Intech Open - October 17, 2012
Influence of Different Strategies of Treatment Muscle Contraction and Relaxation Phases on EMG Signal Processing and Analysis During Cyclic Exercise
Leandro Ricardo Altimari, José Luiz Dantas, Marcelo Bigliassi, Thiago Ferreira Dias Kanthack, Antonio Carlos de Moraes and Taufik Abrão
For a long time we work with muscular activity, trying to answer questions related to fatigue, muscle activity and other issues related to neuromuscular system. In this way we started to use the electromyography (EMG) as a tool to achieve better results in our studies, since it appeared to us as a truthful method to access the muscle activity inside a lot of perspectives we had been working with.
In this chapter we will try to bring some research results that we found on the GEPESINE laboratory in the last couple of years about regarding the EMG analysis. Firstly there are relevant issues that arise during the use of EMG as a tool in others works. It is not hard to find studies that use EMG signal as a way to measure the muscle activity [1-3], muscle fatigue  and also in studies involving healthy issues . Most of those studies try to access the activity or fatigue slope of the muscle during some motor task, mostly trying to access performance or just to categorize an activity according to the muscle(s) accessed. The real problem is that most of those studies use isometric movements or even isokinetic, leaving a remarkable problem for the researchers who decide to work with dynamic contractions, once the available protocols are most based on and suitable isometric studies.
We have decided to take a different look to the process on how to treat the EMG signal and how to analyze it. For instance, in order to have a more trustful signal, founds in literature recommend filtering, smoothing the raw and also rectifying the signal, which the last step does not affect the signal power. However, the filtered root mean square (RMS) signal could not be the best way to pre-process the EMG signal. Other current concern, in EMG signal pre-processing, is about the use of the total signal against evaluation only the burst-time segments of the signal. Those concerns are explained and analyzed along this chapter. In an epistemological language, we take a more critic look into the EMG signal processing. We hope the reader also to have the same look, not only into the results and conclusions, but also, into methods and thoughts, since the intention herein is not to bring an irrefutable true, but the real intention is to discuss and point out valuable arguments for the reader in order to he/she thinks about it by himself or herself, and apply it properly.
Biological Procedures Online 2006; 8: 11–35.
Techniques of EMG signal analysis: detection, processing, classification and applications
M.B.I. Raez, M.S. Hussain, and F. Mohd-Yasin
Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications.
Keywords: Electromyography, Fourier Analysis, Muscles, Nervous System
Sensors (Basel). 2013 Sep 17;13(9):12431-66. doi: 10.3390/s130912431
Surface electromyography signal processing and classification techniques.
Chowdhury RH, Reaz MB, Ali MA, Bakar AA, Chellappan K, Chang TG.
Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.
Hernia (2017) 21 (Suppl 1):S46–S50
Is Electromyography a reliable test for abdominal wall muscles? The basis for clinical protocols development
Bigolin A, Jost R, Plentz R, do Pinho A, Franceschi R, Wermann R, Cacilhas P, Falcão R, Cavazzola L
Introduction: Incisional hernias are a common complication after abdominal surgery. In most of the cases, patient’s quality of life is jeopardized. But, how much the function of abdominal wall muscles contributes for this harm is still in debate. Some studies have been published aiming to find a better method to quantify the abdominal wall function. Just one protocol seems provide a the less subjective evaluation.
Objective: To describe a functional evaluation protocol, involving isokinetic, isometric and respiratory movements with surface electromyography (SEMG) and its results when applied in healthy volunteers.
Methods: A meticulous tree steps protocol was developed. Each step has a different muscles recruitment. A wireless 6 channel electromyography was performed to evaluate of rectus abdominis (RR), external oblique (EO) and internal/transverse (I/T) muscles. Results: 19 patients, 57.8% male, the average was 28 years old, 75 kg, 169 cm height, 85.8 cm of abdominal circumference, BMI 25.9 kg/m2. Step one Isometric analysis reveled an average Peak/ RMS of 0.65/0.12; 0.79/0.23; 0.55/0.14 and in lateral contraction the results were 0.29/0.05; 0.42/0.09; 0.47/0.09 for RR, I/T and EO, respectively. Step two During MIP, SEMG peak/RMS was 0.15/0.01; 0.18/0.02; 0.1/0.01 and during EP was 0.17/0.02; 0.4/0.06; 0.23/0.03 for RR, I/T and EO, respectively. STEP tree: On dynamometer, the isokinetic analysis shown an average Peak torque of 139 N-M (SD 28.2) and on SEMG the peak/RMS was 0.54/0.07; 0.7/0.11; 0.52/0.07 for RR, I/T and EO, respectively. A significant major RR peak was found on lateral isometric contraction.
