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1

Measurements comparison of finger joint angles in hand postures between an sEMG armband and a sensory glove

Pallotti Antonio, Orengo Giancarlo, Saggio Giovanni

Biocybernetics and Biomedical Engineering

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2021

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Vol. 41, no. 2

605--616

EN

This study compares the simultaneous measurements of finger joint angles obtained with a myoelectric armband (Myo), composed of eight surface electromyography (sEMG) sensors mounted on an elastic support, and a data glove, equipped with ten flex sensor on metacarpal and proximal finger joints. The flexion angles of all finger joints in four hand postures, that is open hand, closed hand and grasping two 3D printed molds of different size, were measured with a manual goniometer, and used to create, for each finger joint, a linear model from the measurement of the corresponding flex sensor in an electronic glove, as well as a regression model from the simultaneous measurements of 8 sEMG sensors of the Myo armband. The regression models were extracted testing different algorithms from the Matlab Regression Learner Toolbox. The performance of the models of the two wearable devices were evaluated and compared, applying a standard test, taken from literature on sensory gloves to evaluate the repeatability, reproducibility and reliability of finger joint measurements. These results were also compared with those reported by published works that followed the same standard test, using data gloves based on different sensing technologies. This work aims to demonstrate that the sEMG armbands can be applied to register the static postures of each finger joint with almost the same accuracy of sensory gloves.

2

Muscle coordination analysis by time-varying muscle synergy extraction during cycling across various mechanical conditions

Esmaeili Javad, Maleki Ali

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

90--99

EN

Central nervous system (CNS) uses the combination of a small number of motor primitives, named muscle synergies, for simplification of motor control in human movement. The aim of this study was to investigate the muscle coordination in both leg muscles during pedaling by time-varying muscle synergy extraction. Twenty healthy subjects performed three 6-min cycling tasks over a range of rotational speed (40, 50, and 60 rpm) and resistant torque (3, 5, and 7 N/M). Surface electromyography signals were recorded during pedaling from eight muscles of the right and left lower limbs. We extracted four time-varying muscle synergies from sEMG patterns. Mean and standard deviation of the quality of the signal reconstruction (R2) for all subjects was obtained 0.9328 ± 0.0120. We investigated the similarity of muscle synergies during cycling across various mechanical conditions. We found the high degrees of similarity (>0.85) among the sets of time-varying muscle synergies across mechanical conditions and also across subjects. Our results show that the same motor control strategies for cycling are used by all subjects in various mechanical conditions.

3

Intent based recognition of walking and ramp activities for amputee using sEMG based lower limb prostheses

Hussain Tahir, Iqbal Nadeem, Maqbool Hafiz Farhan, Khan Mukhtaj, Awad Mohammed Ibrahim, Dehghani-Sanij Abbas A.

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 3

1110--1123

EN

The use of surface electromyogram (sEMG) has grown in the field of gait analysis, prostheses and exoskeleton. Surface electromyogram can directly reflect the human intention for locomotion modes and can be used as a source of control for lower limb prosthesis. The variations factors such as non-Gaussian nature of sEMG signal and mobility of amputees have been observed to degrade the activity recognition performance. This study investigates the properties of the sEMG signal with the purpose of determining the discriminant features to classify the feature space into various activities especially in the context of amputees. To address the variations in activity recognition performance, this study proposed the magnitude of bispectrum as a novel feature extraction method that is invariant to the variations factors and an unsupervised feature reduction method was used to extract the discriminant features. Furthermore, sEMG signals from eleven wearable sensors located on the lower limb muscles were recorded from six subjects including four able-bodies, one unilateral transti-bial, and one unilateral transfemoral amputee during walking and ramp activities. Distinct muscles were selected using the L1-norm method. Effective classifier namely support vector machine and linear discriminant analysis were used to classify the multi-class sEMG signal patterns. The experimental results consistently showed an average accuracy of 99.7%. Further evaluation on three different types of prostheses revealed that the proposed method is more robust compared to the existing methods. The promising results of this study can be applied potentially in the control of lower limb wearable devices such as prostheses/ exoskeletons.

