Match!

Classification complexity in myoelectric pattern recognition

Published on Dec 1, 2017in Journal of Neuroengineering and Rehabilitation3.582
· 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 Ortiz-Catalan11
Estimated H-index: 11
(Chalmers University of Technology)
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 (6)
📖 Papers frequently viewed together
2016ICPR: International Conference on Pattern Recognition
1 Citations
437 Citations
50 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
References28
Newest
#1Max Ortiz-Catalan (Chalmers University of Technology)H-Index: 11
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...
11 CitationsSource
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...
64 CitationsSource
#1M Ortiz-Rios (MPG: Max Planck Society)H-Index: 3
#2Paweł Kuśmierek (GUMC: Georgetown University Medical Center)H-Index: 8
Last. Josef P. Rauschecker (Aalto University)H-Index: 57
view all 9 authors...
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...
158 CitationsSource
#1Xiaorong Zhang (SFSU: San Francisco State University)H-Index: 7
#2He Huang (UNC: University of North Carolina at Chapel Hill)H-Index: 23
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...
23 CitationsSource
#1Max Ortiz-Catalan (Chalmers University of Technology)H-Index: 11
#2Bo Håkansson (Chalmers University of Technology)H-Index: 28
Last. Rickard Brånemark (Sahlgrenska University Hospital)H-Index: 33
view all 3 authors...
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...
53 CitationsSource
#1Jie Liu (Rehabilitation Institute of Chicago)H-Index: 10
#2Xiaoyan Li (University of Texas Health Science Center at Houston)H-Index: 15
Last. Ping Zhou (USTC: University of Science and Technology of China)H-Index: 12
view all 4 authors...
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...
20 CitationsSource
#1Johannes Stelzer (MPG: Max Planck Society)H-Index: 9
#2Tilo Buschmann (Fraunhofer Society)H-Index: 8
Last. Robert Turner (MPG: Max Planck Society)H-Index: 90
view all 6 authors...
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...
413 CitationsSource
#1Max Ortiz-Catalan (Chalmers University of Technology)H-Index: 11
#2Nichlas Sander (Chalmers University of Technology)H-Index: 1
Last. Rickard Brånemark (Sahlgrenska University Hospital)H-Index: 33
view all 5 authors...
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...
83 CitationsSource
10 CitationsSource
#1Max Ortiz-Catalan (Chalmers University of Technology)H-Index: 11
#2Rickard Brånemark (Sahlgrenska University Hospital)H-Index: 33
Last. Bo Håkansson (Chalmers University of Technology)H-Index: 28
view all 3 authors...
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 ...
81 CitationsSource
Cited By6
Newest
#1Morten B. Kristoffersen (UMCG: University Medical Center Groningen)H-Index: 2
#2Andreas Franzke (UMCG: University Medical Center Groningen)
Last. Raoul M. Bongers (UMCG: University Medical Center Groningen)H-Index: 19
view all 5 authors...
Human-machine interfaces have not yet advanced to enable intuitive control of multiple degrees of freedom as offered by modern myoelectric prosthetic hands. Pattern Recognition (PR) control has been proposed to make human-machine interfaces in myoelectric prosthetic hands more intuitive, but it requires the user to generate high-quality, i.e., consistent and separable, electromyogram (EMG) patterns. To generate such patterns, user training is required and has shown promising results. However, ho...
Source
Jul 1, 2019 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Max Ortiz-Catalan (Chalmers University of Technology)H-Index: 11
#2Alexandra Middleton (Princeton University)
Last. Magnus Gustafsson (Chalmers University of Technology)H-Index: 6
view all 3 authors...
The number of published peer-reviewed research articles has increased exponentially in the past decades, as has the degree of competitiveness in scientific publishing. Publication of scientific articles remains the gold standard for measuring research quality. In this context, quality is understood as to how rigorously the scientific method was applied. However, a critical disconnect exists between the continuous channel of projects fed to students by research laboratories, and the scientific qu...
Source
#1Carlos A. Gómez (Harvard University)H-Index: 1
#2Buyin Fu (Harvard University)H-Index: 4
Last. Mohammad A. Yaseen (Harvard University)H-Index: 19
view all 4 authors...
Disruptions and alterations to cerebral energy metabolism play a vital role in the onset and progression of many neurodegenerative disorders and cerebral pathologies. In order to precisely understand the complex alterations underlying Alzheimer’s disease (AD) progression, in vivo imaging at the microscopic level is required in preclinical animal models. Utilizing two-photon fluorescence lifetime imaging microscopy and the phasor analysis method, we have observed AD-related variations of endogeno...
Source
#1Geng Yang (ZJU: Zhejiang University)H-Index: 11
#2Jia Deng (ZJU: Zhejiang University)H-Index: 3
Last. Huayong Yang (ZJU: Zhejiang University)H-Index: 1
view all 12 authors...
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...
11 CitationsSource
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...
4 CitationsSource
#1Linda Resnik (Brown University)H-Index: 23
#2He Huang (UNC: University of North Carolina at Chapel Hill)H-Index: 23
Last. Nancy Wolk (UNC: University of North Carolina at Chapel Hill)H-Index: 1
view all 6 authors...
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...
14 CitationsSource
#1Antonio Clim (Bucharest University of Economic Studies)
#2Răzvan Daniel Zota (Bucharest University of Economic Studies)H-Index: 1
view all 3 authors...
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...
Source