Conclusion: This is the first study with electromyography standard- ized by isokinetic and isometric tests to evaluate the abdominal wall function. The values in healthy patients was described. Difference on muscles activation was found among the steps
Gait & Posture 32 (2010) 285–289
Normative EMG activation patterns of school-age children during gait
V. Agostini, A. Nascimbeni, A. Gaffuri, P. Imazio, M.G. Benedetti, M. Knaflitz
Gait analysis is widely used in clinics to study walking abnormalities for surgery planning, definition of rehabilitation protocols, and objective evaluation of clinical outcomes. Surface electromyography allows the study of muscle activity non-invasively and the evaluation of the timing of muscle activation during movement. The aim of this study was to present a normative dataset of muscle activation patterns obtained from a large number of strides in a population of 100 healthy children aged 6–11 years. The activity of Tibialis Anterior, Lateral head of Gastrocnemius, Vastus Medialis, Rectus Femoris and Lateral Hamstrings on both lower limbs was analyzed during a 2.5-min walk at free speed. More than 120 consecutive strides were analyzed for each child, resulting in approximately 28,000 strides. Onset and offset instants were reported for each observed muscle. The analysis of a high number of strides for each participant allowed us to obtain the most recurrent patterns of activation during gait, demonstrating that a subject uses a specific muscle with different activation modalities even in the same walk. The knowledge of the various activation patterns and of their statistics will be of help in clinical gait analysis and will serve as reference in the design of future gait studies.
Gait and Posture 14 (2001) 61–70
The evolution of clinical gait analysis part l: kinesiological EMG
David H. Sutherland
In 1996, I was asked by Roy Davis, President of the Gait and Clinical Movement Analysis Society, to be the presidential guest speaker at the Birmingham, AL, annual society meeting and present a talk on the development of clinical gait analysis. Following my presentation, James Gage, Editor-in-Chief for Gait and Posture, and David Winter, Associate Editor for review articles requested a manuscript for publication. To address this task I have the advantage of being a participant throughout this exciting era and of personally knowing most of the people mentioned in this manuscript. To prepare for this assignment, I wrote letters and/or made phone calls to them. Their replies to my inquiries, plus their publications, provide documentation for this review paper. The opinions expressed, for better or worse, are my own. Due to space limitations, only a partial list of the many that have contributed is presented and I regret that not all of the important contributors have been included. In some instances they will be found in Part II and Part III. Hopefully, later publications on this subject will correct the omissions. Emphasis has been given to the earliest years and to walking gait. The subject of upper extremity analysis has not been included, though studies of subjects with upper extremity motion problems are carried out in many motion laboratories including our own. A further disclaimer is that the flood of more recent publications does not receive equal coverage. History is being written daily as clinical gait analysis gains momentum. We have barely scratched the surface of the development and potential contributions of clinical gait analysis.
EUROPA MEDICO PHYSICAL 2008;44 (Suppl. 1 to No. 3)
Using surface dynamic electromyography during Upper‐extremity robotic training
Molteni F., Caimmi M., Cazzaniga A., Gasperini G., Giandomenico E., Giovanzana C.
It has been verified that muscle weakness and degree of cocontraction correlate significantly with motor impairment and physical disability in upper‐extremity hemiplegia. Robotic training is an innovative rehabilitation approach in the treatment of upper‐extremity disabilities following stroke. At the state of the art no study has been done on the use of dynamic emg during robotic training and only two longitudinal studies on the effect of robotic therapy on the emg activation pattern have been reported in the literature. This preliminary study has a twofold objective: 1) to verify if surface emg may be a suitable tool for setting up a specific upperextremity robotic exercise fitted on patient; 2) to study the effect of robotic training on the emg pattern in the short term.
Optics Express. 2010 Dec 6;18(25):25973‐86
Quantification of functional near infrared spectroscopy to assess cortical reorganization in c hildren with cerebralpalsy.
Tian F., Delgado M.R., Dhamne S.C., Khan B., Alexandrakis G., Romero M.I., Smith L., Reid D., Clegg N.J., Liu H.
