Assessment of Whole Body and Local Muscle Fatigue Using Electromyography and a Perceived Exertion Scale for Squat Lifting

Use of a wearable electromyography armband to detect lift-lower tasks and classify hand loads

We used an armband with embedded surface electromyography (sEMG) electrodes, together with machine-learning (ML) models, to automatically detect lifting-lowering activities and classify hand loads. Nine healthy participants (4 male and 5 female) completed simulated lifting-lowering tasks in various conditions and with two different hand loads (2.3 and 6.8 kg). We compared three sEMG signal feature sets (i.e., time, frequency, and a combination of both domains) and three ML classifiers (i.e., Random Forest, Support Vector Machine, and Logistic Regression). Both Random Forest and Support Vector Machine models, using either time-domain or time- and frequency-domain features, yielded the best performance in detecting lifts, with respective accuracies of 79.2% (start) and 86.7% (end). Similarly, both ML models yielded the highest accuracy (80.9%) in classifying the two hand loads, regardless of the sEMG features used, emphasizing the potential of sEMG armbands for assessing exposure and risks in occupational lifting tasks.

Muscle fatigue tracking during dynamic elbow flexion-extension movements with a varying hand load

Muscle fatigue monitoring, an important element in a fatigue risk management process, can help optimize work intensity and reduce risks for musculoskeletal injuries. An experiment was conducted to determine whether myoelectric manifestations of muscle fatigue can reflect the pace of fatigue development associated with varying load intensity. Twenty male participants performed elbow flexion-extension movements with alternating hand loads (2 kg vs. 1 kg) for 16 min. The pace of fatigue in the biceps brachii in response to load variation was quantified by electromyographic (EMG) fatigue measures collected during the dynamic elbow flexion-extension movements and periodic submaximal isometric elbow flexion trials. The isometric and dynamic EMG measures, except for the amplitude of dynamic EMG, indicated fatigue development during the 2-kg isotonic movements and partial recovery with the 1 kg load. Study results suggest the potential of EMG measures for fatigue monitoring during dynamic work tasks with varying load intensity.

Changes in Neck and Shoulder Muscles Fatigue Threshold When Using a Passive Head/Neck Supporting Exoskeleton During Repetitive Overhead Tasks

OBJECTIVE

This study aimed to investigate the effects of a head/neck supporting exoskeleton (HNSE) on the electromyographic fatigue threshold (EMGFT) of the neck and shoulder muscles during a simulated overhead work task.

BACKGROUND

Overhead work is a well-known risk factor for neck and shoulder musculoskeletal disorders due to the excessive strain imposed on the muscles and joints in these regions.

METHOD

Fourteen healthy males performed a repetitive overhead nut fastening/unfastening task to exhaustion while wearing and not wearing the HNSE at two neck extension angles (40% and 80% of neck maximum range of motion). Electromyographic signals were continuously recorded from the right and left sternocleidomastoid (SCMR, SCML), splenius capitis (SCR, SCL), upper trapezius (UTR, UTL), and anterior deltoid (ADR, ADL) muscles. The normalized electromyographic amplitude (nEMG) data was time normalized, and a bisegmental linear regression was applied to determine the muscle fatigue break point.

RESULTS

The results showed a significant increase in fatigue threshold time in the SCMR (p < .001), SCML (p = .002), and UTR (p = .037) muscles when the HNSE was used. However, the EMGFT times for the right and left deltoid and left trapezius muscles showed a nonsignificant reduction due to the head/neck support exoskeleton use. In addition, the neck extension angle did not reveal a significant effect on muscles' EMGFT time.

CONCLUSION

Overall, the findings confirmed a significant delay in fatigue onset in sternocleidomastoid muscles, as measured by the electromyographic fatigue threshold. This finding suggests that the HNSE can be an effective ergonomic intervention for reducing the risk of musculoskeletal disorders in overhead workers. However, further studies are needed to investigate the effect of the HNSE at other neck extension angles and more realistic tasks to ensure the generalizability of our results.

APPLICATION

The present findings emphasize the application of the fatigue onset time to evaluate the effectiveness of ergonomic interventions, including exoskeletons, which can subsequently be utilized to alleviate postural demands and reduce the risk of musculoskeletal disorders.

