Displaying publications 1 - 20 of 28 in total

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  1. Abdullah, S., Putra, T.E., Nuawi, M.Z., Nopiah, Z.M.
    MyJurnal
    This paper presents a new approach to identify fatigue damaging potential locations using the Morlet wavelet coefficients. For solving the subject matter, the 122.4 second SAESUS strain signal was selected for the simulation purpose. As the result, the Morlet wavelet coefficients predicted that the maximum fatigue damage occurs at 40.4 - 42.6 seconds and 67.4 - 70 seconds. For the validation purpose, the Morrow’s fatigue damaging value was calculated and was obtained that the maximum fatigue damage occurs at 0 seconds and 99.7 seconds. The fatigue damaging value at the points was 0.0047 cycles to failure. Since both the plots had similar pattern, the Morlet wavelet coefficients could be used as the early warning of the fatigue damaging potential locations, although the locations were not entirely correct.
    Matched MeSH terms: Muscle Fatigue
  2. Shakhih MFM, Ridzuan N, Wahab AA, Zainuddin NF, Delestri LFU, Rosslan AS, et al.
    Med Biol Eng Comput, 2021 Aug;59(7-8):1447-1459.
    PMID: 34156602 DOI: 10.1007/s11517-021-02387-x
    Surface electromyography (sEMG) has been widely used in evaluating muscle fatigue among athletes where electrodes are attached on the skin during the activity. Recently, infrared thermography technique (IRT) has gain popularity and shown to be another preferred method in monitoring and predicting muscle fatigue non-obstructively. This paper investigates the correlation between surface temperature and muscle activation parameters obtained using both IRT and sEMG methods simultaneously. Twenty healthy subjects were required to perform a repetitive calf raise exercise with various loads attached around their ankle for 3 min to induce fatigue on the targeted gastrocnemius muscles. Average temperature and temperature difference information were extracted from thermal images, while root mean square (RMS) and median frequency (MF) were extracted from sEMG signals. Spearman statistical analysis performed shows that there is a significant correlation between average temperature with RMS and between temperature difference with MF values at p<0.05. While ANOVA test conducted shows that there is significant impact of loads on RMS and MF where F=12.61 and 3.59, respectively, at p< 0.05. This study suggested that skin surface temperature can be utilized in monitoring and predicting muscle fatigue in low intensity dynamic exercise and can be extended to other dynamic exercises.
    Matched MeSH terms: Muscle Fatigue*
  3. Abd Aziz M, Hamzaid NA, Hasnan N
    J Vis Exp, 2022 Nov 11.
    PMID: 36440840 DOI: 10.3791/63149
    Execution of Sit-to-Stand (SitTS) in incomplete spinal cord injury (SCI) patients involves motor function in both upper and lower extremities. The use of arm support, in particular, is a significant assistive factor while executing SitTS movement in SCI population. In addition, the application of functional electrical stimulation (FES) onto quadriceps and gluteus maximus muscles is one of the prescribed management for incomplete SCI to improve muscle action for simple lower limb movements. However, the relative contribution of upper and lower extremities during SitTS has not been thoroughly investigated. Two motor incomplete SCI paraplegics performed repetitive SitTS to fatigue exercise challenge. Their performance was investigated as a mixed-method case-control study comparing SitTS with and without the assistance of FES. Three sets of SitTS tests were completed with 5-min resting period allocated in between sets, with mechanomyography (MMG) sensors attached over the rectus femoris muscles bilaterally. The exercise was separated into 2 sessions; Day 1 for voluntary SitTS and Day 2 for FES-assisted SitTS. Questionnaires were conducted after every session to gather the participants' input about their repetitive SitTS experience. The analysis confirmed that a SitTS cycle could be divided into three phases; Phase 1 (Preparation to stand), Phase 2 (Seat-off), and Phase 3 (Initiation of hip extension), which contributed to 23% ± 7%, 16% ± 4% and 61% ± 6% of the SitTS cycle, respectively. The contribution of arms and legs during SitTS movement varied in different participants based on their legs' Medical Research Council (MRC) muscle grade. In particular, the applied arm forces start to increase clearly when the leg forces start to decline during standing. This finding is supported by the significantly reduced MMG signal indicating leg muscle fatigue and their reported feeling of tiredness.
    Matched MeSH terms: Muscle Fatigue/physiology
  4. Jamaluddin FN, Ibrahim F, Ahmad SA
    J Healthc Eng, 2023;2023:1951165.
    PMID: 36756137 DOI: 10.1155/2023/1951165
    In sports, fatigue management is vital as adequate rest builds strength and enhances performance, whereas inadequate rest exposes the body to prolonged fatigue (PF) or also known as overtraining. This paper presents PF identification and classification based on surface electromyography (EMG) signals. An experiment was performed on twenty participants to investigate the behaviour of surface EMG during the inception of PF. PF symptoms were induced in accord with a five-day Bruce Protocol treadmill test on four lower extremity muscles: the biceps femoris (BF), rectus femoris (RF), vastus medialis (VM), and vastus lateralis (VL). The results demonstrate that the experiment successfully induces soreness, unexplained lethargy, and performance decrement and also indicate that the progression of PF can be observed based on changes in frequency features (ΔF med and ΔF mean) and time features (ΔRMS and ΔMAV) of surface EMG. This study also demonstrates the ability of wavelet index features in PF identification. Using a naïve Bayes (NB) classifier exhibits the highest accuracy based on time and frequency features with 98% in distinguishing PF on RF, 94% on BF, 9% on VL, and 97% on VM. Thus, this study has positively indicated that surface EMG can be used in identifying the inception of PF. The implication of the findings is significant in sports to prevent a greater risk of PF.
    Matched MeSH terms: Muscle Fatigue*
  5. Halim I, Arep H, Kamat SR, Abdullah R, Omar AR, Ismail AR
    Saf Health Work, 2014 Jun;5(2):97-105.
    PMID: 25180141 DOI: 10.1016/j.shaw.2014.04.002
    BACKGROUND: Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing.