4

A new method of diagnosing athlete's anterior cruciate ligament health status using surface electromyography and deep convolutional neural network

Hatamzadeh Mehran, Hassannejad Reza, Sharifnezhad Ali

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

65--76

EN

Anterior cruciate ligament (ACL) injury is one of the most common injuries in high-demand sports. Due to long-term treatment of this injury, diagnosing recovery of ACL becomes important, particularly six months postoperatively. The purpose of this research is to provide a cost-effective and intelligent method to diagnose ACL's health status. For this purpose, 11 healthy and 27 ACL-injured subjects have been selected. In the proposed method, the athlete performs a single-leg landing protocol and surface electromyographic signals (EMG) are taken from eight lower limb muscles. Then, time–frequency distributions of EMG signals in each landing are calculated as an image, using pseudo Wigner–Ville distribution (PWVD), which are the inputs of a deep convolutional neural network (DCNN). By time–frequency analysis, it has been made clear that any change in ACL's health status causes changes in the extent of energy spread in PWVD, distribution volume, frequency content, damping rate and the peak value of EMG signals. In this research, a new relationship between ACL's health status and lower limb muscles activity is introduced through monitoring of PWVD images. The result indicates that the designed expert system is able to diagnose ACL's health status with 95.8% accuracy. In this non-invasive method, PWVD images of EMG signals are chosen as the inputs of DCNN, instead of MRI images, which, in addition to their high accuracy in diagnosing, are safer and much cheaper. The presented method can play an important role in assessing the recovery process, six months postoperatively and after that.

5

Machine learning-based novel approach to classify the shoulder motion of upper limb amputees

Amanpreet Kaur

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 3

857--867

EN

An upper limb amputation is a traumatic event that can seriously affect the person's capacity to perform regular tasks and can lead individuals to lose their confidence and autonomy. Prosthetic devices can be controlled via the acquisition and processing of electromyogram signal produced at the muscles fiber from the surface of the body with an array of an electrode placed on the residual limb. This paper presents the feasibility of classifying the different shoulder movements from around shoulder muscles of transhumeral amputees. The performance of a classifier is affected by the variation of Surface Electromyography (sEMG) signals due to the different categories of contraction. To avoid this, the wavelet transform and data transformation method are employed for features extraction from sEMG signals. Afterward five different supervised machine learning techniques viz. Support Vector Machines (SVM), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN) and Naïve Bayes (NB) are applied to determine the different classifiers accuracy. An effective combination of wavelet and RF achieves the best performance with a total classification accuracy of 98%.

6

A speech recognition system based on electromyography for the rehabilitation of dysarthric patients: A Thai syllable study

Sae Jong Nida, Phukpattaranont Pornchai

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 1

234--245

EN

The objective of this study is to develop a speech recognition system for classifying nine Thai syllables, which is used for the rehabilitation of dysarthric patients, based on five channels of surface electromyography (sEMG) signals from the human articulatory muscles. After the sEMG signal from each channel was collected, it was processed by a band-pass filter from 20–450 Hz for noise removal. Then, six features from three feature categories were determined and analyzed, namely, mean absolute value (MAV) and wavelength (WL) from amplitude based features (ABF), zero crossing (ZC) and mean frequency (MNF) from frequency based features (FBF), and L-kurtosis (L-KURT) and L-skewness (L-SKW) from statistics based features (SBF). Subsequently, a spectral regression extreme learning machine (SRELM) was used as the feature projection technique to reduce the dimension of feature vector from 30 to 8. Finally, the projected features were classified using a feed forward neural network (NN) classifier with 5-fold cross-validation. The proposed system was evaluated with the sEMG signals from seven healthy volunteers and five dysarthric volunteers. The results show that the proposed system can recognize the sEMG signals from both healthy and dysarthric volunteers. The average classification accuracies obtained from all six features in the healthy and dysarthric volunteers were 94.5% and 89.4%, respectively.

7

Opracowanie metod wykonywania badań biomechaniki ruchu człowieka przy wykorzystaniu elektromiografii kinezjologicznej

Kukla Mateusz, Wieczorek Bartosz, Warguła Łukasz

Autobusy : technika, eksploatacja, systemy transportowe

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2019

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R. 20, nr 1-2

295--298

PL

W artykule przedstawiono zagadnienia dotyczące opracowania metod wykonywania badań biomechaniki ruchu człowieka przy wykorzystaniu elektromiografii kinezjologicznej. Szczegółowo omówiono utworzone procedury dotyczące wyboru umiejscowienia elektrod, przygotowania pacjenta do badań, przeprowadzania eksperymentu oraz opracowania wyników pomiarów. Przedstawiono również wybrane wyniki badań wstępnych.

