EMG assessment of back muscle function during cyclical lifting

Investigation of muscle fatigue during on-water rowing using surface EMG

In this work, four different algorithms (fast Fourier transform FFT, short-time Fourier transform STFT, continuous wavelet transform CWT, and instantaneous frequency IF) for calculating median frequency (MDF) from surface EMG signals were investigated for studying muscle fatigue during a on-water rowing training. The study protocol included 5 consecutive parts with increasing stroke rate. Six athletes participated in the study aged 36.6+-14.6 years and a rowing experience of 6 to 35 years. We considered eight muscles: biceps brachii right, biceps brachii left, latissimus dorsi right, latissimus dorsi left, erector spinae right, erector spinae left, rectus femoris and biceps femoris. By applying Friedmann test, we found a significant difference in MDF behavior between algorithms in assessing muscle fatigue . Correlation analyses showed significant correlations between muscle activity duration t_act and MDF, which differs for the four considered algorithms and should be taken into account in further experiments. With CWT showing the smallest correlation to t_act it might be more robust against time window variations. Our study provides a basis for the development of improved methods for more robust, non-invasive, and continuous detection of muscle fatigue in experiments with dynamic on-water rowing study designs.

Correlation between change in pain, disability, and surface electromyography topographic parameters after interferential current treatment in patients with chronic low back pain

[Purpose] Surface electromyography (SEMG) topography is used to objectively assess patients with low back pain (LBP). This study aimed to investigate the correlation between SEMG topographic variables, pain, and disability in patients with chronic LBP (CLBP) after interferential current (IFC) treatment, and to evaluate IFC treatment efficacy using SEMG topography. [Participants and Methods] Twenty nine patients with CLBP were recruited for a 6-week IFC treatment. Pain and disability scores, and the root-mean-square difference (RMSD) of SEMG topographic variables (relative areas [RAs] at flexion and extension) were compared before and after the intervention by repeated measures ANOVA; the correlation between variables was also explored and p-value was set at 0.001. [Results] Significant positive correlations between changes in pain score and the RMSD of RA at flexion (r(29)=0.593), and between changes in pain and disability scores (r(29)=0.426) were observed. All participants showed statistically significant improvements in the RMSD of RA at flexion, pain score, and disability score after IFC treatment. [Conclusion] SEMG topographic variables are closely associated with changes in pain score in patients with CLBP after IFC treatment. The RMSD of RA at flexion can be used as an objective marker in IFC treatment efficacy evaluation.

Continuous, integrated sensors for predicting fatigue during non-repetitive work: demonstration of technique in the operating room

Surface electromyography (sEMG) can monitor muscle activity and potentially predict fatigue in the workplace. However, objectively measuring fatigue is challenging in complex work with unpredictable work cycles where sEMG may be influenced by the dynamically changing posture demands. This study proposes a multi-modal approach integrating sEMG with motion sensors and demonstrates the approach in the live surgical work environment. Seventy-two exposures from twelve participants were collected, including self-reported musculoskeletal discomfort, sEMG, and postures. Posture sensors were used to identify time windows where the surgeon was static and in non-demanding positions, and mean power frequencies (MPF) were then calculated during those time windows. In 57 out of 72 exposures (80%), participants experienced an increase in musculoskeletal discomfort. Integrated (multi-modality) measurements showed better performance than single-modality (sEMG) measurements in detecting decreases in MPF, a predictor of fatigue. Based on self-reported musculoskeletal discomfort, sensor-based thresholds for identifying fatigue are proposed for the trapezius and deltoid muscle groups. Practitioner summary Work-related fatigue is one of the intermediate risk factors to musculoskeletal disorders. This article presents an objective integrated approach to identify musculoskeletal fatigue using wearable sensors. The presented approach could be implemented by ergonomists to identify musculoskeletal fatigue more accurately and in a variety of workplaces. Abbreviations: sEMG: surface electromyography; IMU: inertia measurement unit; MPF: mean power frequency; ACGIH: American Conference of Governmental Industrial Hygienists; SAGES: Society of American Gastrointestinal and Endoscopic Surgeons; LD: left deltoid; LT: left trapezius; RD: right deltoid; RT: right trapezius.

Influence of seat lumbar support adjustment on muscle fatigue under whole body vibration: An in vivo experimental study

BACKGROUND

In order to alleviate muscle fatigue and improve ride comfort, many published studies aimed to improve the seat environment or optimize seating posture. However, the effect of lumbar support on the lumbar muscle of seated subjects under whole body vibration is still unclear.

OBJECTIVE

This study aimed to investigate the effect of lumbar support magnitude of the seat on lumbar muscle fatigue relief under whole body vibration.

METHODS

Twenty healthy volunteers without low back pain participated in the experiment. By measuring surface electromyographic signals of erector spinae muscles under vibration or non-vibration for 30 minutes, the effect of different lumbar support conditions on muscle fatigue was analyzed. The magnitude of lumbar support d is assigned as d1= 0 mm, d2= 20 mm and d3= 40 mm for no support, small support and large support, respectively.

RESULTS

The results showed that lumbar muscle activation levels vary under different support conditions. For the small support case (d2= 20 mm), the muscle activation level under vibration and no-vibration was the minimum, 42.3% and 77.7% of that under no support (d1= 0 mm). For all support conditions, the muscle activation level under vibration is higher than that under no-vibration.

CONCLUSIONS

The results indicate that the small support yields the minimum muscle contraction (low muscle contraction intensity) under vibration, which is more helpful for relieving lumbar muscle fatigue than no support or large support cases. Therefore, an appropriate lumbar support of seats is necessary for alleviating lumbar muscle fatigue.

Fatigue induces altered spatial myoelectric activation patterns in the medial gastrocnemius during locomotion

This research investigates the effects of muscle fatigue on spatial myoelectric patterns in the lower limb during locomotion. Both spatial and frequency aspects of neuromuscular recruitment in the medial gastrocnemius change in response to fatigue, resulting in altered myoelectric patterns during walking and running. These data may help us better understand the adaptations that occur in lower limb muscles to avoid overuse injuries caused by fatigue.

