Analysis Of Surface Electromyogram Research Articles

Evaluation of dynamic spinal alignment changes and compensation using three-dimensional gait motion analysis for dropped head syndrome

BACKGROUND CONTEXTDynamic kinematic evaluation of spino-pelvic alignment during gait using three-dimensional (3D) motion analysis has been proposed for adult spinal thoracolumbar deformity. That is because conventional full-spine radiographs cannot be used to evaluate dynamic factors. However, dynamic changes in spino-pelvic alignment during gait for dropped head syndrome (DHS) have not been studied using this approach. PURPOSE: This study aimed to assess the dynamic changes in spinal-pelvic alignment during gait in patients with DHS using 3D motion analysis. STUDY DESIGNRetrospective review of collected radiographic and kinematic data. PATIENT SAMPLENineteen DHS patients with neck pain and/or anterior gaze disturbance. OUTCOME MEASURESStatic spino-pelvic radiological alignment, dynamic spino-pelvic kinematic parameters and electromyogram (EMG) data. METHODSCenter of gravity of the head - C7 sagittal vertical axis (CGH-C7 SVA), C2-C7 SVA, T1 slope; cervical lordosis (CL), C7SVA, thoracic kyphosis (TK), lumbar lordosis (LL), pelvic tilt (PT) and pelvic incidence (PI) were assessed using full-spine radiographs in a standing position to assess static spino-pelvic alignment. The 3D gait motion analysis was conducted during gait. Dynamic kinematic parameters were divided into spinal segments: cervical (C-), thoracic (T-), lumbar (L-) and pelvis (P-). Each spinal segment coronal angle to the pelvic angle, each spinal segment sagittal angle to the pelvic angle and pelvic sagittal angle to the horizontal axis were assessed as dynamic spino-pelvic kinematic parameters. Trunk and lower limb muscle activity during gait were assessed using wireless surface EMG analysis. Dynamic spino-pelvic kinematic variables and muscle activity were compared between the first walking lap and the final lap during gait analysis. The change in dynamic kinematic parameters was correlated with static radiological alignment and electromyographic muscular activity change. RESULTSCervical and thoracic anterior tilt increased significantly after an extended period of walking, indicating that dropped head worsened during gait. An increase of cervical anterior tilt during walking was significantly associated with decreased muscle activity in the cervical paraspinal muscles (r=-0.463, P<.05) and latissimus dorsi (r=-0.763, p<.01). Furthermore, significant correlations were found between a change in thoracic sagittal angle to pelvic angle and C7SVA (r=0.683, p<.01) and LL (r=-0.475, p<.05). This means that a larger C7SVA and smaller LL were associated with increased thoracic anterior tilt during gait. CONCLUSIONSThe 3D motion analysis for DHS showed that cervical and thoracic anterior tilt significantly increased after extended walking, resulting in worsening of dropped head. Decreased muscle activity of the neck extensor muscles during gait suggests insufficient neck extensor muscle endurance, which was associated with increased cervical anterior tilt. A greater increase in the thoracic anterior tilt during gait was found in DHS patients with a larger C7SVA and smaller LL due to insufficient thoracolumbar compensation for the dropped head. Correction of the cervical spine alone would not be sufficient to improve dropped head in cases with increased thoracic anterior tilt during gait. The results suggest that C7SVA and LL are crucial parameters in the surgical strategy for DHS.

Ageing effect of lower limb muscle activity for correlating healthy and osteoarthritic knees by surface electromyogram analysis

The ubiquity of osteoarthritis (OA) in human knees has been intensified among the ageing society of the world. The intention of this work is to assess the impact of the ageing on lower limb muscles associated with OA knees through sit-stand-sit movements. Out of total eighty-four participants, 51 healthy and 33 OA patients participated in the research. Surface EMG technique was used to investigate the activities of the vastus lateralis (VL), rectus femoris (RF), vastus medialis (VM), and the medial head of the gastrocnemius (MHGM) with the increase of age. Healthy participants were classified into three groups based on their age. Jarque-Bera normality test and independent t-test were performed for statistical clarifications. Muscle activities of the middle age and older people were found noticeably higher and lower compare to that of the young and OA group respectively. The quadricep muscles were found to contribute more than the calf muscle.