EN

The article presents the issues concerning the development of methods for performing human biomechanics research utilizing kinesiological electromyography. The procedures concerning the selection of the location of electrodes, patient preparation for testing, conducting the experiment and the development of measurement results are discussed in detail. Selected preliminary test results were also presented.

8

Use of the surface electromyography for a quantitative trend validation of estimated muscle forces

Żuk M., Syczewska M., Pezowicz C.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 2

243--250

EN

Surface EMG is a non-invasive measurement of an individual muscle activity and it can be used as the indirect form of a simulated muscle forces validation. The quantitative curves comparison has some potential, which has not been fully exploited yet [13]. The purpose of current study was to quantitatively compare muscle forces predicted using musculoskeletal models to measured surface electromyography signals. A metrics based on correlation and an electromechanical delay correction for a quantitative trend validation has been proposed. Kinematics of a normal gait was collected for three healthy subjects together with ground reaction forces and EMG signals of eight different muscles of both legs. Dynamic simulations have been performed for two models of differing complexity from OpenSim library (Gait2392 and Gait2354) [2,5,6], static optimization method and computed muscle control algorithm [20] have been used. It has been shown, that the level of force-EMG trend compliance, obtained for applied models and simulation techniques, is related rather to the selected muscle than to applied optimization criteria or technique. The contribution of analyzed muscles during gait has been predicted better by complex model than by simplified model. Moreover relationship between the body proportion of subject and the degree of correlation has been observed. Proposed metrics and obtained results can be the basis for further identification of cost functions, which could most closely describe motor control strategy.

9

Komputerowo wspomagana klasyfikacja wybranych sygnałów elektromiografii powierzchniowej

Rzyman G., Redlarski G., Krawczuk M.

Modelowanie Inżynierskie

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2017

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T. 31, nr 62

81--87

PL

Wykorzystywanie sygnałów elektromiografii powierzchniowej (ang. Surface Electromyography, SEMG) w procesach sterowania systemami rehabilitacyjnymi stanowi obecnie standardową procedurę. Popularność SEMG wynika z nieinwazyjności metody oraz możliwości szybkiej i precyzyjnej identyfikacji funkcji mięśniowej. W przypadku osób małoletnich proces klasyfikacji sygnałów jest utrudniony ze względu na mniejsze rozmiary i wyższą dynamikę aktywności włókien mięśniowych niż u osób dorosłych. W związku z powyższymi uwagami, w artykule przedstawiono wyniki badań zwiększających wskaźnik poprawnej klasyfikacji wybranych ruchów dłoni dzieci. Omówiono zastosowane do tego celu modele matematyczne: k-najbliższych sąsiadów, drzewo decyzyjne oraz metodę wektorów nośnych; a także zastosowane miary i metodykę „strojenia” parametrów modeli.

EN

Overarching objective of this paper is classification of basic hand gestures by surface electromyography for healthy children. Main difference between biosignals corresponding to adults and children muscle activity is disparate growth of muscles. For this reason youngsters need separate method of signals classification. In this paper we decide to create a mathematical model and compare three classification method: a support vector machine, k nearest neighbors and decision tree methods. Furthermore we used the best set of time domain (MAV, WAMP, WL and SSC) and selected several parameters to make each model as good as possible.

10

Możliwości zastosowania sygnałów bioelektrycznych (EMG) w systemach sterowania

Kegler M., Jasińska-Choromańska D., Fiok K.

Inżynier i Fizyk Medyczny

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2016

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Vol. 5, nr 6

329--334

PL

W dobie rozwoju inżynierii biomedycznej, technologie mające dotychczas zastosowanie jedynie w diagnostyce klinicznej zyskują coraz większą popularność w dziedzinach niebezpośrednio związanych z medycyną. W artykule przedstawiono przykłady możliwego zastosowania sygnałów elektromiograficznych (EMG) w systemach sterowania.

EN

In times of rapid development of biomedical engineering, technologies previously used exclusively in clinical diagnostics are becoming increasingly popular and applicable in other fields, less related to medicine. The examples of successful applications of control systems based on electromyographic (EMG) biosignals, are introduced in the article.

11

Zastosowanie EMG do analizy wybranych ruchów kończyny górnej

Morawska N., Wojnicz W., Stawicki M.