Next-Generation Wearable Biosensors Developed with Flexible Bio-Chips

The development of biosensors that measure various biosignals from our body is an indispensable research field for health monitoring. In recent years, as the demand to monitor the health conditions of individuals in real time have increased, wearable-type biosensors have received more attention as an alternative to laboratory equipment. These biosensors have been embedded into smart watches, clothes, and accessories to collect various biosignals in real time. Although wearable biosensors attached to the human body can conveniently collect biosignals, there are reliability issues due to noise generated in data collection. In order for wearable biosensors to be more widely used, the reliability of collected data should be improved. Research on flexible bio-chips in the field of material science and engineering might help develop new types of biosensors that resolve the issues of conventional wearable biosensors. Flexible bio-chips with higher precision can be used to collect various human data in academic research and in our daily lives. In this review, we present various types of conventional biosensors that have been used and discuss associated issues such as noise and inaccuracy. We then introduce recent studies on flexible bio-chips as a solution to these issues.

The influence of age on spinal and lower limb muscle activity during repetitive lifting

This study investigated the effects of age on upper erector spinae (UES), lower erector spinae (LES) and lower body (gluteus maximus; biceps femoris; and vastus lateralis) muscle activity during a repetitive lifting task. Twenty-four participants were assigned to two age groups: 'younger' (n = 12; mean age ± SD = 24.6 ± 3.6 yrs) and 'older' (n = 12; mean age = 46.5 ± 3.0 yrs). Participants lifted and lowered a box (13 kg) repetitively at a frequency of 10 lifts per minute for a maximum of 20 min. EMG signals were collected every minute and normalised to a maximum voluntary isometric contraction. A submaximal endurance test of UES and LES was used to assess fatigue. Older participants showed higher levels of UES and LES muscle activity (approximately 12-13%) throughout the task, but less fatigue compared to the younger group post-task completion. When lifting, lower-limb muscle activity was generally higher in older adults, although temporal changes were similar. While increased paraspinal muscle activity may increase the risk of back injury in older workers when repetitive lifting, younger workers may be more susceptible to fatigue-related effects. Education and training in manual materials handling should consider age-related differences when developing training programmes.

Comparative Study of Kinematics and Muscle Activity Between Elite and Amateur Table Tennis Players During Topspin Loop Against Backspin Movements

This study investigated differences of lower limb kinematics and muscle activity during table tennis topspin loop against backspin movements between elite players (EPs) and amateur players (APs). Ten EPs and ten APs performed crosscourt backhand loop movements against the backspin ball with maximal power. Vicon motion analysis and a MEGA ME6000 system was used to capture kinematics and surface EMG data. The motion was divided into two phases, including the backswing and swing. The joints' flexion and extension angle tendency between EPs and APs differed significantly. The coefficient of multiple correlation (CMC) values for EPs were all beyond 0.9, indicating high similarity of joint angles change. APs presented moderate similarity with CMC values from 0.5 to 0.75. Compared to APs, EPs presented larger ankle eversion, knee and hip flexion at the beginning moment of the backswing. In the sEMG test, EPs presented smaller standardized AEMG (average electromyography) of the lower limb muscles in the rectus femoris and tibia anterior on both sides. Additionally, the maximum activation of each muscle for EPs was smaller and MPF (mean power frequency) of the lower limb was greater during the whole movement. The present study revealed that EPs could complete this technical motion more economically than APs, meanwhile, EPs were more efficient in muscle usage and showed better balance ability.

EMG Processing Based Measures of Fatigue Assessment during Manual Lifting

Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies may contribute to musculoskeletal disorders (MSDs), where overexertion contributes as the highest factor. To overcome this problem, electromyography (EMG) signal is used to monitor the workers' muscle condition and to find maximum lifting load, lifting height and number of repetitions that the workers are able to handle before experiencing fatigue to avoid overexertion. Past researchers have introduced several EMG processing techniques and different EMG features that represent fatigue indices in time, frequency, and time-frequency domain. The impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper. It is believed that this paper will greatly benefit researchers who need a bird's eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications.

Surface EMG Recordings as a Risk Assessment Tool for Musculoskeletal Disorders

Injury models for musculoskeletal disorders are considered. It is suggested that several injury mechanisms may coexist in the same body region. This has implications for data reduction procedures used in risk evaluation by surface EMG (SEMG). Biomechanical exposure as an injury risk may conceptually be characterized by the three exposure dimensions: amplitude, duration and repetitiveness. The time dimension has become increasingly important since many work tasks are performed at low exposure amplitude. For practical purposes, static activity levels higher than 2% EMGmax appear to signify increased risk of musculoskeletal disorders. However, a lower activity level does not guarantee good health, as risk factors apparently unrelated to muscle activity also exist. Mental stress may be one such risk factor.

Effect of pre-exercise phototherapy applied with different cluster probe sizes on elbow flexor muscle fatigue

Phototherapy has been used for reducing muscle fatigue. In view of the various types of phototherapy cluster probes available in the market, the purpose of this study was to compare the effects of a similar phototherapy dosage with two different cluster probes on elbow flexor muscle fatigue: small cluster probe (SC = 9 diodes; 7.5 cm(2)) vs. large cluster probe (LC = 33 diodes; 30.2 cm(2)). Ten physically active male aged 18-35 years participate in a randomized, crossover, double-blind, placebo-controlled trial, which each participant was submitted to the same testing protocol in four sessions (separated by at least 48 h) with different treatments: LC-phototherapy, SC-phototherapy, LC-placebo, and SC-placebo. The elbow flexion maximal isometric voluntary contraction (MIVC) was performed before and after a fatigue protocol (60 % of MIVC until exhaustion). Electromyography (EMG) of the biceps brachii muscle was collected during all testing procedure. Phototherapy with dose of 60 J per muscle [LC: 33 diodes = 5 lasers (850 nm), 12 LEDs (670 nm), 8 LEDs (880 nm), and 8 LEDs (950 nm); SC: 9 diodes = 5 lasers (850 nm) and 4 LEDs (670 nm)] or placebo applications occurred before fatigue protocol. Two-way ANOVA (treatment and time factors) and one-way ANOVA were used, followed by LSD post hoc. Time to exhaustion was significantly higher in active LC (15 %; p = 0.031) and SC (14 %; p = 0.038) in comparison with their respective placebo treatments, without differences between LC and SC (p > 0.05) or between placebo conditions (p > 0.05). This larger exercise tolerance in phototherapy conditions was not accompanied by a higher decrement in the volunteers' maximal strength capacity (11-15 %; p > 0.05 for all). EMG signals presented no difference between the four condition tested here. In both large and small cluster probes (according parameters tested in this study) led to reduced fatigue in elbow flexor muscles, without difference between them.

