Use of surface electromyography (EMG) in the diagnosis of childhood hypertonia: a pilot study.
Ontology highlight
ABSTRACT:
SUBMITTER: Sanger TD
PROVIDER: S-EPMC2837764 | biostudies-literature | 2008 Jun
REPOSITORIES: biostudies-literature
Publications
Use of surface electromyography (EMG) in the diagnosis of childhood hypertonia: a pilot study.
Journal of child neurology 20080314 6
In children, increased tone in a joint can be caused by spasticity, dystonia, rigidity, or mechanical limitations such as contracture. Determination of the cause of hypertonia is important for selection of appropriate therapy, but distinction between the types of hypertonia is difficult in a clinical setting. We present results of a pilot test of the use of a portable surface electromyography (EMG) device for the evaluation of hypertonia. Seven children 5-17 years of age with hypertonia due to c ...[more]
Similar Datasets
Project description:Electromyography (EMG) devices are well-suited for measuring the behaviour of muscles during an exercise or a task, and are widely used in many different research areas. Their disadvantage is that commercial systems are expensive. We designed a low-cost EMG system with enough accuracy and reliability to be used in a wide range of possible ways. The present article focuses on the validation of the low-cost system we designed, which is compared with a commercially available, accurate device. The evaluation was done by means of a set of experiments, in which volunteers performed isometric and dynamic exercises while EMG signals from the rectus femoris muscle were registered by both the proposed low-cost system and a commercial system simultaneously. Analysis and assessment of three indicators to estimate the similarity between both signals were developed. These indicated a very good result, with spearman's correlation averaging above 0.60, the energy ratio close to the 80% and the linear correlation coefficient approximating 100%. The agreement between both systems (custom and commercial) is excellent, although there are also some limitations, such as the delay of the signal (<1 s) and noise due to the hardware and assembly in the proposed system.
| S-EPMC6928739 | biostudies-literature
Project description:This article addresses the potential clinical value of techniques based on surface electromyography (sEMG) in rehabilitation medicine with specific focus on neurorehabilitation. Applications in exercise and sport pathophysiology, in movement analysis, in ergonomics and occupational medicine, and in a number of related fields are also considered. The contrast between the extensive scientific literature in these fields and the limited clinical applications is discussed. The "barriers" between research findings and their application are very broad, and are longstanding, cultural, educational, and technical. Cultural barriers relate to the general acceptance and use of the concept of objective measurement in a clinical setting and its role in promoting Evidence Based Medicine. Wide differences between countries exist in appropriate training in the use of such quantitative measurements in general, and in electrical measurements in particular. These differences are manifest in training programs, in degrees granted, and in academic/research career opportunities. Educational barriers are related to the background in mathematics and physics for rehabilitation clinicians, leading to insufficient basic concepts of signal interpretation, as well as to the lack of a common language with rehabilitation engineers. Technical barriers are being overcome progressively, but progress is still impacted by the lack of user-friendly equipment, insufficient market demand, gadget-like devices, relatively high equipment price and a pervasive lack of interest by manufacturers. Despite the recommendations provided by the 20-year old EU project on "Surface EMG for Non-Invasive Assessment of Muscles (SENIAM)," real international standards are still missing and there is minimal international pressure for developing and applying such standards. The need for change in training and teaching is increasingly felt in the academic world, but is much less perceived in the health delivery system and clinical environments. The rapid technological progress in the fields of sensor and measurement technology (including sEMG), assistive devices, and robotic rehabilitation, has not been driven by clinical demands. Our assertion is that the most important and urgent interventions concern enhanced education, more effective technology transfer, and increased academic opportunities for physiotherapists, occupational therapists, and kinesiologists.
| S-EPMC7492208 | biostudies-literature
Project description:ObjectiveNumerous devices have been designed to support the back during lifting tasks. To improve the utility of such devices, this research explores the use of preparatory muscle activity to classify muscle loading and initiate appropriate device activation. The goal of this study was to determine the earliest time window that enabled accurate load classification during a dynamic lifting task.MethodsNine subjects performed thirty symmetrical lifts, split evenly across three weight conditions (no-weight, 10-lbs and 24-lbs), while low-back muscle activity data was collected. Seven descriptive statistics features were extracted from 100 ms windows of data. A multinomial logistic regression (MLR) classifier was trained and tested, employing leave-one subject out cross-validation, to classify lifted load values. Dimensionality reduction was achieved through feature cross-correlation analysis and greedy feedforward selection. The time of full load support by the subject was defined as load-onset.ResultsRegions of highest average classification accuracy started at 200 ms before until 200 ms after load-onset with average accuracies ranging from 80% (±10%) to 81% (±7%). The average recall for each class ranged from 69-92%.ConclusionThese inter-subject classification results indicate that preparatory muscle activity can be leveraged to identify the intent to lift a weight up to 100 ms prior to load-onset. The high accuracies shown indicate the potential to utilize intent classification for assistive device applications.SignificanceActive assistive devices, e.g. exoskeletons, could prevent back injury by off-loading low-back muscles. Early intent classification allows more time for actuators to respond and integrate seamlessly with the user.
