Effect of selective dorsal rhizotomy on gait in children with bilateral spastic paresis: kinematic and EMG-pattern changes

Selective dorsal rhizotomy (SDR) is an effective treatment for reducing spasticity and improving gait in children with spastic cerebral palsy. Data concerning muscle activity changes after SDR treatment are limited.

Feasibility of Using EMG for Early Detection of the Facial Nerve During Robotic Direct Cochlear Access

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.

Método de estimativa de torque da articulação do joelho baseada em EMG

Este trabalho apresenta um método de estimativa de torque do joelho baseado em sinais eletromiográficos (EMG) durante terapia de reabilitação robótica. Os EMGs, adquiridos de cinco músculos envolvidos no movimento de flexão e extensão do joelho, são processados para encontrar as ativações musculares. Em seguida, mediante um modelo simples de contração muscular, são calculadas as forças e, usando a geometria da articulação, o torque do joelho. As funções de ativação e contração musculares possuem parâmetros limitados que devem ser calibrados para cada usuário, sendo o ajuste feito mediante a minimização do erro entre o torque estimado e o torque medido na articulação usando a dinâmica inversa. São comparados dois métodos iterativos para funções não-lineares como técnicas de otimização restrita para a calibração dos parâmetros: Gradiente Descendente e Quasi-Newton. O processamento de sinais, calibração de parâmetros e cálculo de torque estimado foram desenvolvidos no software MATLAB®; o cálculo de torque medido foi feito no software OpenSim com sua ferramenta de dinâmica inversa.

Further evaluation of an EMG technique for assessment of the deep cervical flexor muscles

A novel surface electromyographic (EMG) technique was recently described for the detection of deep cervical flexor muscle activity. Further investigation of this technique is warranted to ensure EMG activity from neighbouring muscles is not markedly influencing the signals recorded. This study compared deep cervical flexor (DCF) muscle activity with the activity of surrounding neck and jaw muscles during various anatomical movements of the neck and jaw in 10 volunteer subjects. DCF EMG activity was recorded with custom electrodes inserted via the nose and fixed by suction to the posterior mucosa of the oropharynx. Surface electrodes were placed over the sternocleidomastoid, anterior scalene, masseter and suprahyoid muscles. Positioned in supine, subjects performed isometric cranio-cervical flexion, cervical flexion, right and left cervical rotation,jaw clench and resisted jaw opening. Across all movements examined, EMG amplitude of the DCF muscles was greatest during neck movements that would require activity of the DCF muscles, particularly during cranio-cervical flexion, their primary anatomical action. The actions of jaw clench and resisted jaw opening demonstrated significantly less DCF EMG activity than the cranio-cervical flexion action (p < 0.05). Across all other movements, the neighbouring neck and jaw muscles demonstrated greatest EMG amplitude during their respective primary anatomical actions, which occurred in the absence of increased EMG amplitude recorded from the DCF muscles. The finding of substantial EMG activity of the DCF muscles only during neck actions that would require their activity, particularly cranio-cervical flexion, and not during actions involving the jaw, provide further assurance that the majority of myoelectric signals detected from the nasopharyngeal electrode are from the DCF muscles. (C) 2005 Elsevier Ltd. All rights reserved.

A simulation of the surface EMG for analysis of muscle activity during whole body vibratory stimulation

Many studies have accounted for whole body vibration effects in the fields of exercise physiology, sport and rehabilitation medicine. Generally, surface EMG is utilized to assess muscular activity during the treatment; however, large motion artifacts appear superimposed to the raw signal, making sEMG recording not suitable before any artifact filtering. Sharp notch filters, centered at vibration frequency and at its superior harmonics, have been used in previous studies, to remove the artifacts. [6, 10] However, to get rid of those artifacts some true EMG signal is lost. The purpose of this study was to reproduce the effect of motor-unit synchronization on a simulated surface EMG during vibratory stimulation. In addition, authors mean to evaluate the EMG power percentage in those bands in which are also typically located motion artifact components. Model characteristics were defined to take into account two main aspect: the muscle MUs discharge behavior and the triggering effects that appear during local vibratory stimulation. [7] Inter-pulse-interval, was characterized by a polimodal distribution related to the MU discharge frequency (IPI 55-80ms, σ=12ms) and to the correlation with the vibration period within the range of ±2 ms due to vibration stimulus. [1, 7] The signals were simulated using different stimulation frequencies from 30 to 70 Hz. The percentage of the total simulated EMG power within narrow bands centered at the stimulation frequency and its superior harmonics (± 1 Hz) resulted on average about 8% (± 2.85) of the total EMG power. However, the artifact in those bands may contain more than 40% of the total power of the total signal. [6] Our preliminary results suggest that the analysis of the muscular activity of muscle based on raw sEMG recordings and RMS evaluation, if not processed during vibratory stimulation may lead to a serious overestimation of muscular response.