Analysis of Muscle Fatigue Progression using Cyclostationary Property of Surface Electromyography Signals

Analysis of neuromuscular fatigue finds various applications ranging from clinical studies to biomechanics. Surface electromyography (sEMG) signals are widely used for these studies due to its non-invasiveness. During cyclic dynamic contractions, these signals are nonstationary and cyclostationary. In recent years, several nonstationary methods have been employed for the muscle fatigue analysis. However, cyclostationary based approach is not well established for the assessment of muscle fatigue. In this work, cyclostationarity associated with the biceps brachii muscle fatigue progression is analyzed using sEMG signals and Spectral Correlation Density (SCD) functions. Signals are recorded from fifty healthy adult volunteers during dynamic contractions under a prescribed protocol. These signals are preprocessed and are divided into three segments, namely, non-fatigue, first muscle discomfort and fatigue zones. Then SCD is estimated using fast Fourier transform accumulation method. Further, Cyclic Frequency Spectral Density (CFSD) is calculated from the SCD spectrum. Two features, namely, cyclic frequency spectral area (CFSA) and cyclic frequency spectral entropy (CFSE) are proposed to study the progression of muscle fatigue. Additionally, degree of cyclostationarity (DCS) is computed to quantify the amount of cyclostationarity present in the signals. Results show that there is a progressive increase in cyclostationary during the progression of muscle fatigue. CFSA shows an increasing trend in muscle fatiguing contraction. However, CFSE shows a decreasing trend. It is observed that when the muscle progresses from non-fatigue to fatigue condition, the mean DCS of fifty subjects increases from 0.016 to 0.99. All the extracted features found to be distinct and statistically significant in the three zones of muscle contraction (p < 0.05). It appears that these SCD features could be useful in the automated analysis of sEMG signals for different neuromuscular conditions.

Using surface electromyography (SEMG) to classify low back pain based on lifting capacity evaluation with principal component analysis neural network method

Low back pain (LBP) is a leading cause of disability. The population with low back pain is continuously growing in the recent years. This study tries to distinguish LBP patients with healthy subjects by using the objective surface electromyography (SEMG) as a quantitative score for clinical evaluations. There are 26 healthy and 26 low back pain subjects who involved in this research. They lifted different weights by static and dynamic lifting process. Multiple features are extracted from the raw SEMG data, including energy and frequency indexes. Moreover, false discovery rate (FDR) omitted the false positive features. Then, a principal component analysis neural network (PCANN) was used for classifications. The results showed the features with different loadings (including 30%, and 50% loading) on lifting which can be used for distinguishing healthy and back pain subjects. By using PCANN method, more than 80% accuracies are achieved when different lifting weights were applied. Moreover, it is correlated between some EMG features and clinical scales, on exertion, fatigue, and pain. This technology can be potentially used for the future researches as a computer-aid diagnosis tool of LBP evaluation.

Reducing cross terms effects in the Choi-Williams transform of mioelectric signals

This study aims at investigating the effect of removing the negative values of Choi-Wiliams distribution (CWD) related to the electromyogram (EMG) for visualization and instantaneous median frequency (IMF) estimation. Beyond the EMG signals from triceps surae and biceps brachialis, the CWD was applied in a simulated sinusoidal signal as like in stationary and non-stationary simulated EMG signals (SES). The CWD negative values of all simulated and EMG signals were removed. The IMF values were obtained for SES and EMG. The CWD IMF values from SES and EMG were thus compared with the IMF values from short time Fourier transform (STFT) by means of correlation. The suppression of negative values from the CWD reduced cross terms influence and improved visualization, as shown by the increased correlation coefficient between the IMF values. Before this suppression, the extracted IMF values showed large oscillation along the time, with various spurious values beyond 500Hz, which disappeared after the suppression. Moreover, this procedure seems to be especially useful for non-stationary signals.

Quantification of the safe maximal lift in functional capacity evaluations: comparison of muscle recruitment using SEMG and therapist observation

INTRODUCTION

This study aimed to identify any correlation between muscle activity using surface electromyography (SEMG) and therapist determined safe maximal lift (SML) during the bench to shoulder lift of the WorkHab FCE. This would support construct (convergent) validity of SML determination in the WorkHab FCE.

METHOD

An experimental laboratory based study design was used. Twenty healthy volunteers performed the bench to shoulder lift of the WorkHab FCE whilst SEMG of upper trapezius, mid deltoid, thoracic, brachioradialis and bicep muscles were recorded. A summary of the data is presented using descriptive statistics and differences between groups were tested using generalised linear mixed models.

RESULTS

Results showed a significant difference in activity and duration of muscle activation with increasing weight lifted [p = 0.000 and p = 0.024 (brachioradialis)]. There was a significant difference between the up lift (bench to shoulder) and the down lift (shoulder to bench) for all muscles (p = 0.000) except the brachioradialis (p = 0.819). No significant change was found in muscle activity before or after the SML.

CONCLUSION

Convergent validity of the bench to shoulder lift of the WorkHab FCE was not established as no relationship between the muscle recruitment using SEMG and SML, as determined by therapist observation was identified during this lift.

