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Classification complexity in myoelectric pattern recognition

Published on Dec 1, 2017in Journal of Neuroengineering and Rehabilitation3.58
· DOI :10.1186/s12984-017-0283-5
Niclas Nilsson1
Estimated H-index: 1
(Chalmers University of Technology),
Bo Håkansson28
Estimated H-index: 28
(Chalmers University of Technology),
Max Jair Ortiz-Catalan9
Estimated H-index: 9
(Chalmers University of Technology)
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Abstract
Background: Limb prosthetics, exoskeletons, and neurorehabilitation devices can be intuitively controlled using myoelectric pattern recognition (MPR) to decode the subject's intended movement. In conventional MPR, descriptive electromyography (EMG) features representing the intended movement are fed into a classification algorithm. The separability of the different movements in the feature space significantly affects the classification complexity. Classification complexity estimating algorithms (CCEAs) were studied in this work in order to improve feature selection, predict MPR performance, and inform on faulty data acquisition. Methods: CCEAs such as nearest neighbor separability (NNS), purity, repeatability index (RI), and separability index (SI) were evaluated based on their correlation with classification accuracy, as well as on their suitability to produce highly performing EMG feature sets. SI was evaluated using Mahalanobis distance, Bhattacharyya distance, Hellinger distance, Kullback-Leibler divergence, and a modified version of Mahalanobis distance. Three commonly used classifiers in MPR were used to compute classification accuracy (linear discriminant analysis (LDA), multi-layer perceptron (MLP), and support vector machine (SVM)). The algorithms and analytic graphical user interfaces produced in this work are freely available in BioPatRec. Results: NNS and SI were found to be highly correlated with classification accuracy (correlations up to 0.98 for both algorithms) and capable of yielding highly descriptive feature sets. Additionally, the experiments revealed how the level of correlation between the inputs of the classifiers influences classification accuracy, and emphasizes the classifiers' sensitivity to such redundancy. Conclusions: This study deepens the understanding of the classification complexity in prediction of motor volition based on myoelectric information. It also provides researchers with tools to analyze myoelectric recordings in order to improve classification performance.
  • References (28)
  • Citations (4)
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References28
Newest
Published on Oct 29, 2015in Frontiers in Neuroscience3.65
Max Jair Ortiz-Catalan9
Estimated H-index: 9
(Chalmers University of Technology)
Accurate descriptors of muscular activity play an important role in clinical practice and rehabilitation research. Such descriptors are features of myoelectric signals extracted from sliding time windows. A wide variety of myoelectric features have been used as inputs to pattern recognition algorithms that aim to decode motor volition. The output of these algorithms can then be used to control limb prostheses, exoskeletons, and rehabilitation therapies. In the present study, cardinality is intro...
Simone Benatti8
Estimated H-index: 8
,
Filippo Casamassima6
Estimated H-index: 6
+ 6 AuthorsLuca Benini79
Estimated H-index: 79
Wearable devices offer interesting features, such as low cost and user friendliness, but their use for medical applications is an open research topic, given the limited hardware resources they provide. In this paper, we present an embedded solution for real-time EMG-based hand gesture recognition. The work focuses on the multi-level design of the system, integrating the hardware and software components to develop a wearable device capable of acquiring and processing EMG signals for real-time ges...
Published on Apr 1, 2015in Frontiers in Neuroscience3.65
M Ortiz-Rios2
Estimated H-index: 2
(MPG: Max Planck Society),
Paweł Kuśmierek8
Estimated H-index: 8
(GUMC: Georgetown University Medical Center)
+ 6 AuthorsJosef P. Rauschecker55
Estimated H-index: 55
(Aalto University)
Using functional magnetic resonance imaging in awake behaving monkeys we investigated how species-specific vocalizations are represented in auditory and auditory-related regions of the macaque brain. We found clusters of active voxels along the ascending auditory pathway that responded to various types of complex sounds: inferior colliculus (IC), medial geniculate nucleus (MGN), auditory core, belt, and parabelt cortex, and other parts of the superior temporal gyrus (STG) and sulcus (STS). Regio...
Published on Jan 1, 2015in Journal of Neuroengineering and Rehabilitation3.58
Xiaorong Zhang6
Estimated H-index: 6
(SFSU: San Francisco State University),
He Huang21
Estimated H-index: 21
(UNC: University of North Carolina at Chapel Hill)
Background Unreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern cla...
Max Jair Ortiz-Catalan9
Estimated H-index: 9
(Chalmers University of Technology),
Bo Håkansson28
Estimated H-index: 28
(Chalmers University of Technology),
Rickard Brånemark33
Estimated H-index: 33
(Sahlgrenska University Hospital)
The prediction of simultaneous limb motions is a highly desirable feature for the control of artificial limbs. In this work, we investigated different classification strategies for individual and simultaneous movements based on pattern recognition of myoelectric signals. Our results suggest that any classifier can be potentially employed in the prediction of simultaneous movements if arranged in a distributed topology. On the other hand, classifiers inherently capable of simultaneous predictions...