    METHODS: The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system.

    RESULTS: Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results.

    CONCLUSION: The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.

    Matched MeSH terms: Muscle Fatigue
  6. Ayuni Nabilah Alias, Karmegam Karuppiah, Vivien How, Velu Perumal
    MyJurnal
    In order to accomplish a wide range of duties and responsibilities that may be done under unpleasant working con- ditions, prolonged standing posture is common with school teachers. Nevertheless, standing upright for a long time or otherwise regarded as prolonged standing frequently contributes to body pain and discomfort, muscle fatigue and even health problems such as musculoskeletal disorders (MSDs). The aim of this paper is to review MSDs arising from prolonged standing and spread information on existing ergonomic and non-ergonomic interventions to alleviate prolonged standing discomfort. Systematic review on prolonged standing school teachers with specific keywords were recognized to discover the appropriate studies and information in a systematic search. The informations in this review may be helpful to guide teacher, school management and researchers to implement the suitable interventions in order to minimise the health issue due to MSDs among school teachers.
    Matched MeSH terms: Muscle Fatigue
  7. Islam MA, Sundaraj K, Ahmad RB, Ahamed NU
    PLoS One, 2013;8(3):e58902.
    PMID: 23536834 DOI: 10.1371/journal.pone.0058902
    BACKGROUND: Mechanomyography (MMG) has been extensively applied in clinical and experimental practice to examine muscle characteristics including muscle function (MF), prosthesis and/or switch control, signal processing, physiological exercise, and medical rehabilitation. Despite several existing MMG studies of MF, there has not yet been a review of these. This study aimed to determine the current status on the use of MMG in measuring the conditions of MFs.