Analysis of muscle coupling during isokinetic endurance contractions by means of nonlinear prediction

Isokinetic exercises have been extensively used in order to analyze muscle imbalances and changes associated with fatigue. It is known that such changes are difficult to assess from EMG signals during dynamic contractions, especially, using linear signal processing tools. The aim of this work was to use nonlinear prediction in order to analyze muscle couplings and interactions in this context and to assess the load-sharing of different muscles during fatigue. Results show promising for detecting interaction strategies between muscles and even for the interaction between muscles and the output torque during endurance tests.

Isometric fatigue patterns in time and time-frequency domains of triceps surae muscle in different knee positions

The occurrence of fatigue in triceps surae (TS) muscles during sustained plantar flexion contraction is investigated by means of the RMS electromyogram (EMG) and the instantaneous median frequency (IMF) of the short time Fourier transform (STFT). Six male subjects realized a 40% maximal plantar flexion isometric voluntary contraction until fatigue in two knee positions. Electrodes were positioned on gastrocnemius medialis, gastrocnemius lateralis and soleus muscles. The torque (TO) and EMG signals were synchronized. The RMS and the median of the IMF values were obtained, respectively, for each 250 ms and 1s windows of signal. Each signal was segmented into 10 epochs, from which the mean values of IMF, RMS and TO were obtained and submitted to linear regressions to determine parameter trends. Friedman test with the Dunn's post hoc were used to test for differences among muscles activation for each knee position and among slopes of regression curves, as well as to observe changes in TS RMS values over time. The results indicate different activation strategies with the knee extended (KE) in contrast to knee flexed (KF). With the KE, the gastrocnemii showed typical fatigue behavior with significant (p<0.05) IMF reductions and RMS increases over time, while soleus showed concomitant RMS and IMF increases (p<0.05) suggesting an increased soleus contribution to the torque production. With KF, the gastrocnemii were under activated, increasing the role of soleus. Thus, time-frequency analysis represented an important tool for TS muscular fatigue evaluation, allowing differentiates the role of soleus muscle.

A review of non-invasive techniques to detect and predict localised muscle fatigue

Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results.

An autonomous wearable system for predicting and detecting localised muscle fatigue

Muscle fatigue is an established area of research and various types of muscle fatigue have been clinically investigated in order to fully understand the condition. This paper demonstrates a non-invasive technique used to automate the fatigue detection and prediction process. The system utilises the clinical aspects such as kinematics and surface electromyography (sEMG) of an athlete during isometric contractions. Various signal analysis methods are used illustrating their applicability in real-time settings. This demonstrated system can be used in sports scenarios to promote muscle growth/performance or prevent injury. To date, research on localised muscle fatigue focuses on the clinical side and lacks the implementation for detecting/predicting localised muscle fatigue using an autonomous system. Results show that automating the process of localised muscle fatigue detection/prediction is promising. The autonomous fatigue system was tested on five individuals showing 90.37% accuracy on average of correct classification and an error of 4.35% in predicting the time to when fatigue will onset.

Differences in time-frequency representation of lower limbs myoelectric activity during single and double leg landing in male athletes

This study compared the instantaneous median frequency (IMF) obtained by means of a Choi-Williams transform of an electromyogram of the lower-limb muscles during single-leg (SL) and double-leg (DL) landings performed by fifteen male athletes. The IMF values of the rectus femoris (RF), biceps femoris (BF) and hip adductors (HA) were compared between two landing tasks, within each landing, and before and after ground contact (GC). The IMF values of the RF did not change between landings in contrast to those of the BF, which presented from 20- to 40-ms higher SL values before GC and from 40 to 60 ms after GC. HA presented higher SL values during the 40-60 ms range before GC. Within each landing, the RF IMF decreased from 40 ms to 60 ms after GC in the SL. Similar results were found for the HA IMF, which decreased from 40ms to 80 ms after GC. The BF IMF showed no significant change. These results suggest muscle recruitment related to anterior cruciate ligament protection since the IMF values of the RF decreased in the SL, whereas the BF IMF increased. Results for the HA showed the importance of hip muscles in stabilizing the core region, allowing the activation of distal muscles with greater safety.

Novel feature modelling the prediction and detection of sEMG muscle fatigue towards an automated wearable system

Surface Electromyography (sEMG) activity of the biceps muscle was recorded from ten subjects performing isometric contraction until fatigue. A novel feature (1D spectro_std) was used to extract the feature that modeled three classes of fatigue, which enabled the prediction and detection of fatigue. Initial results of class separation were encouraging, discriminating between the three classes of fatigue, a longitudinal classification on Non-Fatigue and Transition-to-Fatigue shows 81.58% correct classification with accuracy 0.74 of correct predictions while the longitudinal classification on Transition-to-Fatigue and Fatigue showed lower average correct classification of 66.51% with a positive classification accuracy 0.73 of correct prediction. Comparison of the 1D spectro_std with other sEMG fatigue features on the same dataset show a significant improvement in classification, where results show a significant 20.58% (p < 0.01) improvement when using the 1D spectro_std to classify Non-Fatigue and Transition-to-Fatigue. In classifying Transition-to-Fatigue and Fatigue results also show a significant improvement over the other features giving 8.14% (p < 0.05) on average of all compared features.

Principal components of frequency domain electromyograms for muscular fatigue analysis

The parameters commonly employed for muscular fatigue (MF) analysis, the mean frequency (F(mean)) and median frequency (F(median)) of surface EMG (SEMG) spectra, did not present consistent results for exercises performed at low to moderate intensities. For overcoming this limitation, the present study proposes the use of principal component (PC) analysis of SEMG spectra for MF monitoring. The SEMG from vastus lateralis muscle of 24 young male subjects were recorded during a maximal effort test in cycle ergometer. Epochs of 200 ms SEMG, extracted from each period of muscle activation of each subject were used for estimating the amplitude spectra, which were employed to obtain the first two PCs. The PC coefficients from the first 40 spectra were used as a reference for calculating the standard distance. This index presented a consistent increase along the exercise, while the values of F(mean) and F(median) did not present any pattern. Comparisons between initial and final values from all subjects show no significant changes in F(mean) and F(median) (Student t test, P > 0.05) and a significant increase (P < 10(-3)) in standard distance, indicating this index as an alternative to MF analysis in cyclical exercises.

