927 resultados para Emg Signals
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Um dos maiores desafios da neurofisiologia é o de compreender a forma como a informação é transmitida através do sistema nervoso. O estudo do sistema nervoso tem várias aplicações, tanto na neurologia, permitindo avanços ao nível clínico, como noutras áreas, e.g., nos sistemas de processamento de informação baseados em redes neuronais. A transmissão de informação entre neurónios é feita por via de sinais elétricos. A compreensão deste fenómeno é ainda incompleta e há projectos a nível europeu e mundial com o objetivo de modular o sistema nervoso no seu todo de forma a melhor o compreender. Uma das teses que se desenvolve hoje em dia é a de que a transmissão de sinais elétricos no sistema nervoso é influenciada por fenómenos de sincronia. O objetivo desta dissertação é o de otimizar um protocolo de aquisição e análise de dados reais de eletroencefalograma e eletromiograma com o propósito de observar fenómenos de sincronia, baseando-se num algoritmo (análise por referência de fase, ou RPA, do inglês reference phase analysis) que deteta sincronias de fase entre os sinais de eletroencefalograma (EEG) e um sinal de referência, que é, no caso presente, o eletromiograma (EMG). A otimização deste protocolo e sua validação indicaram a existência de fenómenos significativos de sincronia no sinal elétrico, transmitido entre os músculos da mão e o córtex motor, no decorrer da ação motora.
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Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods
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The repeatability of initial values and rate of change of EMG signal mean spectral frequency (MNF), average rectified values (ARV), muscle fiber conduction velocity (CV) and maximal voluntary contraction (MVC) was investigated in the vastus medialis obliquus (VMO) and vastus lateralis (VL) muscles of both legs of nine healthy male subjects during voluntary, isometric contractions sustained for 50 s at 50% MVC. The values of MVC were recorded for both legs three times on each day and for three subsequent days, while the EMG signals have been recorded twice a day for three subsequent days. The degree of repeatability was investigated using the Fisher test based upon the ANalysis Of VAriance (ANOVA), the Standard Error of the Mean (SEM) and the Intraclass Correlation Coefficient (ICC). Data collected showed a high level of repeatability of MVC measurement (normalized SEM from 1.1% to 6.4% of the mean). MNF and ARV initial values also showed a high level of repeatability (ICC > 70% for all muscles and legs except right VMO). At 50% MVC level no relevant pattern of fatigue was observed for the VMO and VL muscles, suggesting that other portions of the quadriceps might have contributed to the generated effort. These observations seem to suggest that in the investigation of muscles belonging to a multi-muscular group at submaximal level, the more selective electrically elicited contractions should be preferred to voluntary contractions. (C) 2001 Elsevier Science Ltd. All rights reserved.
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Purpose: The aims of the present study were to examine electromyographic (EMG) activity of six bilateral trunk muscles during maximal contraction in three cardinal planes, and to determine the direction of contraction that gives maximal activation for each muscle. both for healthy subjects and back-pain patients. Methods: Twenty-eight healthy subjects and 15 back-pain patients performed maximum voluntary contractions in three cardinal planes, Surface EMG signals were recorded from rectus abdominis, external oblique, internal oblique, latissimus dorsi, iliocostalis lumborum, and multifidus bilaterally. Root mean square values of the EMG data were calculated to quantify I the amplitude of EMG signals. Results: For both healthy subjects and back-pain patients. one single direction of contraction was found to give the maximum EMG signals for most muscles. Rectus abdominis demonstrated maximal activity in trunk flexion, external oblique in lateral flexion. internal oblique in axial rotation, and multifidus in extension. For the latissimus dorsi and iliocostalis lumborum. maximal activity was demonstrated in more than one cardinal plane. Conclusion: This study has implications for future research involving normalization of muscle activity to maximal levels required in many trunk EMG studies. As the latissimus dorsi and iliocostalis lumborum demonstrate individual differences in the plane that gives maximal activity, these muscles may require testing in more than one plane.
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This paper investigates the application of the Hilbert spectrum (HS), which is a recent tool for the analysis of nonlinear and nonstationary time-series, to the study of electromyographic (EMG) signals. The HS allows for the visualization of the energy of signals through a joint time-frequency representation. In this work we illustrate the use of the HS in two distinct applications. The first is for feature extraction from EMG signals. Our results showed that the instantaneous mean frequency (IMNF) estimated from the HS is a relevant feature to clinical practice. We found that the median of the IMNF reduces when the force level of the muscle contraction increases. In the second application we investigated the use of the HS for detection of motor unit action potentials (MUAPs). The detection of MUAPs is a basic step in EMG decomposition tools, which provide relevant information about the neuromuscular system through the morphology and firing time of MUAPs. We compared, visually, how MUAP activity is perceived on the HS with visualizations provided by some traditional (e.g. scalogram, spectrogram, Wigner-Ville) time-frequency distributions. Furthermore, an alternative visualization to the HS, for detection of MUAPs, is proposed and compared to a similar approach based on the continuous wavelet transform (CWT). Our results showed that both the proposed technique and the CWT allowed for a clear visualization of MUAP activity on the time-frequency distributions, whereas results obtained with the HS were the most difficult to interpret as they were extremely affected by spurious energy activity. (c) 2008 Elsevier Inc. All rights reserved.