Aktualne Problemy Biomechaniki

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2016

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z. 11

103--108

PL

Celem badań było przeprowadzenie pomiarów sygnału mioelektrycznego czterech mięśni powierzchniowych lewej kończyny górnej, biorących udział w ruchach zginania-prostowania w stawie łokciowym w płaszczyźnie strzałkowej. Rejestrację elektromiogramów (EMG) odprowadzono z: głowy długiej oraz bocznej mięśnia trójgłowego ramienia, głowy długiej mięśnia dwugłowego ramienia i mięśnia ramienno-promieniowego. Wykazano, iż metoda może zostać wykorzystana do oceny funkcjonowania wybranych mięśni.

EN

The aim of the study was to perform measurements of the sEMG signal for the analysis of the four surface muscles of the left upper limb participating in the flexion-extension movements at the elbow in the sagittal plane. Electromyography signal was measured and registered from the long head and lateral head of the triceps of the arm, the long head of the biceps and muscle brachioradialis. It has been shown that this method can be used to evaluate functioning of selected muscles.

12

The muscle activation patterns of lower limb during stair climbing at different backpack load

Yali H., Aiguo S., Haitao G., Songqing Z.

Acta of Bioengineering and Biomechanics

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2015

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Vol. 17, no. 4

13--20

EN

Stair climbing under backpack load condition is a challenging task. Understanding muscle activation patterns of lower limb during stair climbing with load furthers our understanding of the factors involved in joint pathology and the effects of treatment. At the same time, stair climbing under backpack load requires adjustments of muscle activations and increases joint moment compared to level walking, which with muscle activation patterns are altered as a result of using an assistive technology, such as a wearable exoskeleton leg for human walking power augmentation. Therefore, the aim of this study was to analyze lower limb muscles during stair climbing under different backpack load. Nine healthy volunteers ascended a four-step staircase at different backpack load (0 kg, 10 kg, 20 kg, 30 kg). Electromyographic (EMG) signals were recorded from four lower limb muscles (gastrocnemius, tibialis anterior, hamstring, rectus femoris). The results showed that muscle activation amplitudes of lower limb increase with increasing load during stair climbing, the maximum RMS of gastrocnemius are greater than tibialis anterior, hamstring and rectus femoris whether stair climbing or level walking under the same load condition. However, the maximum RMS of hamstring are smaller than gastrocnemius, tibialis anterior and rectus femoris. The study of muscle activation under different backpack load during stair climbing can be used to design biomechanism and explore intelligent control based on EMG for a wearable exoskeleton leg for human walking power augmentation.

13

Hip strategy alterations in patients with history of low disc herniation and non-specific low back pain measured by surface electromyography and balance platform

Ciesielska J., Lisiński P., Bandosz A., Huber J., Kulczyk A., Lipiec J.

Acta of Bioengineering and Biomechanics

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2015

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Vol. 17, no. 3

103--108

EN

Purpose: The appearance of pathology in the lumbar spine, such as a previous episode of low disc herniation or non-specific low back pain contributes to improper activation of the hip muscles. The aim of the study was to detect alterations in hip strategy manifested by differences in balance parameters and rectus femoris and gluteus maximus activity in people with previous episode of pain radiation to one lower limb caused by low disc herniation or non-specific low back pain. Methods: We studied 11 patients with history of low-disc herniation, 9 patients with history of non-specific low back pain and 10 healthy subjects. Hip strategy alterations were detected by measuring rectus femoris and gluteus maximus activity in bilateral surface polyelectromyographic recordings and by stability measurements on a balance platform. Results: In the surface polyelectromyography study, in both patients' group the value of the average amplitude was higher and the amount of the fluctuations was lower than in healthy subjects. There were no significant differences in stability parameters. Conclusions: A changed pattern of hip muscles activity was detected in the patients without changes in stability parameters. Greater disorder occurs in people in with previous episode of pain radiation to one lower limb caused by low disc herniation than in people with non-specific low back pain.

14

Określanie sił mięśniowych podczas chodu na podstawie sygnałów sEMG

Świtoński E., Głowacka A.