Acute Effects of Whole-Body Electrostimulation Combined with Stretching on Lower Back Pain

Data from recent studies suggest that whole-body electromyostimulation (WB-EMS) is a time-effective and tailored intervention for chronic lower back pain (CLBP). The aim of this non-randomized controlled study was to compare the efficacy of a WB-EMS training and the association between WB-EMS specific training with passive stretching (Well Back System, [WBS]) on CLBP. Forty patients with CLBP, 43-81 years old, were assigned to one of the two groups: WB-EMS (n=20) and WB-EMS+WBS (n=20). Both groups completed 12 sessions (8 weeks) of the WB-EMS protocol (2×20 minutes/week). The second group performed core-specific exercises with WB-EMS plus 6 extra stretching sessions (30 minutes each). Primary study endpoints were based on changes on the visual analogue scale (VAS) and changes on the Oswestry Low Back Disability Questionnaire (ODI). Secondary study endpoints were percentage changes of maximum trunk flexion (Sit & Reach, [SR]) and changes in consumption of painkillers. Both interventions significantly improved VAS, ODI, and SR values (p range: 0.04;<0.001). However, the change of VAS (-46% vs. -17%, p<0.001), ODI (-53% vs. -17%, p<0.001), and SR (+ 7 vs.+3 cm, p=0.001) were significantly higher in the WB-EMS+WBS group compared to the WB-EMS group. The working method with WB-EMS+WBS can be a joint-friendly, individualized form to decrease CLBP.

Validation of Endurance Model for Manual Tasks. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-5. [PMID: 38083441 DOI: 10.1109/embc40787.2023.10341139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Physical fatigue in the workplace can lead to work-related musculoskeletal disorders (WMSDs), especially in occupations that require repetitive, mid-air movements, such as manufacturing and assembly tasks in industry settings. The current paper endeavors to validate an existing torque-based fatigue prediction model for lifting tasks. The model uses anthropometrics and the maximum torque of the individual to predict the time to fatigue. Twelve participants took part in the study which measured body composition parameters and the maximum force produced by the shoulder joint in flexion, followed by three lifting tasks for the shoulder in flexion, including isometric and dynamic tasks with one and two hands. Inertial measurements units (IMUs) were worn by participants to determine the torque at each instant to calculate the endurance time and CE, while a self-subjective questionnaire was utilized to assess physical exertion, the Borg Rate of Perceived Exertion (RPE) scale. The model was effective for static and two-handed tasks and produced errors in the range of [28.62 49.21] for the last task completed, indicating the previous workloads affect the endurance time, even though the individual perceives they are fully rested. The model was not effective for the one-handed dynamic task and differences were observed between males and females, which will be the focus of future work.An individualized, torque-based fatigue prediction model, such as the model presented, can be used to design worker-specific target levels and workloads, take inter and intra individual differences into account, and put fatigue mitigating interventions into place before fatigue occurs; resulting in potentially preventing WMSDs, aiding in worker wellbeing and benefitting the quality and efficiency of the work output.Clinical Relevance- This research provides the basis for an individualized, torque-based approach to the prediction of fatigue at the shoulder joint which can be used to assign worker tasks and rest breaks, design worker specific targets and reduce the prevalence of work-related musculoskeletal disorders in occupational settings.

Effect of sub-dermal exposure of silver nanoparticles on hepatic, renal and cardiac functions accompanying oxidative damage in male Wistar rats

Silver nanoparticles (AgNPs) have been generally used due to their strong antibacterial, antiviral and antifungal and antimicrobial properties. However, their toxicity is a subject of sustained debate, thus requiring further studies. Hence, this study examines the adverse effects of the sub-dermal administered dose of AgNPs (200 nm) on the liver, kidney and heart of male Wistar rats. Thirty male rats were randomly distributed into six groups of five animals per group. Group A and D served as the control and received distilled water for 14 and 28 days respectively. Groups B and C were sub-dermally exposed to AgNPs at 10 and 50 mg/kg daily for 14 days while E and F were sub-dermally exposed to AgNPs at 10 and 50 mg/kg daily for 28 days. The liver, kidney and heart of the animals were collected, processed and used for biochemical and histological analysis. Our results revealed that the subdermal administration of AgNPs induced significant increased (p < 0.05) activities of aspartate aminotransferase (AST), alanine transferase (ALT), alkaline phosphatase (ALP), urea, creatinine, and malondialdehyde (MDA) while decreasing the levels of glutathione (GSH), catalase (CAT), superoxide dismutase (SOD), and total thiol groups in the rat tissues. Our findings suggest that the subdermal administration of AgNPs induced oxidative stress and impaired the hepatic, renal and cardiac functions of male Wistar rats.