Simulation of surface EMG for the analysis of muscle activity during whole body vibratory stimulation

This study aims to reproduce the effect of motor-unit synchronization on surface EMG recordings during vibratory stimulation to highlight vibration evoked muscle activity. The authors intended to evaluate, through numerical simulations, the changes in surface EMG spectrum in muscles undergoing whole body vibration stimulation. In some specific bands, in fact, vibration induced motion artifacts are also typically present. In addition, authors meant to compare the simulated EMGs with respect to real recordings in order to discriminate the effect of synchronization of motor units discharges with vibration frequencies from motion artifacts. Computations were performed using a model derived from previous studies and modified to consider the effect of vibratory stimulus, the motor unit synchronization and the endplates-electrodes relative position on the EMG signal. Results revealed that, in particular conditions, synchronization of MUs' discharge generates visible peaks at stimulation frequency and its harmonics. However, only a part of the total power of surface EMGs might be enclosed within artifacts related bands (±1. Hz centered at the stimulation frequency and its superior harmonics) even in case of strong synchronization of motor units discharges with the vibratory stimulus. © 2013 Elsevier Ireland Ltd.

Muscle motion and EMG activity in vibration treatment

The aim of this study is to highlight the relationship between muscle motion, generated by whole body vibration, and the correspondent electromyographic (EMG) activity and to suggest a new method to customize the stimulation frequency. Simultaneous recordings of EMG and tri-axial accelerations of quadriceps rectus femoris from fifteen subjects undergoing vibration treatments were collected. Vibrations were delivered via a sinusoidal oscillating platform at different frequencies (10-45 Hz). Muscle motion was estimated by processing the accelerometer data. Large EMG motion artifacts were removed using sharp notch filters centred at the vibration frequency and its superior harmonics. EMG-RMS values were computed and analyzed before and after artifact suppression to assess muscular activity. Muscles acceleration amplitude increased with frequency. Muscle displacements revealed a mechanical resonant-like behaviour of the muscle. Resonance frequencies and dumping factors depended on subject. Moreover, RMS of artifact-free EMG was found well correlated (R 2 = 0.82) to the actual muscle displacement, while the maximum of the EMG response was found related to the mechanical resonance frequency of muscle. Results showed that maximum muscular activity was found in correspondence to the mechanical resonance of the muscle itself. Assuming the hypothesis that muscle activation is proportional to muscle displacement, treatment optimization (i.e. to choose the best stimulation frequency) could be obtained by simply monitoring local acceleration (resonance), leading to a more effective muscle stimulation. Motion artifact produced an overestimation of muscle activity, therefore its removal was essential. © 2009 IPEM.

Correspondence between muscle motion and EMG activity during whole body vibration

The aim of this study is to highlight the relation between muscle motion and electromyographyc activity during whole body vibration. This treatment is accounted for eliciting a reflex muscle activity in response to vibratory stimulation. Simultaneous recordings from quadriceps Rectus Femoris EMG and 3D muscle accelerations on fifteen subjects undergoing vibration treatments were collected. In our study vibrations were delivered via a sinusoidal oscillating platform at different frequencies (10-45 Hz), with a constant amplitude. Muscle motion was estimated by processing accelerometer data. Displacements revealed a mechanical resonant-like behaviour of the muscle; resonance frequencies and dumping factors depended on subject. Large EMG motion artifacts were removed using sharp notch filters centred at the vibration frequency and its superior harmonics. RMS values of artifact-free EMG were found correlated to the actual muscle displacement. The results were in accordance to the hypothesis of a proprioceptive response during vibration treatment. Nevertheless, motion artifacts produced an overestimation of muscle activity, therefore its removal was essential. © 2009 Springer Berlin Heidelberg.

A practical system for hands-off computer interaction based on electromyogram (EMG)/eye gaze tracking (EGT)

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.

Classificador máquina de suporte vetorial com análise de Fourier aplicada em dados de EEG e EMG

The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.

Décomposition automatique de signaux EMG intramusculaires

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Décomposition automatique de signaux EMG intramusculaires

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.