Electromyography for assessment of pain in low back muscles

BACKGROUND AND PURPOSE

Pain is currently evaluated with "subjective" methods (eg, patient self-report). This study aimed to test whether fatigue indexes are able to accurately discriminate between subjects with and subjects without low back pain.

SUBJECTS

Sixty subjects separated into 2 groups--a group with low back pain (n=30) and a group without low back pain (n=30)--participated in this study.

METHODS

Electromyographic (EMG) and force data were obtained during a muscle fatigue test. The same test was repeated to monitor recovery. Linear regression analysis was used to obtain fatigue indexes.

RESULTS

Subjects with pain produced significantly lower force values than those without pain. The use of fatigue indexes and force values permitted accurate classification in 89.5% of cases.

DISCUSSION AND CONCLUSION

The results confirm that subjects with pain show early myoelectrical manifestations of muscle fatigue and that EMG can be a useful tool in the evaluation of low back pain.

Muscular load characterization during isometric shoulder abductions with varying force

This study sought to characterize muscle loading and fatigue during static shoulder abductions with varying force. In a supine posture, participants maintained fixed shoulder abductions against a time-varying external resistance, generated by a dynamometer-spring mechanism. Patterns (cumulative distribution) of the external resistance were varied by selecting different 10th and 90th percentiles of the distribution. Dynamometer angular velocities were also varied, to reflect different rates of cyclic muscle contraction. The degree of local fatigue development was assessed by common measures, including endurance time, strength reduction, and perceived discomfort. Myoelectric (EMG) signals were continuously obtained from the middle deltoid muscle throughout experimental exercise (60min max). Changes in EMG root-mean-square (RMS) and spectral measures (derived from 1-s windows at peaks in the cyclic contractions) were used as manifestations of muscle fatigue. For each minute, the RMS signal was further reduced using two methods, the cumulative probability distribution of EMG (CPDE) and exposure variation analysis (EVA). The former resulted in three percentile values (10th, 50th, and 90th), whereas the latter method resulted in 10 different measures (grouped by EMG activity level and duration). A main finding of the study was the applicability of several common fatigue indicators for these cyclic, repetitive exertions. Overall, the use of CPDE and EVA to characterize task differences and predict muscle fatigue was found to have limited value.

The effect of increasing resistance on trunk muscle activity during extension and flexion exercises on training devices

Although progressive resistance training of trunk muscles on devices is very common, today, the effects of increasing resistance on trunk muscle activity during dynamic extension and flexion movements on training devices have not been reported yet. Thirty healthy subjects participated in maximal isometric and submaximal dynamic (at 30%, 50% and 70% of maximum mean torque (MMT)) extension and flexion exercises on Tergumed lumbar training devices. The normalized (as a percentage of maximal voluntary isometric contractions (MVIC)) electromyographic activity of 16 abdominal and back muscles was investigated. The results of the present study indicated that in general, with increasing resistance from 30% MMT to 50% MMT and 70% MMT, the activity of all back muscles during the extension exercises and the activity of all abdominal muscles during the flexion exercises increased significantly. To train strength (>60% of MVIC), low intensities (30% and 50% MMT) appeared sufficient to affect the back muscles, but for the abdominals higher resistance (70% MMT) was required. In contrast to the other back muscles, the lumbar multifidus demonstrated high activity levels during both the extension and the flexion exercises. As the lumbar multifidus is demonstrated to be an important muscle in segmental stabilization of the lumbar spine, this finding may help in understanding the efficacy of rehabilitation programs using specific training devices.

Correlations between short-time Fourier- and continuous wavelet transforms in the analysis of localized back and hip muscle fatigue during isometric contractions

The aims of the current study were to examine the stationarities of surface electromyographic (EMG) signals obtained from eight bilateral back and hip muscles during a modified Biering-Sørensen test, and to investigate whether short-time Fourier (STFT) and continuous wavelet transforms (CWT) provided similar information with regard to EMG spectral parameters in the analysis of localized muscle fatigue. Twenty healthy subjects participated in the study after giving their informed consent. Reverse arrangement tests showed that 91.6% of the EMG signal epochs demonstrated no significant trends (all p>0.05), meaning 91.6% of the EMG signal epochs could be considered as stationary signals. Pearson correlation coefficients showed that STFT and CWT in general provide similar information with respect to the EMG spectral variables during isometric back extensions, and as a consequence STFT can still be used.

Muscle fatigue during intermittent isokinetic shoulder abduction: age effects and utility of electromyographic measures

Most existing evidence regarding the effects of age on muscular fatigue has focused on prolonged isometric contractions, repeated maximum dynamic contractions and individuals beyond traditional retirement age (>65 years). In the present study, age-related differences in muscle fatigue during submaximal dynamic efforts were examined. There were 24 younger (18-25 years) and 24 older (55-65 years) participants, all of whom were healthy and active, with equal numbers of each gender within each age group. Participants performed repetitive, intermittent shoulder abductions until exhaustion, at peak moments of 30% and 40% of individual maximum voluntary isokinetic contraction (MVIC) and with cycle durations of 20 and 40 s. Fatigue development was determined based on changes in MVIC, electromyographic (EMG) signals and ratings of perceived discomfort (RPD). Following the exhaustive exercises, strength recovery was monitored using a series of MVICs over a 15-min period. Results indicated the existence of an age-related fatigue resistance, with the older group demonstrating significantly slower rates of MVIC decline and RPD increase and smaller modifications in EMG-based fatigue measures. These age effects were generally more pronounced at the higher effort level. Main effects of effort level and cycle duration were also significant, while gender effects appeared to be marginal. Rates of strength recovery were not significantly influenced by age. In addition, the utility of standard EMG-based fatigue measures was assessed. Findings indicated that time-dependent changes in static and dynamic EMG-based measures were roughly comparable in terms of sensitivity and variability, supporting the use of standard EMG analyses for fatigue monitoring during intermittent dynamic contractions.