    METHODOLOGY/PRINCIPAL FINDINGS: Five electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. Two authors independently assessed selected articles using an MS-Word based form created for this review. Several domains (name of muscle, study type, sensor type, subject's types, muscle contraction, measured parameters, frequency range, hardware and software, signal processing and statistical analysis, results, applications, authors' conclusions and recommendations for future work) were extracted for further analysis. From a total of 2184 citations 119 were selected for full-text evaluation and 36 studies of MFs were identified. The systematic results find sufficient evidence that MMG may be used for assessing muscle fatigue, strength, and balance. This review also provides reason to believe that MMG may be used to examine muscle actions during movements and for monitoring muscle activities under various types of exercise paradigms.

    CONCLUSIONS/SIGNIFICANCE: Overall judging from the increasing number of articles in recent years, this review reports sufficient evidence that MMG is increasingly being used in different aspects of MF. Thus, MMG may be applied as a useful tool to examine diverse conditions of muscle activity. However, the existing studies which examined MMG for MFs were confined to a small sample size of healthy population. Therefore, future work is needed to investigate MMG, in examining MFs between a sufficient number of healthy subjects and neuromuscular patients.

    Matched MeSH terms: Muscle Fatigue/physiology
  8. Ibitoye MO, Hamzaid NA, Hasnan N, Abdul Wahab AK, Davis GM
    PLoS One, 2016;11(2):e0149024.
    PMID: 26859296 DOI: 10.1371/journal.pone.0149024
    BACKGROUND: Rapid muscle fatigue during functional electrical stimulation (FES)-evoked muscle contractions in individuals with spinal cord injury (SCI) is a significant limitation to attaining health benefits of FES-exercise. Delaying the onset of muscle fatigue is often cited as an important goal linked to FES clinical efficacy. Although the basic concept of fatigue-resistance has a long history, recent advances in biomedical engineering, physiotherapy and clinical exercise science have achieved improved clinical benefits, especially for reducing muscle fatigue during FES-exercise. This review evaluated the methodological quality of strategies underlying muscle fatigue-resistance that have been used to optimize FES therapeutic approaches. The review also sought to synthesize the effectiveness of these strategies for persons with SCI in order to establish their functional impacts and clinical relevance.

    METHODS: Published scientific literature pertaining to the reduction of FES-induced muscle fatigue was identified through searches of the following databases: Science Direct, Medline, IEEE Xplore, SpringerLink, PubMed and Nature, from the earliest returned record until June 2015. Titles and abstracts were screened to obtain 35 studies that met the inclusion criteria for this systematic review.

    RESULTS: Following the evaluation of methodological quality (mean (SD), 50 (6) %) of the reviewed studies using the Downs and Black scale, the largest treatment effects reported to reduce muscle fatigue mainly investigated isometric contractions of limited functional and clinical relevance (n = 28). Some investigations (n = 13) lacked randomisation, while others were characterised by small sample sizes with low statistical power. Nevertheless, the clinical significance of emerging trends to improve fatigue-resistance during FES included (i) optimizing electrode positioning, (ii) fine-tuning of stimulation patterns and other FES parameters, (iii) adjustments to the mode and frequency of exercise training, and (iv) biofeedback-assisted FES-exercise to promote selective recruitment of fatigue-resistant motor units.

    CONCLUSION: Although the need for further in-depth clinical trials (especially RCTs) was clearly warranted to establish external validity of outcomes, current evidence was sufficient to support the validity of certain techniques for rapid fatigue-reduction in order to promote FES therapy as an integral part of SCI rehabilitation. It is anticipated that this information will be valuable to clinicians and other allied health professionals administering FES as a treatment option in rehabilitation and aid the development of effective rehabilitation interventions.

    Matched MeSH terms: Muscle Fatigue/physiology*
  9. Hussain J, Sundaraj K, Subramaniam ID, Lam CK
    J Musculoskelet Neuronal Interact, 2019 09 01;19(3):276-285.
    PMID: 31475934
    OBJECTIVE: The objective of this study was to investigate fatigue in the three heads of the triceps brachii (TB) muscle using surface electromyography (sEMG) obtained at 30%, 45% and 60% of maximal voluntary contraction (MVC).