A Comprehensive Evaluation of Spine Kinematics, Kinetics, and Trunk Muscle Activities During Fatigue-Induced Repetitive Lifting

OBJECTIVE

Spine kinematics, kinetics, and trunk muscle activities were evaluated during different stages of a fatigue-induced symmetric lifting task over time.

BACKGROUND

Due to neuromuscular adaptations, postural behaviors of workers during lifting tasks are affected by fatigue. Comprehensive aspects of these adaptations remain to be investigated.

METHOD

Eighteen volunteers repeatedly lifted a box until perceived exhaustion. Body center of mass (CoM), trunk and box kinematics, and feet center of pressure (CoP) were estimated by a motion capture system and force-plate. Electromyographic (EMG) signals of trunk/abdominal muscles were assessed using linear and nonlinear approaches. The L5-S1 compressive force (Fc) was predicted via a biomechanical model. A two-way multivariate analysis of variance (MANOVA) was performed to examine the effects of five blocks of lifting cycle (C1 to C5) and lifting trial (T1 to T5), as independent variables, on kinematic, kinetic, and EMG-related measures.

RESULTS

Significant effects of lifting trial blocks were found for CoM and CoP shift in the anterior-posterior direction (respectively p < .001 and p = .014), trunk angle (p = .004), vertical box displacement (p < .001), and Fc (p = .005). EMG parameters indicated muscular fatigue with the extent of changes being muscle-specific.

CONCLUSION

Results emphasized variations in most kinematics/kinetics, and EMG-based indices, which further provided insight into the lifting behavior adaptations under dynamic fatiguing conditions.

APPLICATION

Movement and muscle-related variables, to a large extent, determine the magnitude of spinal loading, which is associated with low back pain.

Shoulder electromyography-based indicators to assess manifestation of muscle fatigue during laboratory-simulated manual handling task

Muscle fatigue is a risk factor for developing shoulder musculoskeletal disorders. The aim of this study was to identify shoulder electromyographic indicators that are most indicative of muscle fatigue during a laboratory simulated manual handling task. Thirty-two participants were equipped with electromyographic electrodes on 10 shoulder muscles and moved boxes for 45-minutes. The modified rate of perceived exertion (mRPE) was assessed every 5-minutes and multivariate linear regressions were performed between myoelectric manifestation of fatigue (MMF) and the mRPE scores. During a manual handling task representative of industry working conditions, spectral entropy, median frequency, and mobility were the electromyographic indicators that explained the largest percentage of the mRPE. Overall, the deltoids, biceps and upper trapezius were the muscles that most often showed significant changes over time in their electromyographic indicators. The combination of these three indicators may improve the accuracy for the assessment of MMF during manual handling. Practitioner Summary: To date, muscle fatigue has primarily been assessed during tasks done to exhaustion, which are not representative of typical working conditions. During a manual handling task representative of industry working conditions, EMG-derived spectral entropy, and median frequency, both extracted from time-frequency analysis, and mobility extracted from time domain, were the best indicators of the manifestation of muscle fatigue.

Retentive capacity of power output and linear versus non-linear mapping of power loss in the isotonic muscular endurance test

The limit of dynamic endurance during repetitive contractions has been referred to as the point of muscle fatigue, which can be measured by mechanical and electrophysiological parameters combined with subjective estimates of load tolerance for revealing the human real-world capacity required to work continuously. In this study, an isotonic muscular endurance (IME) testing protocol under a psychophysiological fatigue criterion was developed for measuring the retentive capacity of the power output of lower limb muscles. Additionally, to guide the development of electrophysiological evaluation methods, linear and non-linear techniques for creating surface electromyography (sEMG) models were compared in terms of their ability to estimate muscle fatigue. Forty healthy college-aged males performed three trials of an isometric peak torque test and one trial of an IME test for the plantar flexors and knee and hip extensors. Meanwhile, sEMG activity was recorded from the medial gastrocnemius, lateral gastrocnemius, vastus medialis, rectus femoris, vastus lateralis, gluteus maximus, and biceps femoris of the right leg muscles. Linear techniques (amplitude-based parameters, spectral parameters, and instantaneous frequency parameters) and non-linear techniques (a multi-layer perception neural network) were used to predict the time-dependent power output during dynamic contractions. Two mechanical manifestations of muscle fatigue were observed in the IME tests, including power output reduction between the beginning and end of the test and time-dependent progressive power loss. Compared with linear mapping (linear regression) alone or a combination of sEMG variables, non-linear mapping of power loss during dynamic contractions showed significantly higher signal-to-noise ratios and correlation coefficients between the actual and estimated power output. Muscular endurance required in real-world activities can be measured by considering the amount of work produced or the activity duration via the recommended IME testing protocol under a psychophysiological termination criterion. Non-linear mapping techniques provide more powerful mapping of power loss compared with linear mapping in the IME testing protocol.