Modelowanie Inżynierskie

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2013

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T. 16, nr 47

185--189

PL

Praca zawiera opis metodyki wyznaczania sił mięśniowych na podstawie zarejestrowanych potencjałów czynnościowych mięśni kończyn dolnych podczas chodu dla zdrowej dorosłej osoby. Badania w ramach niniejszej pracy zostały przeprowadzone z wykorzystaniem zestawu do elektromiografii powierzchniowej BTS Pocket EMG.

EN

The paper contains a description of the methodology for determination of muscle forces on the basis of recorded action potentials of lower limb muscles during gait for a healthy adult. The research in this study were conducted using BTS Pocket EMG surface electromyography system.

15

Surface electromyography for assessing triceps brachii muscle activities: a literature review

Ali A., Sundaraj K., Ahmad R. B., Ahamed N. U., Islam A.

Biocybernetics and Biomedical Engineering

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2013

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Vol. 33, no. 4

187--195

EN

The goal of this review was to summarise the scientific findings of research conducted on the triceps brachii muscle using surface electromyography. To achieve this goal, we searched through several articles available from the online databases ScienceDirect and SpringerLink published in the English language between January 2008 and June 2012. We specifically searched for the phrases ‘‘EMG’’ and ‘‘triceps brachii’’ in the title, abstract, keywords or methods sections. From a total of 569 articles we identified 77 potentially relevant studies where 42 studies have been examined triceps brachii muscle activity using surface electromyography that applied in the field of rehabilitation, physiological exercise, sports, and prosthesis control. Among the 42 articles found, 16 studies have been examined triceps brachii muscle activity in rehabilitation, 13 for physiological exercise, 9 for sports, and 4 for prosthesis control in this literature review. We therefore believe that the information contained in this review will greatly assist and guide the progress of studies that use surface electromyography to measure triceps brachii muscle activity in the context of rehabilitation, physiological exercise, sports, and prosthesis control.

16

Changes of bioelectrical activity in cervical paraspinal muscle during gait in low and high heel shoes

Mika A., Oleksy Ł., Mikołajczyk E., Marchewka A., Mika P.

Acta of Bioengineering and Biomechanics

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2011

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Vol. 13, no. 1

27-33

EN

High heel footwear may be destructive for the spine because of an increased erector spinae muscle bioelectrical activity and increased ground reaction forces affecting lower limbs and the spine. The aim of this study was to evaluate the changes of bioelectrical activity in cervical paraspinal muscle during gait in low and in high heel shoes in different age groups. In 31 women aged 20-25 years and in 15 women aged 45-55 years without neck pain, the bioelectrical activity of the cervical paraspinal muscle was assessed during gait on flat surface with natural speed in three conditions: without shoes, in low (4 cm) and in high (10 cm) heel shoes. Higher bioelectrical activity cervical paraspinal muscle was noted during gait in high heel shoes in comparison to gait without shoes. The changes were more pronounced in the group of subjects aged 45-55 years. The prolonged wearing of shoes with stiletto type heels by individuals without neck pain is not safe for their spine and may lead to chronic paraspinal muscle fatigue.

17

Adaptacyjny system sterowania protezą ręki wykorzystujący elektromiografię powierzchniową

Gmerek A.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2010

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z. 175, t. 1

99-110

PL

Skuteczne sterowanie protezami kończyn o wielu stopniach swobody jest trudnym zadaniem, które wymaga innowacyjnego podejścia do zagadnienia sterowania. W nowoczesnych protezach do tego celu używa się sygnałów biologicznych natury elektrycznej. Autor eksperymentował z sygnałami EMG (elektromiograficznymi), rejestrowanymi za pomocą tzw. elektromiografii powierzchniowej. W artykule tym do sterowania skonstruowaną protezą ręki został zaproponowany algorytm bazujący na sztucznych sieciach neuronowych (SSN) i logice rozmytej. W celu wyodrębnienia unikalnych cech analizowanych sygnałów (potrzebnych na wejście sieci), były one poddawane wieloetapowemu procesowi przetwarzania i obróbki.

EN

An effective control of multi-DOF limb prosthesis is a difficult task, which require innovative approach to the problem. In high-tech limb prosthesis the electrical-nature biological signals are used for this task. Author experimented with EMG (electromyographic) signals, registered with a surface electromyography. In this paper for control a constructed artificial limb an algorithm based on Artificial Neural Networks (ANN) and Fuzzy Logic was proposed. In order to extract unique features of analyzed signals (needed for input of the net), they were expose to multi-level procedure of signal processing.