    METHODS: Twenty-five subjects performed isometric elbow extension until failure, and the rate of fatigue (ROF), time to fatigue (TTF) and normalized TTF (NTTF) were statistically analysed. Subsequently, the behaviour of root-mean-square (RMS), mean-power frequency (MPF) and median-power frequency (MDF) under pre-, onset- and post-fatigue conditions were compared.

    RESULTS: The findings indicated that, among the heads, ROF was statistically significant at 30% and 45% MVC (P<0.05) but TTF and NTTF at all intensities was statistically insignificant (P>0.05). For every head, only TTF was statistically significant (P<0.05) at different intensities. MPF and MDF under pre-, onset- and post-fatigue conditions were statistically significant (P<0.05) among the heads at all intensities, whereas RMS showed no such behaviour.

    CONCLUSION: The investigated parameters reveal that the three heads of TB act independently before fatigue onset and appear to work in union after fatigue. Synergist head pairs exhibit similar spectral and temporal behaviour in contrast to the non-synergist TB head pair. We find spectral parameters to be more specific predictors of fatigue.

    Matched MeSH terms: Muscle Fatigue/physiology*
  10. Talib I, Sundaraj K, Lam CK, Sundaraj S
    J Musculoskelet Neuronal Interact, 2018 12 01;18(4):446-462.
    PMID: 30511949
    This systematic review aims to categorically analyses the literature on the assessment of biceps brachii (BB) muscle activity through mechanomyography (MMG). The application of our search criteria to five different databases identified 319 studies. A critical review of the 48 finally selected records, revealed the diversity of protocols and parameters that are employed in MMG-based assessments of BB muscle activity. The observations were categorized into the following: muscle torque, fatigue, strength and physiology. The available information on the muscle contraction protocol, sensor(s), MMG signal parameters and obtained results were then tabulated based on these categories for further analysis. The review affirms that - 1) MMG is suitable for skeletal muscle activity assessment and can be employed potentially for further investigation of the BB muscle activity and condition (e.g., force, torque, fatigue, and contractile properties), 2) a majority of the records focused on static contractions of the BB, and the analysis of dynamic muscle contractions using MMG is thus a research gap, and 3) very few studies have focused on the analysis of BB muscle activity under externally stimulated contractions. Taken together, the findings of this review on BB activity assessment using MMG affirm the potential of MMG as an alternative tool.
    Matched MeSH terms: Muscle Fatigue/physiology*
  11. Naeem J, Hamzaid NA, Azman AW, Bijak M
    Biomed Tech (Berl), 2020 Aug 27;65(4):461-468.
    PMID: 32304295 DOI: 10.1515/bmt-2019-0191
    Functional electrical stimulation (FES) has been used to produce force-related activities on the paralyzed muscle among spinal cord injury (SCI) individuals. Early muscle fatigue is an issue in all FES applications. If not properly monitored, overstimulation can occur, which can lead to muscle damage. A real-time mechanomyography (MMG)-based FES system was implemented on the quadriceps muscles of three individuals with SCI to generate an isometric force on both legs. Three threshold drop levels of MMG-root mean square (MMG-RMS) feature (thr50, thr60, and thr70; representing 50%, 60%, and 70% drop from initial MMG-RMS values, respectively) were used to terminate the stimulation session. The mean stimulation time increased when the MMG-RMS drop threshold increased (thr50: 22.7 s, thr60: 25.7 s, and thr70: 27.3 s), indicating longer sessions when lower performance drop was allowed. Moreover, at thr70, the torque dropped below 50% from the initial value in 14 trials, more than at thr50 and thr60. This is a clear indication of muscle fatigue detection using the MMG-RMS value. The stimulation time at thr70 was significantly longer (p = 0.013) than that at thr50. The results demonstrated that a real-time MMG-based FES monitoring system has the potential to prevent the onset of critical muscle fatigue in individuals with SCI in prolonged FES sessions.