| S-EPMC5814006 | biostudies-literature
Project description:Historical, educational, and technical barriers have been reported to limit the use of surface electromyography (sEMG) in clinical neurorehabilitation settings. In an attempt to identify, review, rank, and interpret potential factors that may play a role in this scenario, we gathered information on (1) current use of sEMG and its clinical potential; (2) professional figures primarily dealing with sEMG; (3) educational aspects, and (4) possible barriers and reasons for its apparently limited use in neurorehabilitation. To this aim, an online 30-question survey was sent to 52 experts on sEMG from diverse standpoints, backgrounds, and countries. Participants were asked to respond to each question on a 5-point Likert scale or by ranking items. A cut-off of 75% agreement was chosen as the consensus threshold. Thirty-five invitees (67%) completed the electronic survey. Consensus was reached for 77% of the proposed questions encompassing current trends in sEMG use in neurorehabilitation, educational, technical, and methodological features as well as its translational utility for clinicians and patients. Data evidenced the clinical utility of sEMG for patient assessment, to define the intervention plan, and to complement/optimize other methods used to quantify muscle and physical function. The aggregate opinion of the interviewed experts confirmed that sEMG is more frequently employed in technical/methodological than clinical research. Moreover, the slow dissemination of research findings and the lack of education on sEMG seem to prevent prompt transfer into practice. The findings of the present survey may contribute to the ongoing debate on the appropriateness and value of sEMG for neurorehabilitation professionals and its potential translation into clinical settings.
| S-EPMC7566898 | biostudies-literature
Project description:Transcutaneous spinal cord electrical stimulation (tSCS) is an emerging technology that targets to restore functionally integrated neuromuscular control of gait. The purpose of this study was to demonstrate a novel filtering method, Artifact Component Specific Rejection (ACSR), for removing artifacts induced by tSCS from surface electromyogram (sEMG) data for investigation of muscle response during walking when applying spinal stimulation. Both simulated and real tSCS contaminated sEMG data from six stroke survivors were processed using ACSR and notch filtering, respectively. The performance of the filters was evaluated with data collected in various conditions (e.g., simulated artifacts contaminating sEMG in multiple degrees, various tSCS intensities in five lower-limb muscles of six participants). In the simulation test, after applying the ACSR filter, the contaminated-signal was well matched with the original signal, showing a high correlation (r = 0.959) and low amplitude difference (normalized root means square error = 0.266) between them. In the real tSCS contaminated data, the ACSR filter showed superior performance on reducing the artifacts (96% decrease) over the notch filter (25% decrease). These results indicate that ACSR filtering is capable of eliminating artifacts from sEMG collected during tSCS application, improving the precision of quantitative analysis of muscle activity.
| S-EPMC8209256 | biostudies-literature
Project description:Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a specific instant. We introduce the concept of an sEMG image spatially composed from high-density sEMG and verify our findings from a computational perspective with experiments on gesture recognition based on sEMG images with a classification scheme of a deep convolutional network. Without any windowed features, the resultant recognition accuracy of an 8-gesture within-subject test reached 89.3% on a single frame of sEMG image and reached 99.0% using simple majority voting over 40 frames with a 1,000 Hz sampling rate. Experiments on the recognition of 52 gestures of NinaPro database and 27 gestures of CSL-HDEMG database also validated that our approach outperforms state-of-the-arts methods. Our findings are a starting point for the development of more fluid and natural muscle-computer interfaces with very little observational latency. For example, active prostheses and exoskeletons based on high-density electrodes could be controlled with instantaneous responses.
| S-EPMC5109222 | biostudies-literature
Project description:Adverse childhood experiences (ACE), such as emotional or physical abuse, can produce a lasting effect on the individual. The aim of this study was to investigate how ACE may impact electromyography (EMG) activity of the trapezius muscle in a novel experimental stress paradigm, in a sample of 120 healthy participants. The stress paradigm consisted of a memory task, in which participants were asked to memorize and recall as many words as possible, displayed on a screen. The study protocol included 2 identical experimental sessions (T0 = 0 and T1 = 6 months). EMG activity was analyzed using multilevel regression analysis. EMG activity was higher during the memory task compared to baseline, supporting the validity of the experimental EMG-stress paradigm. In addition, the EMG increase was attenuated during the second session. Analyses were indicative for a moderating effect of ACE on stress-induced EMG activity: higher ACE scores resulted in greater EMG reactivity. These associations were apparent for early ACE exposure (0-11 years) as well as for later exposure (12-17 years). The association between ACE and EMG reactivity remained significant but was much weaker at T1 in comparison to T0, likely because of reduced unpredictability and uncertainty related to the experiment. In conclusion, this study showed that enduring liabilities occasioned by ACE in a non-clinical population can be studied using an experimental paradigm of EMG stress reactivity, contingent on the level of predictability of the stressor.
