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Real-Time Classification of Hand Motions Using Ultrasound Imaging of Forearm Muscles

Published on Aug 1, 2016in IEEE Transactions on Biomedical Engineering4.49
· DOI :10.1109/TBME.2015.2498124
Nima Akhlaghi3
Estimated H-index: 3
(GMU: George Mason University),
Clayton A. Baker2
Estimated H-index: 2
(GMU: George Mason University)
+ 7 AuthorsSiddhartha Sikdar16
Estimated H-index: 16
(GMU: George Mason University)
Cite
Abstract
Surface electromyography (sEMG) has been the predominant method for sensing electrical activity for a number of applications involving muscle–computer interfaces, including myoelectric control of prostheses and rehabilitation robots. Ultrasound imaging for sensing mechanical deformation of functional muscle compartments can overcome several limitations of sEMG, including the inability to differentiate between deep contiguous muscle compartments, low signal-to-noise ratio, and lack of a robust graded signal. The objective of this study was to evaluate the feasibility of real-time graded control using a computationally efficient method to differentiate between complex hand motions based on ultrasound imaging of forearm muscles. Dynamic ultrasound images of the forearm muscles were obtained from six able-bodied volunteers and analyzed to map muscle activity based on the deformation of the contracting muscles during different hand motions. Each participant performed 15 different hand motions, including digit flexion, different grips (i.e., power grasp and pinch grip), and grips in combination with wrist pronation. During the training phase, we generated a database of activity patterns corresponding to different hand motions for each participant. During the testing phase, novel activity patterns were classified using a nearest neighbor classification algorithm based on that database. The average classification accuracy was 91%. Real-time image-based control of a virtual hand showed an average classification accuracy of 92%. Our results demonstrate the feasibility of using ultrasound imaging as a robust muscle–computer interface. Potential clinical applications include control of multiarticulated prosthetic hands, stroke rehabilitation, and fundamental investigations of motor control and biomechanics.
  • References (53)
  • Citations (18)
Cite
References53
Newest
Published on Oct 1, 2014in IEEE Transactions on Haptics2.76
Franck Gonzalez3
Estimated H-index: 3
(University of Paris),
Florian Gosselin9
Estimated H-index: 9
,
Wael Bachta8
Estimated H-index: 8
(University of Paris)
Manual human-computer interfaces for virtual reality are designed to allow an operator interacting with a computer simulation as naturally as possible. Dexterous haptic interfaces are the best suited for this goal. They give intuitive and efficient control on the environment with haptic and tactile feedback. This paper is aimed at helping in the choice of the interaction areas to be taken into account in the design of such interfaces. The literature dealing with hand interactions is first review...
Published on Sep 1, 2014in Expert Systems With Applications4.29
Iker Mesa3
Estimated H-index: 3
(Centro de Estudios e Investigaciones Técnicas de Gipuzkoa),
Angel Rubio19
Estimated H-index: 19
(University of Navarra)
+ 2 AuthorsJavier Diaz3
Estimated H-index: 3
(Centro de Estudios e Investigaciones Técnicas de Gipuzkoa)
Abstract The objective of this research is to select a reduced group of surface electromyographic (sEMG) channels and signal-features that is able to provide an accurate classification rate in a myoelectric control system for any user. To that end, the location of 32 sEMG electrodes placed around-along the forearm and 86 signal-features are evaluated simultaneously in a static-hand gesture classification task (14 different gestures). A novel multivariate variable selection filter method named mR...
Siddhartha Sikdar16
Estimated H-index: 16
(GMU: George Mason University),
Huzefa Rangwala18
Estimated H-index: 18
(GMU: George Mason University)
+ 5 AuthorsJoseph J. Pancrazio15
Estimated H-index: 15
(GMU: George Mason University)
Recently there have been major advances in the electro-mechanical design of upper extremity prosthetics. However, the development of control strategies for such prosthetics has lagged significantly behind. Conventional noninvasive myoelectric control strategies rely on the amplitude of electromyography (EMG) signals from flexor and extensor muscles in the forearm. Surface EMG has limited specificity for deep contiguous muscles because of cross talk and cannot reliably differentiate between indiv...
Lukai Liu4
Estimated H-index: 4
,
Pu-Kun Liu2
Estimated H-index: 2
+ 2 AuthorsKevin Englehart36
Estimated H-index: 36
(UNB: University of New Brunswick)
Time and frequency domain features of the surface electromyogram (EMG) signal acquired from multiple channels have frequently been investigated for use in controlling upper-limb prostheses. A common control method is EMG-based motion classification. We propose the use of EMG signal whitening as a preprocessing step in EMG-based motion classification. Whitening decorrelates the EMG signal and has been shown to be advantageous in other EMG applications including EMG amplitude estimation and EMG-fo...