Usefulness of Scissors with a Power-Support Mechanism to Assist Thumb Movement: An Observational Study

Long-term repetitive movements, such as opening and closing scissors, increase strain on muscles and joints. Amplitude probability distribution function (APDF) analysis of surface electromyogram (sEMG) data was used to quantify the burden of muscle activity. We aimed to test the hypothesis that scissors with a power-support device assist repetitive thumb movements to reduce potential myoelectric activity. Twenty female university students who met the eligibility criteria performed a cutting experiment, with and without power-support device scissors. The primary outcome was a change in muscle load due to sEMG data that were analyzed using APDF, and the secondary outcomes investigated the occurrence of muscle fatigue and pain. The adductor pollicis muscle showed a significant decrease in muscle activity with power assistance. In addition, it was also found that fatigue and pain of the thumb and on the radial side of the forearm were significantly lower under the power-assisted conditions. The results of this study suggest that the assistive action of scissors with a power-support device compensate for muscle load on the thenar eminence. This may be used as a reference value to prevent the occurrence of hand disorders for hairdressers.

Analysis of Central Nervous System Factors and Muscle Hypertrophic Factors in a Muscle Strengthening Exercise: Changes in Muscle Thickness and a Discrete Wavelet Transform in Surface Electromyogram Analysis at Maximum Muscle Strength

Analysis of Central Nervous System Factors and Muscle Hypertrophic Factors in a Muscle Strengthening Exercise: Changes in Muscle Thickness and a Discrete Wavelet Transform in Surface Electromyogram Analysis at Maximum Muscle Strength

Progress on the evaluation method of paraspinal muscle and its correlation with lumbar diseases

To review the evaluation method of paraspinal muscle and its role in lumbar spine diseases, and offer reference for further research on paraspinal muscles. The related literature of paraspinal muscle measurement and its role in lumbar spine diseases was reviewed. The evaluation methods of paraspinal muscle were analyzed from the advantages and disadvantages and the role of paraspinal muscle in lumbar spine diseases was summarized. Radiographic methods are often used to evaluate the atrophy of paraspinal muscle, mainly including CT and MRI. The cross-sectional area and fatty infiltration of paraspinal muscle are two key parameters. Radiographic methods are reproducible and widely applied, but CT has the disadvantage of radiation exposure, while the cost of MRI is high. Besides, more and more researchers focus on the functional evaluation of paraspinal muscle, which mainly includes surface electromyogram analysis and back muscle strength test. The surface electromyogram analysis can quantitatively measure neuromuscular function, but the results could be affected by many influencing factors. The back muscle strength test is simple, but it lacks standardized posture. The atrophy of paraspinal muscle is related to many lumbar spine diseases, while the results of different researches are different. There are many methods to evaluate paraspinal muscles, but there is no unified standard. The role of paraspinal muscle in lumbar spine diseases need to be further studied.

Quantification of grip strength with complexity analysis of surface electromyogram for hemiplegic post-stroke patients.

Reduction in grip-strength due to spasticity is a common cause of impairment after stroke. To find an objective measure of post-stroke spasticity affecting grip-strength through quantification of interaction between antagonist and agonist muscles using complexity analysis of surface electromyogrm (sEMG) signals during isometric grip in healthy and post-stroke participants. The interaction between sEMG signals from antagonist and agonist muscles is quantified through Multiscale-Multivariate-Sample-Entropy (MMSE). This is used to quantify dissimilarity between hands of 12 healthy and 8 post-stroke participants during isometric grip. The clinical relevance of MMSE is explored by examining its correlation with spasticity score i.e. Modified-Ashworth-Scale (MAS). Further, potential of sEMG-based approach to quantify muscle-specific dissimilarity in sEMG activation across hands is investigated in terms of Cepstral-coefficients and power content of sEMG during grip tasks. Mean MMSE scores of sEMG signals were significantly different (p < 0.05) between paretic and non-paretic hands of Post-stroke participants. High negative correlation was observed between spasticity and complexity scores of paretic hand for post-stroke participants. A negative correlation between MAS and MMSE shows higher spasticity can lead to reduced complexity in sEMG. Thus, MMSE based complexity analysis can be used as an indicator of spasticity, affecting grip function.

Muscle Fatigue Analysis by Using a Scale Mixture-based Stochastic Model of Surface EMG Signals.

This paper presents the estimation and analysis of surface electromyogram (EMG) signals during fatiguing contractions based on a stochastic EMG model. In the model, the probability distribution of EMG signals is assumed to be a mixture of Gaussians with the same mean but different variances, facilitating the representation of the variance distribution of EMG signals. The paper proposes a continuous estimation method for variance distribution parameters using a sliding window, enabling the evaluation of the time-varying stochastic properties of EMG signals. Estimation experiments were conducted on six healthy young adults to analyze changes in EMG variance distribution with the progression of muscle fatigue. The results reveal the linear and nonlinear relationships between muscle fatigue and variance distribution parameters.