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This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.
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Objective To assess the diagnostic accuracy of the surface electromyography (sEMG) parameters associated with referred anterior knee pain in diagnosing patellofemoral pain syndrome (PFPS). Design Sensitivity and specificity analysis. Setting Physical rehabilitation center and laboratory of biomechanics and motor control. Participants Pain-free subjects (n=29) and participants with PFPS (n=22) selected by convenience. Interventions Not applicable. Main Outcome Measure The diagnostic accuracy was calculated for sEMG parameters’ reliability, precision, and ability to differentiate participants with and without PFPS. The selected sEMG parameter associated with anterior knee pain was considered as an index test and was compared with the reference standard for the diagnosis of PFPS. Intraclass correlation coefficient, SEM, independent t tests, sensitivity, specificity, negative and positive likelihood ratios, and negative and positive predictive values were used for the statistical analysis. Results The medium-frequency band (B2) parameter was reliable (intraclass correlation coefficient=.80–.90), precise (SEM=2.71–3.87 normalized unit), and able to differentiate participants with and without PFPS (P<.05). The association of B2 with anterior knee pain showed positive diagnostic accuracy values (specificity, .87; sensitivity, .70; negative likelihood ratio, .33; positive likelihood ratio, 5.63; negative predictive value, .72; and positive predictive value, .86). Conclusions The results provide evidence to support the use of EMG signals (B2 – frequency band of 45–96Hz) of the vastus lateralis and vastus medialis muscles with referred anterior knee pain in the diagnosis of PFPS.
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Abstract Study design Controlled laboratory study. Objectives The purposes of this paper were to investigate (d) whether vastus medialis obliquus (VMO), vastus lateralis longus (VLL) and vastus lateralis obliquus (VLO) EMG activity can be influenced by hip abduction performed by healthy subjects. Background Some clinicians contraindicate hip abduction for patellofemoral patients (with) based on the premise that hip abduction could facilitate the VLL muscle activation leading to a VLL and VMO imbalance Methods and measures Twenty-one clinically healthy subjects were involved in the study, 10 women and 11 men (aged X = 23.3 ± 2.9). The EMG signals were collected using a computerized EMG VIKING II, with 8 channels and three pairs of surface electrodes. EMG activity was obtained from MVIC knee extension at 90° of flexion in a seated position and MVIC hip abduction at 0° and 30° with patients in side-lying position with the knee in full extension. The data were normalized in the MVIC knee extension at 50° of flexion in a seated position, and were submitted to ANOVA test with subsequent application of the Bonferroni multiple comparisons analysis test. The level of significance was defined as p ≤ 0.05. Results The VLO muscle demonstrated a similar pattern to the VMO muscle showing higher EMG activity in MVIC knee extension at 90° of flexion compared with MVIC hip abduction at 0° and 30° of abduction for male (p < 0.0007) and MVIC hip abduction at 0° of abduction for female subjects (p < 0.02196). There were no statistically significant differences in the VLL EMG activity among the three sets of exercises tested. Conclusion The results showed that no selective EMG activation was observed when comparison was made between the VMO, VLL and VLO muscles while performing MVIC hip abduction at 0° and 30° of abduction and MVIC knee extension at 90° of flexion in both male and female subjects. Our findings demonstrate that hip abduction do not facilitated VLL and VLO activity in relation to the VMO, however, this study included only healthy subjects performing maximum voluntary isometric contraction contractions, therefore much remains to be discovered by future research
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HYPOTHESIS Facial nerve monitoring can be used synchronous with a high-precision robotic tool as a functional warning to prevent of a collision of the drill bit with the facial nerve during direct cochlear access (DCA). BACKGROUND Minimally invasive direct cochlear access (DCA) aims to eliminate the need for a mastoidectomy by drilling a small tunnel through the facial recess to the cochlea with the aid of stereotactic tool guidance. Because the procedure is performed in a blind manner, structures such as the facial nerve are at risk. Neuromonitoring is a commonly used tool to help surgeons identify the facial nerve (FN) during routine surgical procedures in the mastoid. Recently, neuromonitoring technology was integrated into a commercially available drill system enabling real-time monitoring of the FN. The objective of this study was to determine if this drilling system could be used to warn of an impending collision with the FN during robot-assisted DCA. MATERIALS AND METHODS The sheep was chosen as a suitable model for this study because of its similarity to the human ear anatomy. The same surgical workflow applicable to human patients was performed in the animal model. Bone screws, serving as reference fiducials, were placed in the skull near the ear canal. The sheep head was imaged using a computed tomographic scanner and segmentation of FN, mastoid, and other relevant structures as well as planning of drilling trajectories was carried out using a dedicated software tool. During the actual procedure, a surgical drill system was connected to a nerve monitor and guided by a custom built robot system. As the planned trajectories were drilled, stimulation and EMG response signals were recorded. A postoperative analysis was achieved after each surgery to determine the actual drilled positions. RESULTS Using the calibrated pose synchronized with the EMG signals, the precise relationship between distance to FN and EMG with 3 different stimulation intensities could be determined for 11 different tunnels drilled in 3 different subjects. CONCLUSION From the results, it was determined that the current implementation of the neuromonitoring system lacks sensitivity and repeatability necessary to be used as a warning device in robotic DCA. We hypothesize that this is primarily because of the stimulation pattern achieved using a noninsulated drill as a stimulating probe. Further work is necessary to determine whether specific changes to the design can improve the sensitivity and specificity.