Published on May 1, 2013in Computer Methods and Programs in Biomedicine3.42
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)
Driver distraction is regarded as a significant contributor to motor-vehicle crashes. One of the important factors contributing to driver distraction was reported to be the handling and reaching of in-car electronic equipment and controls that usually requires taking the drivers' hands off the wheel and eyes off the road. To minimize the amount of such distraction, we present a new control scheme that senses and decodes the human muscles signals, denoted as Electromyogram (EMG), associated with ...
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...
Claudio Castellini26
Estimated H-index: 26
,
Georg Passig8
Estimated H-index: 8
,
Emanuel Zarka1
Estimated H-index: 1
(DLR: German Aerospace Center)
Medical ultrasound imaging is a well-known technique to gather live views of the interior of the human body. It is totally safe, it provides high spatial and temporal resolution, and it is nowadays available at any hospital. This suggests that it could be used as a human-computer interface. In this paper, we use ultrasound images of the human forearm to predict the finger positions, including thumb adduction and thumb rotation. Our experimental results show that there is a clear linear relations...
Published on Oct 1, 2012in Ultrasound in Medicine and Biology2.21
Jun Shi16
Estimated H-index: 16
(SHU: Shanghai University),
Jing-Yi Guo14
Estimated H-index: 14
(New York Chiropractic College)
+ 1 AuthorsYong-Ping Zheng34
Estimated H-index: 34
(PolyU: Hong Kong Polytechnic University)
Abstract Muscle contraction results in structural and morphologic changes of the related muscle. Therefore, finger flexion can be monitored from measurements of these morphologic changes. We used ultrasound imaging to record muscle activities during finger flexion and extracted features to discriminate different fingers' flexions using a support vector machine (SVM). Registration of ultrasound images before and after finger flexion was performed to generate a deformation field, from which angle ...
Published on Jul 1, 2012in Journal of Human Evolution3.15
Rui Diogo24
Estimated H-index: 24
(HU: Howard University),
Brian G. Richmond37
Estimated H-index: 37
(GW: George Washington University),
Bernard Wood57
Estimated H-index: 57
(GW: George Washington University)
In this paper, we explore how the results of a primate-wide higher-level phylogenetic analysis of muscle characters can improve our understanding of the evolution and homologies of the forearm and hand muscles of modern humans. Contrary to what is often suggested in the literature, none of the forearm and hand muscle structures usually present in modern humans are autapomorphic. All are found in one or more extant non-human primate taxa. What is unique is the particular combination of muscles. H...
Published on Jun 1, 2012in Journal of Electromyography and Kinesiology1.75
Heather Daley2
Estimated H-index: 2
(UNB: University of New Brunswick),
Kevin Englehart36
Estimated H-index: 36
(UNB: University of New Brunswick)
+ 1 AuthorsUsha Kuruganti10
Estimated H-index: 10
(UNB: University of New Brunswick)
Pattern recognition based control of powered upper limb myoelectric prostheses offers a means of extracting more information from the available muscles than conventional methods. By identifying repeatable patterns of muscle activity across multiple muscle sites rather than relying on independent EMG signals it is possible to provide more natural, reliable control of myoelectric prostheses. The purposes of this study were to (1) determine if participants can perform distinctive muscle activation ...
Cited By18
Newest
Published on Dec 1, 2019in Scientific Reports4.01
Ananya S. Dhawan (GMU: George Mason University), Biswarup Mukherjee3
Estimated H-index: 3
(GMU: George Mason University)
+ 7 AuthorsSiddhartha Sikdar16
Estimated H-index: 16
(GMU: George Mason University)
Technological advances in multi-articulated prosthetic hands have outpaced the development of methods to intuitively control these devices. In fact, prosthetic users often cite "difficulty of use" as a key contributing factor for abandoning their prostheses. To overcome the limitations of the currently pervasive myoelectric control strategies, namely unintuitive proportional control of multiple degrees-of-freedom, we propose a novel approach: proprioceptive sonomyographic control. Unlike myoelec...
Published on Jan 1, 2019in IEEE Sensors Journal3.08
Wei Xia , Yu Zhou1
Estimated H-index: 1
+ 2 AuthorsHonghai Liu26
Estimated H-index: 26
It is evident that non-invasive muscle-based human–machine interface (HMI) has been the research focus of human–machine interaction. To improve the performance of muscle-based HMI, it is significantly important to obtain electrophysiological and morphological changes of muscle contraction. However, there is still lacking of solution to present electrophysiological and morphological information of the same muscle at the same time. Surface electromyography (sEMG) can reflect the electrical activit...