Published on Jul 1, 2014in Medical Engineering & Physics1.78
Jie Liu8
Estimated H-index: 8
(Rehabilitation Institute of Chicago),
Xiaoyan Li14
Estimated H-index: 14
(University of Texas Health Science Center at Houston)
+ 1 AuthorsPing Zhou10
Estimated H-index: 10
(USTC: University of Science and Technology of China)
Myoelectric pattern recognition with a large number of electromyogram (EMG) channels provides an approach to assessing motor control information available from the recorded muscles. In order to develop a practical myoelectric control system, a feature dependent channel reduction method was developed in this study to determine a small number of EMG channels for myoelectric pattern recognition analysis. The method selects appropriate raw EMG features for classification of different movements, usin...
Published on Apr 16, 2014in Frontiers in Neuroscience3.65
Johannes Stelzer8
Estimated H-index: 8
(MPG: Max Planck Society),
Tilo Buschmann6
Estimated H-index: 6
(Fraunhofer Society)
+ 3 AuthorsRobert Turner41
Estimated H-index: 41
(MPG: Max Planck Society)
Although ultra-high-field fMRI at field strengths of 7T or above provides substantial gains in BOLD contrast-to-noise ratio, when very high-resolution fMRI is required such gains are inevitably reduced. The improvement in sensitivity provided by multivariate analysis techniques, as compared with univariate methods, then becomes especially welcome. Information mapping approaches are commonly used, such as the searchlight technique, which take into account the spatially distributed patterns of act...
Published on Jan 1, 2014in Frontiers in Neuroscience3.65
Max Jair Ortiz-Catalan9
Estimated H-index: 9
(Chalmers University of Technology),
Nichlas Sander1
Estimated H-index: 1
(Chalmers University of Technology)
+ 2 AuthorsRickard Brånemark33
Estimated H-index: 33
(Sahlgrenska University Hospital)
A variety of treatments have been historically used to alleviate phantom limb pain (PLP) with varying efficacy. Recently, virtual reality (VR) has been employed as a more sophisticated mirror therapy. Despite the advantages of VR over a conventional mirror, this approach has retained the use of the contralateral limb and is therefore restricted to unilateral amputees. Moreover, this strategy disregards the actual effort made by the patient to produce phantom motions. In this work, we investigate...
Published on Dec 1, 2013in Source Code for Biology and Medicine
Max Jair Ortiz-Catalan9
Estimated H-index: 9
(Chalmers University of Technology),
Rickard Brånemark33
Estimated H-index: 33
(Sahlgrenska University Hospital),
Bo Håkansson28
Estimated H-index: 28
(Chalmers University of Technology)
Background Processing and pattern recognition of myoelectric signals have been at the core of prosthetic control research in the last decade. Although most studies agree on reporting the accuracy of predicting predefined movements, there is a significant amount of study-dependent variables that make high-resolution inter-study comparison practically impossible. As an effort to provide a common research platform for the development and evaluation of algorithms in prosthetic control, we introduce ...
Cited By4
Newest
Published on Dec 1, 2018in Journal of Neuroengineering and Rehabilitation3.58
Linda Resnik23
Estimated H-index: 23
(Brown University),
He Huang21
Estimated H-index: 21
(UNC: University of North Carolina at Chapel Hill)
+ 3 AuthorsNancy Wolk1
Estimated H-index: 1
(UNC: University of North Carolina at Chapel Hill)
Background Although electromyogram (EMG) pattern recognition (PR) for multifunctional upper limb prosthesis control has been reported for decades, the clinical benefits have rarely been examined. The study purposes were to: 1) compare self-report and performance outcomes of a transradial amputee immediately after training and one week after training of direct myoelectric control and EMG pattern recognition (PR) for a two-degree-of-freedom (DOF) prosthesis, and 2) examine the change in outcomes o...
Published on May 1, 2018in Sensors3.03
Karina O. A. Moura2
Estimated H-index: 2
,
Alexandre Balbinot7
Estimated H-index: 7
A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. Th...
Published on Jan 1, 2018in Procedia Computer Science
Antonio Clim (Bucharest University of Economic Studies), Răzvan Daniel Zota2
Estimated H-index: 2
(Bucharest University of Economic Studies),
Grigore TinicĂ
Abstract Kullback-Leibler divergence class or relative entropy is an exceptional instance of a more extensive divergence. It is an estimation of how a particular dissemination wanders from another, normal likelihood appropriation. Kullback-Leibler divergence has a considerable measure of ongoing applications. Despite the fact that there is an advance in the drug field, it still requires a measurable examination for supporting developing prerequisites. This paper discusses the use of Kullback-Lei...
Geng Yang9
Estimated H-index: 9
(ZJU: Zhejiang University),
Jia Deng2
Estimated H-index: 2
(ZJU: Zhejiang University)
+ 9 AuthorsPasi Liljeberg27
Estimated H-index: 27
(UTU: University of Turku)
Surface electromyography signal plays an important role in hand function recovery training. In this paper, an IoT-enabled stroke rehabilitation system was introduced which was based on a smart wearable armband (SWA), machine learning (ML) algorithms, and a 3-D printed dexterous robot hand. User comfort is one of the key issues which should be addressed for wearable devices. The SWA was developed by integrating a low-power and tiny-sized IoT sensing device with textile electrodes, which can measu...
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