Cerebral palsy (CP) is the most common motor disorder in children. Currently available neuroimaging techniques require complete body confinement and steadiness and thus are extremely difficult for pediatric patients. Here, we report the use and quantification of functional near infraredspectroscopy (fNIRS) to investigate the functional reorganization of the sensorimotor cortex in children with hemiparetic CP. Ten of sixteen childrenwith congenital hemiparesis were measured during finger tapping tasks and compared with eight of sixteen age‐matched healthy children, with an overall measurement success rate of 60%. Spatiotemporal analysis was introduced to quantify the motor activation and brain laterality. Such a quantitative approach reveals a consistent, contralateral motor activation in healthy children at 7 years of age or older. In sharp contrast, childrenwith congenital hemiparesis exhibit all three of contralateral, bilateral and ipsilateral motor activations, depending on specific ages of the pediatric subjects. This study clearly demonstrates the feasibility of fNIRS to be utilized for investigating cortical reorganization in children with CP or othercortical disorders.
Medical Engineering & Physics. 2010 Oct;32(8):840‐8
An automated ECG‐artifact removal method for trunk muscle surface EMG recordings.
Mak J.N., Hu Y., Luk K.D.
This study aimed at developing a method for automated electrocardiography (ECG) artifact detection and removal from trunk electromyography signals. Independent Component Analysis (ICA) method was applied to the simulated data set of ECG‐corrupted surface electromyography (SEMG) signals. Independent Components (ICs) correspond to ECG artifact were then identified by an automated detection algorithm and subsequently removed. The detection performance of the algorithm was compared to that by visual inspection, while the artifact elimination performance was compared with Butterworth high pass filter at 30 Hz cutoff (BW HPF 30). The automated ECG‐ artifact detection algorithm successfully recognized the ECG source components in all data sets with a sensitivity of 100% and specificity of 99%. Better performance indicated by a significantly higher correlation coefficient (p<0.001) with the original EMG recordings was found in the SEMG data cleaned by the ICA‐based method, than that by BW HPF 30. The automated ECG‐artifact removal method for trunk SEMG recordings proposed in this study was demonstrated to produce a very good detection rate and preserved essential EMG components while keeping its distortion to minimum. The automatic nature of our method has solved the problem of visual inspection by standard ICA methods and brings great clinical benefits.
Portuguese Journal of Sport Sciences 11 (Suppl. 2), 2011
The Effect of Juvenile idiopathic arthritis on lower limb muscle activity in the propulsion phase of the counter movement jump
Dwyer K., Kennedy M. J., Lamontagne M., Roth J.
The purpose of this study was to investigate the effect of Juvenile Idiopathic Arthritis (JIA) on lower limb muscle activity during a countermovement jump (CMJ). Two groups of 2 patient data were collected; 6 patients had unilateral arthritis, and 8 patients had bilateral arthritis. Activity of lower limb muscles was assessed using integrated EMG (iEMG) and peak EMG (pEMG) of the propulsion phase of the CMJ. Analysis of the unilateral patients compared the iEMG and pEMG differences of each muscle for the limb affected with arthritis versus the same muscles in the unaffected lower limb. Analysis for the bilateral group compared the left versus right side. No significance was found between sides when comparing lower limb iEMG and pEMG. It still needs to be determined if children who suffer from JIA have adverse muscle deficiencies as a result of the disease.
The Fourth IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, Roma, Italy. 2012 Jun.
Proprioceptivity and Upper‐Extremity Dynamics in Robot‐Assisted Reaching Movement
Caimmi M., Pedrocchi N., Scano A., Malosio M., Vicentini F., Molinari Tosatti L., Molteni F.
Reaching‐against‐gravity movements feature some remarkable aspects of human motion, like a wide exploration of the upper extremity workspace and high dynamics. In clinical rehabilitation protocols the recovery of the reaching movement capability is considered as a “paradigm” because of its fundamental role as a precursor for the use of the hand in activities of daily living. Reaching‐based protocol may take advantage of robot usage, which has become a standard procedure in rehabilitation of neurological patients although the efficacy of the robot‐assisted treatment is still matter of discussion. Even fewer studies in literature investigate proprioception, upper‐extremity dynamics and their mutual relationship. Robot‐assistance introduces alterations in the dynamics of movements, e.g. limited maximum velocities and accelerations, partial upper‐extremity weight support, interaction forces between the robot and a subject. As a consequence, the subjects’proprioception may be altered too. The purpose of this preliminary work is to investigate the relationship between upper‐extremity dynamics and proprioception by comparing the estimation of shoulder torques and EMG activation pattern with the evaluation given by the subjects on the quality of the perceived movements during different reaching trials with and without robot assistance. Results show that slow free (nonassisted) reaching movements are felt as uncomfortable and figure large shoulder torques and EMG cocontraction levels. Comfortable movements are those displaying shoulder torques and cocontraction levels comparable to those in natural free reaching, suggesting the strong correlation of torques patterns and co‐contractions in motion comfort.