Time- and frequency-domain monitoring of the myoelectric signal during a long-duration, cyclic, force-varying, fatiguing hand-grip task

The amplitude and mean power spectral frequency (MNF) of the electromyogram (EMG) of flexor digitorum superficialis and extensor carpi radialis muscles were monitored during cyclic, force-varying, constant-posture, submaximal, grip-force contractions until endurance. These contractions are reminiscent of work tasks associated with the risk of repetitive stress injuries. Based on recommendations from a prior cross-comparison study of these data, the cyclic grip-force contractions were temporally aligned cycle-by-cycle to the achieved grip force profile, then EMG amplitude was computed using signal whitening (500 ms window) and MNF was computed using the short-time Fourier transform (500 ms window). In addition, brief (8s) constant-force (static) contractions were interspersed within the cyclic contractions every 5 min. MNF was tracked during these periods. All subjects reported a marked increase in pain/discomfort/fatigue during the contraction trials, until self-selecting to discontinue contractions after 30-90 min. Discomfort returned to near-baseline levels during the ensuing 45 min recovery (rest) period. No statistical trend was found in either EMG amplitude or MNF during the cyclic contractions or the recovery period. Initial MNF and MNF slope were monitored during the 8s interspersed static contractions. These parameters also did not follow any consistent trend. These results indicate limitations in the use of these EMG descriptors for assessment of fatigue during long-duration, force-varying contractions.

Recurrence quantification analysis of electrically evoked surface EMG signal

Recurrence Plot is a quite useful tool used in time-series analysis, in particular for measuring unstable periodic orbits embedded in a chaotic dynamical system. This paper introduced the structures of the Recurrence Plot and the ways of the plot coming into being. Then the way of the quantification of the Recurrence Plot is defined. In this paper, one of the possible applications of Recurrence Quantification Analysis (RQA) strategy to the analysis of electrical stimulation evoked surface EMG. The result shows the percent determination is increased along with stimulation intensity.

Development of the system to detect and process Electromyogram signals

This paper is about the design of a system that can detect four channel electromyogram (EMG) signals. EMG signals can be acquired, transformed into electrical signals and input into computer through AD acquisition card. The computer then processes the data and the signal figures are displayed on the screen. In the signals processing system various methods integrated such as adaptive filtering, the methods in time domain, the methods for frequency analysis, and also some newly developed methods, e.g., wavelet transform. The nonlinear tools such as the recurrence quantification analysis (RQA) also has been introduced to analyze the surface EMG and has shown particularly promising for the detection of muscle statue changes. The basic construction of the system and the software analysis are introduced.

Modulation effects of epidural spinal cord stimulation on muscle activities during walking

Epidural spinal cord stimulation (ESCS) combined with partial weight bearing therapy (PWBT) has been reported to facilitate recovery of functional walking for individuals after chronic incomplete spinal cord injury (ISCI). Muscle activities were analyzed in this report to examine the modulation effect of ESCS on muscle recruitment during gait training. Two ISCI individuals participated in the study and both are classified as ASIA C with low motor scores in the lower limbs. Stimulating electrodes were placed at the epidural space over T10-L2 spinal segments, along the midline in participant 1 (S1), and off-midline in participant 2 (S2). Surface electromyograms (EMGs) from leg muscles under both ESCS ON and OFF conditions recorded during treadmill gait were analyzed in time-frequency domains. ESCS application produced acute modulations in muscle activities in both participants, but the observed pattern, magnitude, and spectral content of the EMGs differed. In S1, ESCS induced a significant shift in the temporal pattern of muscle activity toward normal comparing with that when ESCS was OFF, though without eliciting noticeable change in frequency distribution between ESCS ON and OFF conditions. When ESCS was applied in S2, a modulation of EMG magnitude was observed and, consequently, improved joint kinematics during walking. In this case, a stimulation entrainment appeared in time-frequency analysis. The results suggest that ESCS activates neural structures in the dorsal aspect of the spinal cord and facilitates gait-related muscle recruitment. The exact effects of ESCS depend on the electrode placement and possibly injury history and residual functions, but in general ESCS produces a positive effect on improved walking speed, endurance, and reduced sense of effort in both ISCI subjects.

Cross-comparison of time- and frequency-domain methods for monitoring the myoelectric signal during a cyclic, force-varying, fatiguing hand-grip task

Various conventional methods to estimate the mean and median power spectral frequencies, and amplitude of the surface electromyogram during 30-90 min, cyclic, force-varying, constant-posture contractions were cross-compared in an experimental trial. The aim was to determine the most appropriate algorithm implementations and reduce the total number of algorithms that need to be considered when monitoring time trends. Subjects produced hand-grip contractions in a repeated intermittent pattern until exhaustion. For all estimated parameters: analysis of contraction levels below 25% maximum voluntary contraction produced poor estimates due to high relative measurement noise; parameter reproducibility was best when comparisons were aligned to the actual force produced rather than the target force and when the biomechanics of the contraction were more consistent; and estimates were not greatly influenced by the rate of change of the force trajectory. For frequency parameters: estimates based on the short-time Fourier transform were similar to those based on time-varying autoregressive methods; longer duration analysis windows exhibited better repeatability; and simple frequency-domain noise filters were not effective in reducing the impact of measurement noise. For amplitude estimates: whitening reduced the variance of the amplitude estimate; and the best analysis window duration was a trade-off between bias (decreased with a short duration window) and variance (decreased with a long duration window).