Measuring complexity in different muscles during sustained contraction using fractal properties of SEMG signal.

Modelling and analysis of surface Electromyogram (sEMG) signal has gained increasing attention in bio-signal processing for medical and healthcare applications. This research reports the study to examine the complexity in surface electromyogram signal measured from different muscles to identify the properties of muscles. Experiments were conducted to study the properties of the four muscle groups representing four sizes in length and complexities: Zygomaticus (facial), biceps, quadriceps and flexor digitorum superficialis (FDS). Complexity of the sEMG signal was computed using Higuchi's Fractal dimension. The relationship between FD and the muscle properties was investigated. Experimental results demonstrate that for a small variation in muscle contraction, there is very small change in the value of complexity (measured using Fractal dimension $\sim 0.1$%) and indicates that the larger and more complex muscles having a higher complexity at MVC. It is observed that the change in FD with muscle contraction is a result of changes in the properties of the particular muscle and its associated movement or change in length.

Surface Electromyographic Examination of Poststroke Neuromuscular Changes in Proximal and Distal Muscles Using Clustering Index Analysis.

Whether stroke-induced paretic muscle changes vary across different distal and proximal muscles remains unclear. The objective of this study was to compare paretic muscle changes between a relatively proximal muscle (the biceps brachii muscle) and two distal muscles (the first dorsal interosseous muscle and the abductor pollicis brevis muscle) following hemisphere stroke using clustering index (CI) analysis of surface electromyograms (EMGs). For each muscle, surface EMG signals were recorded from the paretic and contralateral sides of 12 stroke subjects versus the dominant side of eight control subjects during isometric muscle contractions to measure the consequence of graded levels of contraction (from a mild level to the maximal voluntary contraction). Across all examined muscles, it was found that partial paretic muscles had abnormally higher or lower CI values than those of the healthy control muscles, which exhibited a significantly larger variance in the CI via a series of homogeneity of variance tests (p < 0.05). This finding indicated that both neurogenic and myopathic changes were likely to take place in paretic muscles. When examining two distal muscles of individual stroke subjects, relatively consistent CI abnormalities (toward neuropathy or myopathy) were observed. By contrast, consistency in CI abnormalities were not found when comparing proximal and distal muscles, indicating differences in motor unit alternation between the proximal and distal muscles on the paretic sides of stroke survivors. Furthermore, CI abnormalities were also observed for all three muscles on the contralateral side. Our findings help elucidate the pathological mechanisms underlying stroke sequels, which might prove useful in developing improved stroke rehabilitation protocols.

Complex Neuromuscular Changes Post-Stroke Revealed by Clustering Index Analysis of Surface Electromyogram.

The objective of this paperwas to characterize complex neuromuscular changes induced by a hemisphere stroke through a novel clustering index (CI) analysis of surface electromyogram (EMG). The CI analysis was performed using surface EMG signals collected bilaterally from the thenar muscles of 17 subjects with stroke and 12 age-matched healthy controls during their performance of varying levels of isometric muscle contractions. Compared with the neurologically intact or contralateral muscles, mixed CI patterns were observed in the paretic muscles. Two paretic muscles showed significantly increased CI implying dominant neurogenic changes, whereas three paretic muscles had significantly reduced CI indicating dominantmyopathic changes; the other paretic muscles did not demonstrate a significant CI alternation, likely due to a deficit of descending central drive or a combined effect of neuromuscular factors. Such discrimination of paretic muscles was further highlighted using a modified CI method that emphasizes between-side comparison for each individual subject. The CI findings suggest that there appears to be different central and peripheral processes at work in varying degrees after stroke. This paper provides a convenient and quantitative analysis to assess the nature of neuromuscular changes after stroke, without using any special equipment but conventional surface EMG recording. Such assessment is helpful for the development of appropriate rehabilitation strategies for recovery of motor function.