A Weak Monotonicity Based Muscle Fatigue Detection Algorithm for a Short-Duration Poor Posture Using sEMG Measurements

Muscle fatigue is usually defined as a decrease in the ability to produce force. The surface electromyography (sEMG) signals have been widely used to provide information about muscle activities including detecting muscle fatigue by various data-driven techniques such as machine learning and statistical approaches. However, it is well-known that sEMGs are usually weak signals with a smaller amplitude and a lower signal-to-noise ratio, making it difficult to apply the traditional signal processing techniques. In particular, the existing methods cannot work well to detect muscle fatigue coming from static poses. This work exploits the concept of weak monotonicity, which has been observed in the process of fatigue, to robustly detect muscle fatigue in the presence of measurement noises and human variations. Such a population trend methodology has shown its potential in muscle fatigue detection as demonstrated by the experiment of a static pose.

Relationship Between the Borg Scale Rating of Perceived Exertion and Leg-Muscle Deoxygenation During Incremental Exercise in Healthy Adults

INTRODUCTION

The Borg scale rating of perceived exertion is a reliable indicator and widely used to monitor and guide exercise intensity. We aimed to evaluate the relationships between the Borg scale score and oxygenated hemoglobin (O2Hb) and deoxygenated hemoglobin (HHb) concentrations in the leg muscle as measured by near-infrared spectroscopy (NIRS) during cardiopulmonary exercise testing (CPET) in healthy adult men. We also investigated the relationships between the Borg scale score and the work rate (WR), heart rate (HR), oxygen uptake (VO₂), and minute ventilation (VE).

METHODS

Participants comprised 12 healthy men. Cardiopulmonary and NIRS parameters were assessed during each minute of CPET and at the end of the test.

RESULTS

The Borg scale score was significantly correlated with cardiopulmonary parameters including WR, HR, VO₂, and VE during CPET (Rs = 0.87-0.95; p < 0.05). Furthermore, the Borg scale score was significantly correlated with NIRS parameters including O2Hb and HHb levels during CPET (Rs = -0.48 and 0.45, respectively; p < 0.05).

DISCUSSION

The Borg scale score is significantly correlated with cardiopulmonary parameters (WR, HR, VO₂, and VE), as well as with leg-muscle oxygenation parameters as assessed by NIRS, during CPET in healthy adults. The correlation coefficients obtained from NIRS parameters were lower than those of cardiopulmonary parameters.

CONCLUSIONS

The Borg scale score might better reflect cardiopulmonary responses than muscle deoxygenation during exercise. These results can aid in the planning of rehabilitation programs for healthy adults.

Effective Assessments of a Short-Duration Poor Posture on Upper Limb Muscle Fatigue Before Physical Exercise

A forward head and rounded shoulder posture is a poor posture that is widely seen in everyday life. It is known that sitting in such a poor posture with long hours will bring health issues such as muscle pain. However, it is not known whether sitting in this poor posture for a short period of time will affect human activities. This paper investigates the effects of a short-duration poor posture before some typical physical activities such as push-ups. The experiments are set up as follows. Fourteen male subjects are asked to do push-ups until fatigue with two surface electromyography (sEMG) at the upper limb. Two days later, they are asked to sit in this poor posture for 15 min with eight sEMG sensors located at given back muscles. Then they do the push-ups after the short-duration poor posture. The observations from the median frequency of sEMG signals at the upper limb indicate that the short-duration poor posture does affect the fatigue procedure of push-ups. A significant decreasing trend of the performance of push-ups is obtained after sitting in this poor posture. Such effects indicate that some parts of the back muscles indeed get fatigued with only 15 min sitting in this poor posture. By further investigating the time-frequency components of sEMG of back muscles, it is observed that the low and middle frequencies of sEMG signals from the infraspinatus muscle of the dominant side are demonstrated to be more prone to fatigue with the poor posture. Although this study focuses only on push-ups, similar experiments can be arranged for other physical exercises as well. This study provides new insights into the effect of a short-duration poor posture before physical activities. These insights can be used to guide athletes to pay attention to postures before physical activities to improve performance and reduce the risk of injury.