Published on May 1, 2019in IEEE Transactions on Biomedical Engineering4.49
Jiayuan He , Henry Luo + 2 AuthorsNing Jiang27
Estimated H-index: 27
(UW: University of Waterloo)
With the ability to detect volumetric changes of contracting muscles, ultrasound (US) was a potential technique in the field of human–machine interface. Compared to the US imaging (B-mode US), the signal from a static single-element US transducer, A-mode US, was a more cost-effective and convenient way toward the real-world application, particularly the wearables. This study compared the performance of the single-channel A-mode US with single-channel surface electromyogram (sEMG) signals, one of...
Published on Feb 21, 2019in Robotics
This paper compiles and analyzes some of the most current works related to upper limb prosthesis with emphasis on man-machine interfaces. A brief introduction of the basic subjects is given to explain what a prosthesis is, what types of prostheses exist, what they serve for, how they communicate with the user (control and feedback), and what technologies are involved. The method used in this review is also discussed, as well as the cataloging process and analysis of articles for the composition ...
Published on Jan 1, 2019in Science China-technological Sciences2.18
Yu Zhou1
Estimated H-index: 1
(SJTU: Shanghai Jiao Tong University),
Jingbiao Liu (SJTU: Shanghai Jiao Tong University)+ 2 AuthorsHonghai Liu26
Estimated H-index: 26
(University of Portsmouth)
It is of great importance to decode motion dynamics of the human limbs such as the joint angle and torque in order to improve the functionality and provide more intuitive control in human-machine collaborative systems. In order to achieve feasible prediction, both the surface electromyography (sEMG) and A-mode ultrasound were applied to detect muscle deformation and motor intent. Six abled subjects were recruited to perform five trails elbow isokinetic flexion and extension, and each trail conta...
Published on Sep 1, 2018in IEEE Journal of Biomedical and Health Informatics4.22
Youjia Huang1
Estimated H-index: 1
(SJTU: Shanghai Jiao Tong University),
Xingchen Yang1
Estimated H-index: 1
(SJTU: Shanghai Jiao Tong University)
+ 3 AuthorsHonghai Liu26
Estimated H-index: 26
(University of Portsmouth)
Motions of the fingers are complex since hand grasping and manipulation are conducted by spatial and temporal coordination of forearm muscles and tendons. The dominant methods based on surface electromyography (sEMG) could not offer satisfactory solutions for finger motion classification due to its inherent nature of measuring the electrical activity of motor units at the skin's surface. In order to recognize morphological changes of forearm muscles for accurate hand motion prediction, ultrasoun...
Published in bioRxiv
Ananya S. Dhawan (GMU: George Mason University), Biswarup Mukherjee3
Estimated H-index: 3
(GMU: George Mason University)
+ -3 AuthorsSiddhartha Sikdar16
Estimated H-index: 16
(GMU: George Mason University)
Technological advances in multi-articulated prosthetic hands have outpaced the methods available to amputees to intuitively control these devices. Amputees often cite difficulty of use as a key contributing factor for abandoning their prosthesis, creating a pressing need for improved control technology. A major challenge of traditional myoelectric control strategies using surface electromyography electrodes has been the difficulty in achieving intuitive and robust proportional control of multipl...
Xingchen Yang1
Estimated H-index: 1
(SJTU: Shanghai Jiao Tong University),
Xueli Sun2
Estimated H-index: 2
(SJTU: Shanghai Jiao Tong University)
+ 2 AuthorsHonghai Liu26
Estimated H-index: 26
(SJTU: Shanghai Jiao Tong University)
It is evident that surface electromyography (sEMG) based human–machine interfaces (HMI) have inherent difficulty in predicting dexterous musculoskeletal movements such as finger motions. This paper is an attempt to investigate a plausible alternative to sEMG, ultrasound-driven HMI, for dexterous motion recognition due to its characteristic of detecting morphological changes of deep muscles and tendons. A multi-channel A-mode ultrasound lightweight device is adopted to evaluate the performance of...
Published on Feb 2, 2018in Frontiers in Neurorobotics3.00
Manelle Merad2
Estimated H-index: 2
(French Institute of Health and Medical Research),
Etienne de Montalivet1
Estimated H-index: 1
(French Institute of Health and Medical Research)
+ 3 AuthorsNathanaël Jarrassé11
Estimated H-index: 11
(French Institute of Health and Medical Research)
Most transhumeral amputees report that their prosthetic device lacks functionality, citing the control strategy as a major limitation. Indeed, they are required to control several degrees of freedom with muscle groups primarily used for elbow actuation. As a result, most of them choose to have a one-degree-of-freedom myoelectric hand for grasping objects, a myoelectric wrist for pronation/supination, and a body-powered elbow. Unlike healthy upper limb movements, the prosthetic elbow joint, adjus...