Intermuscular coupling characteristics based on variational mode decomposition-coherence

Intermuscular coupling is defined as the interaction, correlation and coordination between different muscles during the body movement, which could be revealed by the synchronization analysis of surface electromyogram (sEMG). The multiscaled coherence analysis of sEMG signals could describe the multiple spatial and temporal functional connection characteristics of intermuscular coupling, which could be helpful for understanding the multiple spatial and temporal coupling mechanism of neuromuscular system. Furthermore, the coupling characteristics in frequency band of sEMG generally reflect the functional connection between muscles which relate to motion control and coordinative mechanism of the central nervous system (CNS). In this paper, we combine variational mode decomposition (VMD) and intermuscular coherence (IMC) analysis to propose a new method named VMD-IMC to quantitatively describe the muscular coupling characteristics in the corresponding frequency bands. First, sEMG data of flexor digitorum superficialis (FDS), flexor carpi ulnaris (FCU) and extensor digitorum (ED) are recorded simultaneously from twenty healthy subjects (253 years) who perform the designed grip task at sustained 20% maximum voluntary contraction under the static load. Then, the VMD approach is employed to adaptively decompose sEMG into several intrinsic mode functions to describe the information about different time-frequency scales. Furthermore, the coherence on different time-frequency scales between different sEMG signals is analyzed, and the significant coherent area index is calculated to quantitatively describe the functional coupling characteristics of the feature bands. And combining VMD with Hilbert transform, we calculate root mean square and mean instantaneous frequency (MIF) to describe the variations of energy and frequency of each muscle. The results show that coupling strengths increase with time, respectively, in beta (15-30 Hz) and gamma (30-45 Hz) band between two muscles (FDS vs FCU, FDS vs ED) during the sustained static force with low load. In addition, compared with the coupling between FDS and ED, the couplings between FDS and FCU in beta and gamma band under the condition of fatigue present more significant changes and similar trend in MIF variation with time. The obtained results reveal that the congenerous muscle is coordinated by CNS in a more synchronous way during the sustained isometric fatiguing contraction.

Reliability of Power Spectral Analysis of Surface Electromyogram Recorded during Sustained Vastus Medialis Isometric Contraction in Assessment of Muscle Fatigability

The aim of this study was to determine the within-day and between-days reliability of surface electromyographic (EMG) power spectral analysis in assessing fatigability of the vastus medialis (VM) muscle during knee and hip flexion under constant load application. The subjects were 13 healthy adult men free of knee abnormalities. Surface EMG was recorded from vastus medialis obliquus (VMO) and vastus medialis longus (VML) during sustained isometric contractions at 60% of maximal voluntary contraction until exhaustion on the leg press machine (static leg press test). Linear regression analysis was applied to median frequency (MF) time series to calculate initial MF and MF slope. For VMO and VML, the initial MF showed moderate to high reliability, while the MF slope showed high reliability (Intraclass correlation coefficient (ICC) = initial MF: 0.63 - 0.92, MF slope: 0.70 - 0.86). The results demonstrated that spectral analysis of surface EMG recording during isometric VM muscle contraction has high within-day and between-days reliability in the assessment of fatigability of the VMO and VML.

EMG-Torque Relation in Chronic Stroke: A Novel EMG Complexity Representation With a Linear Electrode Array.

This study examines the electromyogram (EMG)-torque relation for chronic stroke survivors using a novel EMG complexity representation. Ten stroke subjects performed a series of submaximal isometric elbow flexion tasks using their affected and contralateral arms, respectively, while a 20-channel linear electrode array was used to record surface EMG from the biceps brachii muscles. The sample entropy (SampEn) of surface EMG signals was calculated with both global and local tolerance schemes. A regression analysis was performed between SampEn of each channel's surface EMG and elbow flexion torque. It was found that a linear regression can be used to well describe the relation between surface EMG SampEn and the torque. Each channel's root mean square (RMS) amplitude of surface EMG signal in the different torque level was computed to determine the channel with the highest EMG amplitude. The slope of the regression (observed from the channel with the highest EMG amplitude) was smaller on the impaired side than on the nonimpaired side in 8 of the 10 subjects, regardless of the tolerance scheme (global or local) and the range of torques (full or matched range) used for comparison. The surface EMG signals from the channels above the estimated muscle innervation zones demonstrated significantly lower levels of complexity compared with other channels between innervation zones and muscle tendons. The study provides a novel point of view of the EMG-torque relation in the complexity domain, and reveals its alterations post stroke, which are associated with complex neural and muscular changes post stroke. The slope difference between channels with regard to innervation zones also confirms the relevance of electrode position in surface EMG analysis.

Properties of the motor unit action potential shape in proximal and distal muscles of the upper limb in healthy and post-stroke individuals.

