG can be deployed to develop a closed-loop control system for physically disabled and elderly people to improve their quality of life. On the other hand, as the road and industrial accidents are increasing in countries like Bangladesh, more and more people are losing body parts and are not able to treat their condition properly due to the financial burden...
Published on Nov 5, 2018 in ICCAD (International Conference on Computer Aided Design)
Kofi Otseidu (NU: Northwestern University), Tianyu Jia2
Estimated H-index: 2
(NU: Northwestern University)
+ 2 AuthorsGu Jie14
Estimated H-index: 14
(NU: Northwestern University)
Modern biomedical devices use sensor fusion techniques to improve the classification accuracy of motion intent of users for rehabilitation application. The design of motion classifier observes significant challenges due to the large number of channels and stringent communication latency requirement. This paper proposes an edge-computing distributed neural processor to effectively reduce the data traffic and physical wiring congestion. A special local and global networking architecture is introdu...
Published on Nov 1, 2018in Neural Computing and Applications4.66
Qin Zhang1
Estimated H-index: 1
(NU: Northeastern University),
Changsheng Zhang2
Estimated H-index: 2
(NU: Northeastern University)
Constraint satisfaction problem (CSP) is a fundamental problem in the field of constraint programming. To tackle this problem more efficiently, an improved ant colony optimization algorithm is proposed. In order to further improve the convergence speed under the premise of not influencing the quality of the solution, a novel strengthened pheromone updating mechanism is designed, which strengthens pheromone on the edge which had never appeared before, using the dynamic information in the process ...
View next paperA new strategy for multifunction myoelectric control