Assessment of Average Muscle Fiber Conduction Velocity From Surface EMG Signals During Fatiguing Dynamic Contractions

In this paper, we propose techniques of surface electromyographic (EMG) signal detection and processing for the assessment of muscle fiber conduction velocity (CV) during dynamic contractions involving fast movements. The main objectives of the study are: 1) to present multielectrode EMG detection systems specifically designed for dynamic conditions (in particular, for CV estimation); 2) to propose a novel multichannel CV estimation method for application to short EMG signal bursts; and 3) to validate on experimental signals different choices of the processing parameters. Linear adhesive arrays of electrodes are presented for multichannel surface EMG detection during movement. A new multichannel CV estimation algorithm is proposed. The algorithm provides maximum likelihood estimation of CV from a set of surface EMG signals with a window limiting the time interval in which the mean square error (mse) between aligned signals is minimized. The minimization of the windowed mse function is performed in the frequency domain, without limitation in time resolution and with an iterative computationally efficient procedure. The method proposed is applied to signals detected from the vastus laterialis and vastus medialis muscles during cycling at 60 cycles/min. Ten subjects were investigated during a 4-min cycling task. The method provided reliable assessment of muscle fatigue for these subjects during dynamic contractions.

Influence of muscle fibre shortening on estimates of conduction velocity and spectral frequencies from surface electromyographic signals

The study of surface electromyographic (EMG) signals under dynamic contractions is becoming increasingly important. However, knowledge of the methodological issues that may affect such analysis is still limited. The aim of the study was to analyse the effect of fibre shortening on estimates of conduction velocity (CV) and mean power spectral frequency (MNF) from surface EMG signals. Single fibre action potentials were simulated, as detected by commonly used spatial filters, for different fibre lengths. No physiological modifications were included with changes in fibre length, and thus only geometrical artifacts related to fibre shortening were investigated. The simulation results showed that the dependence of CV and MNF on fibre shortening is affected by the fibre location, electrode position and the spatial filter applied. With shortening of up to 50% for a fibre of 50 mm semi-length, the variations in CV and MNF estimates with shortening in bipolar recordings were 0.5% (CV) and 0.7% (MNF) for superficial fibres, and 3.6% and 5.1% for deeper fibres. Using the longitudinal double differential filter, under the same conditions, the percent variation was 0% and 0.2%, and 24.7% and 15.8%, respectively. The main conclusions were, first, muscle fibre shortening can significantly affect estimates of CV and MNF, especially for short fibre lengths. However, for long (semi-length >50 mm) and superficial fibres, this effect is limited for shortenings of up to 50% of the initial fibre length. Secondly, CV and MNF are almost equally affected by changes in muscle length; and, thirdly, sensitivity to fibre shortening depends on the spatial filter applied for signal detection.

Muscle fatigue and fatigue-related biomechanical changes during a cyclic lifting task

STUDY DESIGN

Electromyographic and biomechanical methods were utilized to investigate correlations between indexes of localized muscle fatigue and changes in the kinematics and kinetics of motion during a cyclic lifting task.

SUMMARY OF BACKGROUND DATA

Recent advances in time-frequency analysis procedures for electromyographicic signal processing provide a new way of studying localized muscle fatigue during dynamic contractions. These methods provide a means to investigate fatigue-related functional impairments in patients with low back pain.

OBJECTIVES

To study the relationship between localized muscle fatigue and the biomechanics of lifting and lowering a weighted box. Fatigue-related changes in the electromyographicic signal of trunk and limb muscles were evaluated and compared to kinematic and kinetic measures in order to determine whether lifting strategy is modified with fatigue.

METHODS

A total of 14 healthy male subjects (26 +/- 5 years) cyclically lifted and lowered a 13 kg box (12 lifts/min) for 4.5 minutes. A 5-second static maximum lifting task was included immediately before and after the cyclic lifting task to measure changes in lifting strength and static electromyographicic fatigue indexes. Electromyographic signals from 14 muscle sites (including paravertebral and limb muscles) were measured. Changes in the electromyographicic Instantaneous Median Frequency, a fatigue index, were computed using time-frequency analysis methods. This index was compared with more standardized measures of fatigue, such as those based on electromyographicic median frequency acquired during a static trunk extension test, subjective fatigue measures, and maximal static lifting strength. Biomechanical measures were gathered using a motion analysis system to study kinematic and kinetic changes during the lifting task.

RESULTS

During the cyclic lifting task, the electromyographic Instantaneous Median Frequency significantly decreased over time in the paravertebral muscles, but not in the limb muscles. Paravertebral electromyographicic Instantaneous Median Frequency changes were consistent with self-reports of fatigue as well as decreases in trunk extension strength. The magnitude of muscle-specific changes in electromyographicic Instantaneous Median Frequency was not significantly correlated with electromyographicic median frequency changes from the static trunk extension task. The load of the box relative to the maximal static lifting strength significantly affected the electromyographicic Instantaneous Median Frequency changes of paravertebral back muscles. Significant changes with fatigue during the task were found in the angular displacements at the knee, hip, trunk, and elbow. These biomechanical changes were associated with increased peak torque and forces at the L4-L5 vertebral segment.

CONCLUSIONS

Our results demonstrate correlation between localized muscle fatigue and biomechanical adaptations that occur during a cyclic lifting task. This new technique may provide researchers and clinicians with a means to investigate fatigue-related effects of repetitive work tasks or assessment procedures that might be useful in improving education, lifting ergonomy, and back school programs. Although both the dynamic and static tasks resulted in spectral shifts in the electromyographicic data, the fact that these methods led to different muscle-specific findings indicates that they should not be considered as equivalent assessment procedures.