Spectral analysis of surface electromyograms (sEMG) is often used to estimate central and peripheral characteristics of a motor unit (MU) population, such as average conduction velocity, proportion of muscle fiber types, and pattern of MU recruitment. This estimation is based on the assumption that the sEMG adequately reflects the frequency characteristics of the underlying MU action potentials (MUAP). However, sEMG has limitations in this respect, based on physiological and non-physiological factors that influence its frequency content. We present a method to examine characteristics of a MU population more reliably by assessing the distributions of frequency content and amplitude for a collection of individual MUAPs, identified using high-density sEMG decomposition. We demonstrate the use of this approach to examine how MU characteristics differ across muscles and in the post-stroke state by presenting preliminary data from deltoid (DELT), biceps (BIC), and finger flexor (FF) MU populations from 12 post-stroke individuals and 8 able-bodied controls. The results show differences in the magnitude and range of MUAP median frequencies across muscles in both groups. The group median values were higher in the stroke group for the DELT and FF and lower in the stroke group for the BIC. The range of frequencies was larger in the stroke group for all muscles. The distribution of MUAP RMS amplitude in both stroke and control groups had a substantially larger range in FF than in DELT and BIC. The group median values for the FF were twice as large in the stroke group. In addition, there were differences in the frequency and amplitude results between MUAP and global sEMG analyses. The implications of these findings and possible applications of the approach are discussed.

Extraction and Analysis of above elbow SEMG for Pattern classification

This paper presents the detailed evaluation and classification of Surface Electromyogram (SEMG) signals at different upper arm muscles for different operations. After acquiring the data from selected locations, interpretation of signals was done for the estimation of parameters using simulated algorithm. First, different types of arm operations were analysed; then statistical techniques were implemented for investigating muscle force relationships in terms of amplitude estimation. The classification (Artificial Neural Network) based results have been presented for detecting different pre-defined arm motions in order to discriminate SEMG signals. The outcome of research indicates that a neural network classifier performs best with an average classification rate of 92.50%. Finally, the result also inferred the operations which were observed to be easy for arm recognition and the study is a step forward to develop powerful, flexible and efficient prosthetic designs.

Analysis of linear electrode array EMG for assessment of hemiparetic biceps brachii muscles.

This study presents a frequency analysis of surface electromyogram (EMG) signals acquired by a linear electrode array from the biceps brachii muscles bilaterally in 14 hemiparetic stroke subjects. For different levels of isometric contraction ranging from 10 to 80% of the maximum voluntary contraction (MVC), the power spectra of 19 bipolar surface EMG channels arranged proximally to distally along the muscle fibers were examined in both paretic and contralateral muscles. It was found that across all stroke subjects, the median frequency (MF) and the mean power frequency (MPF), averaged from different surface EMG channels, were significantly smaller in the paretic muscle compared to the contralateral muscle at each of the matched percent MVC contractions. The muscle fiber conduction velocity (MFCV) was significantly slower in the paretic muscle than in the contralateral muscle. No significant correlation between the averaged MF, MPF, or MFCV vs. torque was found in both paretic and contralateral muscles. However, there was a significant positive correlation between the global MFCV and MF. Examination of individual EMG channels showed that electrodes closest to the estimated muscle innervation zones produced surface EMG signals with significantly higher MF and MPF than more proximal or distal locations in both paretic and contralateral sides. These findings suggest complex central and peripheral neuromuscular alterations (such as selective loss of large motor units, disordered control of motor units, increased motor unit synchronization, and atrophy of muscle fibers, etc.) which can collectively influence the surface EMG signals. The frequency difference with regard to the innervation zone also confirms the relevance of electrode position in surface EMG analysis.

Recurrence quantification analysis of surface electromyogram supports alterations in motor unit recruitment strategies by anodal transcranial direct current stimulation.

Recent evidence indicates that anodal transcranial direct current stimulation (tDCS) can selectively alter the EMG/force relationship of agonist arm muscles; however, the mechanisms mediating those changes are less clear. The purpose of this study was to evaluate the effect of anodal tDCS on motor unit synchronization by using a sophisticated non-linear EMG analysis called recurrence quantification analysis (RQA). Surface EMG signals were collected from the biceps brachii muscle of eighteen healthy young adults (9 tDCS and 9 control) at various force levels (12.5%, 25%, 37.5%, and 50% maximum) before and after the application of anodal tDCS over the primary motor cortex. RQA was employed to quantify the changes in percentage of determinism (% DET) and laminarity (% LAM) of the surface EMG signals, which are surrogate measures of motor unit synchronization. RQA analyses indicated that the changes in % DET and % LAM scores were significantly higher in the tDCS group than in the control group (p < 0.05) and this effect was particularly pronounced at higher force levels. The results of this study provide novel evidence supporting that anodal tDCS significantly alters motor unit firing strategies (i.e., the degree of synchronization) of the biceps brachii muscle.