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This paper explores a new method of analysing muscle fatigue within the muscles predominantly used during microsurgery. The captured electromyographic (EMG) data retrieved from these muscles are analysed for any defining patterns relating to muscle fatigue. The analysis consists of dynamically embedding the EMG signals from a single muscle channel into an embedded matrix. The muscle fatigue is determined by defining its entropy characterized by the singular values of the dynamically embedded (DE) matrix. The paper compares this new method with the traditional method of using mean frequency shifts in the EMG signal's power spectral density. Linear regressions are fitted to the results from both methods, and the coefficients of variation of both their slope and point of intercept are determined. It is shown that the complexity method is slightly more robust in that the coefficient of variation for the DE method has lower variability than the conventional method of mean frequency analysis.
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Effective interaction with personal computers is a basic requirement for many of the functions that are performed in our daily lives. With the rapid emergence of the Internet and the World Wide Web, computers have become one of the premier means of communication in our society. Unfortunately, these advances have not become equally accessible to physically handicapped individuals. In reality, a significant number of individuals with severe motor disabilities, due to a variety of causes such as Spinal Cord Injury (SCI), Amyothrophic Lateral Sclerosis (ALS), etc., may not be able to utilize the computer mouse as a vital input device for computer interaction. The purpose of this research was to further develop and improve an existing alternative input device for computer cursor control to be used by individuals with severe motor disabilities. This thesis describes the development and the underlying principle for a practical hands-off human-computer interface based on Electromyogram (EMG) signals and Eye Gaze Tracking (EGT) technology compatible with the Microsoft Windows operating system (OS). Results of the software developed in this thesis show a significant improvement in the performance and usability of the EMG/EGT cursor control HCI.
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The aim of this paper was to verify whether AC biosusceptometry (ACB) is suitable for monitoring gastrointestinal (GI) contraction directly from smooth muscle in dogs, comparing with electrical recordings simultaneously. All experiments were performed in dogs with magnetic markers implanted under the serosa of the right colon and distal stomach, and their movements were recorded by ACB. Monopolar electrodes were implanted close to the magnetic markers and their electric potentials were recorded by electromyography (EMG). The effects of neostigmine, hyoscine butylbromide and meal on gastric and colonic parameters were studied. The ACB signal from the distal stomach was very similar to EMG; in the colonic recordings, however, within the same low-frequency band, ACB and EMG signals were characterized by simultaneity or a widely changeable frequency profile with time. ACB recordings were capable of demonstrating the changes in gastric and colonic motility determined by pharmacological interventions as well as by feeding. Our results reinforce the importance of evaluating the mechanical and electrical components of motility and show a temporal association between them. ACB and EMG arecomplementary for studying motility, with special emphasis on the colon. ACB offers an accurate method for monitoring in vivo GI motility.