| S-EPMC6508727 | biostudies-literature
Project description:Background/aimsSurface electromyography (sEMG) is a commonly used technique to investigate muscle activation and fatigue, which is non-invasive and can allow for continuous measurement. Systematic research on the use of sEMG in the sporting environment has been on-going for many years and predominantly based on cycling and rowing activities. To date there have been no reviews assessing the validity and reliability in sEMG exclusively in running activities specifically during on-field testing. The purpose of this review is to evaluate the use of sEMG in the practical context and whether this be translated to on-field testing.MethodsElectronic literature searches were performed using the Cochrane Library, PUBMED, CINAHL and PeDro without restrictions on the study date to identify the relevant current English language literature.Results10 studies were relevant after title and content review. All the studies identified were all level three evidence based. The general trends of the sEMG activity appear to correlate with running velocity and muscle fatigue seems almost always the consequence of prolonged, dynamic activity. However, these changes are not consistently measured or statistically significant throughout the studies raising the question of the accuracy and reliability when analysing sEMG measurements and making assumptions about the cause of fatigue.ConclusionsAn agreed consensus when measuring and analysing sEMG data during running activities particularly in field testing with the most appropriate study design and reliable methodology is yet to be determined and further studies are required.
| S-EPMC5117013 | biostudies-literature
Project description:Muscle activities of the elbow flexors, especially the brachialis muscle (BR), have been measured with intramuscular electromyography (EMG) using the fine-wire electrodes. It remains unclear whether BR activity can be assessed using surface EMG. The purpose of this study was to compare the EMG patterns of the BR activity recorded during elbow flexion using surface and fine-wire electrodes and to determine whether surface EMG can accurately measure the BR activity. Six healthy men were asked to perform two tasks-a maximum isometric voluntary contractions (MVICs) task and an isotonic elbow-flexion task without lifting any weight. The surface and intramuscular EMG were simultaneously recorded from the BR and the long and short heads of the biceps brachii muscle (BBLH and BBSH, respectively). The locations of the muscles were identified and marked under ultrasonographic guidance. The peak cross-correlation coefficients between the EMG signals during the MVICs task were calculated. For the isotonic elbow-flexion task, the EMG patterns for activities of each muscle were compared between the surface and the fine-wire electrodes. All cross-correlation coefficients between the surface EMG signals from the muscles were lower than 0.3. Furthermore, the EMG patterns of the BR activity were not significantly different between the surface and the fine-wire electrodes. The BR has different EMG pattern from the BBLH and the BBSH. The BR activity, conventionally measured with intramuscular EMG, can be accurately accessed with surface EMG during elbow flexion performed without lifting any weight, independent from the BBLH and BBSH activities.
| S-EPMC8733609 | biostudies-literature
Project description:BACKGROUND:Robotic arm supports aim at improving the quality of life for adults with Duchenne muscular dystrophy (DMD) by augmenting their residual functional abilities. A critical component of robotic arm supports is the control interface, as is it responsible for the human-machine interaction. Our previous studies showed the feasibility of using surface electromyography (sEMG) as a control interface to operate robotic arm supports in adults with DMD (22-24 years-old). However, in the biomedical engineering community there is an often raised skepticism on whether adults with DMD at the last stage of their disease have sEMG signals that can be measured and used for control. FINDINGS:In this study sEMG signals from Biceps and Triceps Brachii muscles were measured for the first time in a 37 year-old man with DMD (Brooke 6) that lost his arm function 15 years ago. The sEMG signals were measured during maximal and sub-maximal voluntary isometric contractions and evaluated in terms of signal-to-noise ratio and co-activation ratio. Beyond the profound deterioration of the muscles, we found that sEMG signals from both Biceps and Triceps muscles were measurable in this individual, although with a maximum signal amplitude 100 times lower compared to sEMG from healthy subjects. The participant was able to voluntarily modulate the required level of muscle activation during the sub-maximal voluntary isometric contractions. Despite the low sEMG amplitude and a considerable level of muscle co-activation, simulations of an elbow orthosis using the measured sEMG as driving signal indicated that the sEMG signals of the participant had the potential to provide control of elbow movements. CONCLUSIONS:To the best of our knowledge this is the first time that sEMG signals from a man with DMD at the last-stage of the disease were measured, analyzed and reported. These findings offer promising perspectives to the use of sEMG as an intuitive and natural control interface for robotic arm supports in adults with DMD until the last stage of the disease.
| S-EPMC5576133 | biostudies-literature