Wavelet Transform-Based Classification of Electromyogram Signals Using an Anova Technique

Wavelet analysis of surface electromyogram (sEMG) signals has been investigated. Methods to remove noise before processing and further analysis are rather significant for these signals. The sEMG signals were estimated with the following steps, first, the obtained signal was decomposed using wavelet transform; then, decomposed coefficients were analyzed by threshold methods, and, finally, reconstruction was performed. Comparison of the Daubechies wavelet family for effective removing noise from the recorded sEMGs was executed preciously. As was found, wavelet transform db4 performs denoising best among the aforesaid wavelet family. Results inferred that Daubechies wavelet families (db4) were more suitable for the analysis of sEMG signals related to different upper limb motions, and a classification accuracy of 88.90% was achieved. Then, a statistical technique (one-way repeated factorial analysis) for the experimental coefficient was done to investigate the class separ ability among different motions.

Hand Motion Recognition from Single Channel Surface EMG Using Wavelet &amp; Artificial Neural Network

The strength of the muscle contraction can be easily measured by the muscle activity extracted at the skin surface. Analysis of surface Electromyogram (sEMG) is one of the standard procedures to identify posture, gesture and actions (i.e. control of prosthe- sis via learnt body actions). sEMG signals are usually complex in nature. It can be easily classified into differentiated muscular activities with appropriate signal processing tools. In order to analyze its complexity, various studies have been carried out but have proved unsuccessful, due to huge differences in muscular activities of some muscles over the other. This paper presents a new technique to identify low level hand movement by classifying the single channel sEMG. Single channel sEMG analysis is preferred over multi-channel due to its simplicity, computational cost and efficiency. Wavelet transformation and artificial neural network (ANN) classifier are utilized to classify and analyze the sEMG signal in a better way.

Power spectral analysis of surface electromyography (EMG) at matched contraction levels of the first dorsal interosseous muscle in stroke survivors

ObjectiveThe objective of this study was to help assess complex neural and muscular changes induced by stroke using power spectral analysis of surface electromyogram (EMG) signals. MethodsFourteen stroke subjects participated in the study. They were instructed to perform isometric voluntary contractions by abducting the index finger. Surface EMG signals were collected from the paretic and contralateral first dorsal interosseous (FDI) muscles with forces ranging from 30% to 70% maximum voluntary contraction (MVC) of the paretic muscle. Power spectral analysis was performed to characterize features of the surface EMG in paretic and contralateral muscles at matched forces. A Linear Mixed Model was applied to identify the spectral changes in the hemiparetic muscle and to examine the relation between spectral parameters and contraction levels. Regression analysis was performed to examine the correlations between spectral characteristics and clinical features. ResultsDifferences in power spectrum distribution patterns were observed in paretic muscles when compared with their contralateral pairs. Nine subjects showed increased mean power frequency (MPF) in the contralateral side (>15Hz). No evident spectrum difference was observed in 3 subjects. Only 2 subjects had higher MPF in the paretic muscle than the contralateral muscle. Pooling all subjects’ data, there was a significant reduction of MPF in the paretic muscle compared with the contralateral muscle (paretic: 168.7±7.6Hz, contralateral: 186.1±8.7Hz, mean±standard error, F=36.56, p<0.001). Examination of force factor on the surface EMG power spectrum did not confirm a significant correlation between the MPF and contraction force in either hand (F=0.7, p>0.5). There was no correlation between spectrum difference and Fugl–Meyer or Chedoke scores, or ratio of paretic and contralateral MVC (p>0.2). ConclusionsThere appears to be complex muscular and neural processes at work post stroke that may impact the surface EMG power spectrum. The majority of the tested stroke subjects had lower MPF in the paretic muscle than in the contralateral muscle at matched isometric contraction force. The reduced MPF of paretic muscles can be attributed to different factors such as increased motor unit synchronization, impairments in motor unit control properties, loss of large motor units, and atrophy of muscle fibers. SignificanceSurface EMG power spectral analysis can serve as a useful tool to indicate complex neural and muscular changes after stroke.