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Objective: The aim of the present study was to investigate the between-days reliability of electromyographic (EMG) measurement of 6 bilateral trunk muscles and also the torque output in 3 planes during isometric right and left axial rotation at different exertion levels. Methods: Ten healthy subjects performed isometric right and left axial rotation at 100, 70, 50 and 30% maximum voluntary contractions in two testing sessions at least 7 days apart. EMG amplitude and frequency analyses of the recorded surface EMG signals were performed for rectus abdominis, external oblique, internal oblique, latissimus dorsi, iliocostalis lumborum and multifidus bilaterally. The primary torque in the transverse plane and the coupling torques in sagittal and coronal planes were measured. Results: For both EMG amplitude and frequency values, good (intraclass correlation coefficient, ICC = 0.75-0.89) to excellent (ICC greater than or equal to 0.90) reliability was found in the 6 trunk muscles at different exertion levels during axial rotation. The reliability of both maximal isometric axial rotation torque and coupling torques in sagittal and coronal planes were found to be excellent (ICC greater than or equal to 0.93). Conclusions: Good to excellent reliability of EMG measures of trunk muscles and torque measurements during isometric axial rotation was demonstrated. This provides further confidence of using EMG and triaxial torque assessment as outcome measures in rehabilitation and in the evaluation of the human performance in the work place. (C) 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
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Esta dissertação apresenta o desenvolvimento de uma plataforma multimodal de aquisição e processamento de sinais. O projeto proposto insere-se no contexto do desenvolvimento de interfaces multimodais para aplicação em dispositivos robóticos cujo propósito é a reabilitação motora adaptando o controle destes dispositivos de acordo com a intenção do usuário. A interface desenvolvida adquire, sincroniza e processa sinais eletroencefalográficos (EEG), eletromiográficos (EMG) e sinais provenientes de sensores inerciais (IMUs). A aquisição dos dados é feita em experimentos realizados com sujeitos saudáveis que executam tarefas motoras de membros inferiores. O objetivo é analisar a intenção de movimento, a ativação muscular e o início efetivo dos movimentos realizados, respectivamente, através dos sinais de EEG, EMG e IMUs. Para este fim, uma análise offline foi realizada. Nessa análise, são utilizadas técnicas de processamento dos sinais biológicos e técnicas para processar sinais provenientes de sensores inerciais. A partir destes, os ângulos da articulação do joelho também são aferidos ao longo dos movimentos. Um protocolo experimental de testes foi proposto para as tarefas realizadas. Os resultados demonstraram que o sistema proposto foi capaz de adquirir, sincronizar, processar e classificar os sinais combinadamente. Análises acerca da acurácia dos classificadores utilizados mostraram que a interface foi capaz de identificar intenção de movimento em 76, 0 ± 18, 2% dos movimentos. A maior média de tempo de antecipação ao movimento foi obtida através da análise do sinal de EEG e foi de 716, 0±546, 1 milisegundos. A partir da análise apenas do sinal de EMG, este valor foi de 88, 34 ± 67, 28 milisegundos. Os resultados das etapas de processamento dos sinais biológicos, a medição dos ângulos da articulação, bem como os valores de acurácia e tempo de antecipação ao movimento se mostraram em conformidade com a literatura atual relacionada.
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Novas ferramentas de Tecnologias Assistivas (TAs) têm aparecido ultimamente. Um exemplo são os Ambientes Virtuais (AVs), os quais são importantes para o desenvolvimento de novas TAs, que podem ser direcionadas para promoverem uma melhor qualidade de vida de pessoas com mobilidade reduzida permanente ou promover a reabilitação de pessoas com deficiência motora temporária. Outras ferramentas, que surgiram há algumas décadas com o desenvolvimento dos computadores, também ajudam no tratamento de pessoas com deficiência motora, que são as Interfaces Humano-Máquina (IHM). Utilizando em conjunto com equipamentos que capturam sinais biológicos, como equipamentos de Eletromiografia (EMG) e Eletroencefalografia (EEG), essas ferramentas se configuram como canais de comunicações entre o ser humano e os computadores, diferentemente das comumente utilizadas. Isso abre uma gama de possibilidades para sua utilização no tratamento e na assistência de pessoas com deficiência motora, onde sinais EMG podem ser utilizados para controlar próteses robóticas; e sinais EEG, quando capturados da região do córtex motor, podem ser utilizados em neuroreabilitação. Por outro lado, quando capturados na região occipital, os sinais de EEG podem ser utilizados para gerar comandos e outras finalidades. Este trabalho apresenta o desenvolvimento de novas ferramentas para auxiliar em pesquisas de TAs envolvendo sinais biológicos. Três diferentes AVs foram desenvolvidos para auxiliar nesse tipo de pesquisa. Além deles, um equipamento EEG comercial foi adaptado para ser utilizado com uma IHM, o qual utiliza dois desses três AVs desenvolvidos. Como resultados, temos a utilização bem sucedida do equipamento EEG obtido com sua utilização com SSVEP e Imaginação motora, além da implementação com sucesso dos três AVs desenvolvidos, que estão disponíveis para download gratuito, e que podem ser utilizados em demais pesquisas envolvendo TAs.