Assessment of low back muscle fatigue by surface EMG signal analysis: methodological aspects

This paper focuses on methodological issues related to surface electromyographic (EMG) signal detection from the low back muscles. In particular, we analysed (1) the characteristics (in terms of propagating components) of the signals detected from these muscles; (2) the effect of electrode location on the variables extracted from surface EMG; (3) the effect of the inter-electrode distance (IED) on the same variables; (4) the possibility of assessing fatigue during high and very low force level contractions. To address these issues, we detected single differential surface EMG signals by arrays of eight electrodes from six locations on the two sides of the spine, at the levels of the first (L1), the second (L2), and the fifth (L5) lumbar vertebra. In total, 42 surface EMG channels were acquired at the same time during both high and low force, short and long duration contractions. The main results were: (1) signal quality is poor with predominance of non-travelling components; (2) as a consequence of point (1), in the majority of the cases it is not possible to reliably estimate muscle fiber conduction velocity; (3) despite the poor signal quality, it was possible to distinguish the fatigue properties of the investigated muscles and the fatigability at different contraction levels; (4) IED affects the sensitivity of surface EMG variables to electrode location and large IEDs are suggested when spectral and amplitude analysis is performed; (5) the sensitivity of surface EMG variables to changes in electrode location is on average larger than for other muscles with less complex architecture; (6) IED influences amplitude initial values and slopes, and spectral variable initial values; (7) normalized slopes for both amplitude and spectral variables are not affected by IED and, thus, are suggested for fatigue analysis at different postures or during movement, when IED may change in different conditions (in case of separated electrodes); (8) the surface EMG technique at the global level of amplitude and spectral analysis cannot be used to characterize fatigue properties of low back muscles during very low level, long duration contractions since in these cases the non-stable MU pool has a major influence on the EMG variables. These considerations clarify issues only partially investigated in past studies. The limitations indicated above are important and should be carefully discussed when presenting surface EMG results as a means for low back muscle assessment in clinical practice.

Activation imbalances in lumbar spine muscles in the presence of chronic low back pain

Paraspinal electromyographic (EMG) activity was recorded bilaterally from three lumbar levels during 30-s isometric trunk extensions [40 and 80% of maximum voluntary contraction (MVC)] in 20 healthy men and 14 chronic low back pain patients in pain. EMG parameters indicating neuromuscular fatigue and contralateral imbalances in EMG root-mean-square amplitude and median frequency were analyzed. Patients in pain showed less fatigue than controls at both contraction levels and produced only 55% of their MVC. Patients in pain likely did not produce a "true" maximum effort. A low MVC estimate would mean lower absolute contraction levels and less neuromuscular fatigue, thus explaining lower scores in the patients. Contralateral root-mean-square amplitude imbalances were present in both categories of subjects although such imbalances, when averaged across lumbar levels, were significantly larger in patients. Median frequency imbalances were significantly larger in the patients, at segmental as well as across lumbar levels. These results suggest that the presence of pain in these patients caused a redistribution of the activation behavior between synergistic muscles of the lumbar back.

Reliability of EMG time-frequency measures of fatigue during repetitive lifting

PURPOSE

To test the short-term and long-term reliability of time-frequency electromyographic (EMG) measures of fatigue during repetitive dynamic lifting and compare it with the reliability of median frequency (MF) EMG measures of fatigue during static lifting.

METHODS

Fourteen' healthy male subjects (26 +/- 5 years) repetitively (12 lifts/min) lifted and lowered a box (29 x 25 x 23 cm, 13 kg) for 4.5 min during 3 different tests on 2 different days. EMG data and the biomechanics of motion were recorded. Before and after dynamic lifting, static maximum lifting tests were performed. At the end of each of the two sessions, subjects performed a static lift at 80% of their maximum lifting force for 30 s.

RESULTS

Significant fatigue-related changes were observed during the lifting exercise via EMG time-frequency analysis at the paravertebral L5, L2, T10, and vastus lateralis (VL) electrode sites. Two parameters for assessing fatigue during dynamic contractions [i.e., the Instantaneous Median Frequency (IMDF) and its time dependent change] were shown to be reproducible both in the short-term (2 h) and long-term (2 wk). The corresponding ICCs reflecting the reproducibility of values between sessions were 96.9% (L5), 98.1% (L2), 90.1% (T10), 96.4% (UT), 98.0% (GM), 89.5% (VL), and 99.0% (BF), respectively. For most EMG recording sites, the reliability of the IMDF measures was not dependent upon the postural strategy that the subject used to accomplish the lifting task or on the subject's strength as measured via the static maximum lifting test. A comparison between the ICC values of the IMDF measures and those of the parameters utilized to assess fatigue during static sustained lifts [i.e., the Median Frequency (MDF) and its change during the test] revealed equally good reproducibility for most EMG recording sites. The respective ICC values that took into account time dependent trends for the IMDF parameter were 87.1% (L5), 62.4% (L2), 90.1% (T10), 0% (UT), 72.7% (GM), 45.4% (VL), and 100% (BF), and for the MDF parameter 94.9% (L5), 73.0% (L2), 80.9% (T10), 100% (UT), 89% (GM), 91.7% (VL), and 90.9% (BF), respectively.

CONCLUSIONS

The time-frequency approach allows one to derive EMG spectral parameters that can be used to monitor muscle fatigue during dynamic real-world tasks such as lifting.

Changes in the surface EMG signal and the biomechanics of motion during a repetitive lifting task

The analysis of surface electromyographic (EMG) data recorded from the muscles of the back during isometric constant-force contractions has been a useful tool for assessing muscle deficits in patients with lower back pain (LBP). Until recently, extending the technique to dynamic tasks, such as lifting, has not been possible due to the nonstationarity of the EMG signals. Recent developments in time-frequency analysis procedures to compute the instantaneous median frequency (IMDF) were utilized in this study to overcome these limitations. Healthy control subjects with no history of LBP (n = 9; mean age 26.3 +/- 6.7) were instrumented for acquisition of surface EMG data from six electrodes on the thoraco-lumbar region and whole-body kinematic data from a stereo-photogrammetric system. Data were recorded during a standardized repetitive lifting task (load = 15% body mass; 12 lifts/min; 5-min duration). The task resulted in significant decreases in IMDF for six of the nine subjects, with a symmetrical pattern of fatigue among contralateral muscles and greater decrements in the lower lumbar region. For those subjects with a significant decrease in IMDF, a lower limb and/or upper limb biomechanical adaptation to fatigue was observed during the task. Increases in the peak box acceleration were documented. In two subjects, the acceleration doubled its value from the beginning to the end of the exercise, which lead to a significant increase in the torque at L4/L5. This observation suggests an association between muscle fatigue at the lumbar region and the way the subject manipulates the box during the exercise. Fatigue-related biomechanical adaptations are discussed as a possible supplement to functional capacity assessments among patients with LBP.