    Matched MeSH terms: Muscle Fatigue
  12. Noor'Ain Azizan, Seri Rahayu Kamat, Nur Syafiqah Rayme, Ruzy Haryati Hambali
    MyJurnal
    Repetitive movement can lead to the pain muscle, nerves, and tendons that cause by
    repetitive overuse of working task. The muscle will fatigue due to; repetitive
    movement, force that been applied, posture during working and duration of working.
    The stress level during working can influent the energy performance usage during
    working. The aim of this paper is to analyse the influence of heart rate and muscle
    activity of workers in composite manufacturing towards muscle fatigue. The data was
    collected for a worker in hand layup department and the Qualitative method was used
    in a way to investigate the working load and level of pain received by their body. Then,
    the Qualitative data was sorted and the respondent proceeded for a Quantitative
    method which involves muscle activity analysis and heart rate analysis. The tools that
    were used to conduct these experiments were surface electromyography (sEMG),
    Wristwatch with chest strap and perceived stress scale (PSS). The experimentation
    used to calculate the average reading of heart rate and muscle activity during working
    and detect the duration the muscle to start fatigue. Moreover, this paper analysed the
    relationship between heart rate and muscle activity through the duration of working.
    As an overall finding of this research, it was shown that the heart rate of the workers
    influence the muscle activity of workers and has high potential relationship to the
    fatigue of muscles of the workers in the layup department.
    Matched MeSH terms: Muscle Fatigue
  13. Mohd Safee MK, Abu Osman NA
    Occup Ther Int, 2021;2021:4357473.
    PMID: 34707468 DOI: 10.1155/2021/4357473
    Muscle fatigue is a decline in muscle maximum force during contraction and can influence the fall risk among people. This study is aimed at identifying the effect of fatigue on prospective fall risk in transfemoral amputees (TFA). Fourteen subjects were involved in this study with TFA (34.7 ± 8.1 yrs, n = 7) and normal subjects (31.1 ± 7.4 yrs, n = 7). Fatigue of lower limb muscles was induced with the fatigue protocol. Subjects were tested prefatigue and postfatigue using the standardized fall risk assessment. All results were calculated and compared between pre- and postfatigue to identify fatigue's effect on both groups of subjects. The results showed that the fall risk increased significantly during pre- and postfatigue for TFA (p = 0.018), while there were no significant differences in normal subjects (p = 0.149). Meanwhile, the fall risk between TFA and normal subjects for prefatigue (p = 0.082) and postfatigue (p = 0.084) also showed no significant differences. The percentage (%) of increased fall risk for TFA was 19.2% compared to normal subjects only 16.7%. However, 61.4% increased of % fall risk in TFA after fatigue by using the baseline of the normal subject as the normalized % of fall risk. The increasing fall risks for TFA after fatigue are three times higher than the potential fall risk in normal subjects. The result indicates that they need to perform more precautions while prolonging lower limb activities. These results showed the implications of fatigue that can increase the fall risk due to muscle fatigue from repetitive and prolonged activities. Therefore, rehabilitation programs can be done very safely and precisely so that therapists can pursue fitness without aggravating existing injuries.
    Matched MeSH terms: Muscle Fatigue
  14. Mohamad Ismail MR, Lam CK, Sundaraj K, Rahiman MHF
    J Musculoskelet Neuronal Interact, 2021 12 01;21(4):481-494.
    PMID: 34854387
    OBJECTIVE: This paper presents the analyses of the fatigue effect on the cross-talk in mechanomyography (MMG) signals of extensor and flexor forearm muscles during pre- and post-fatigue maximum voluntary isometric contraction (MVIC).

    METHODS: Twenty male participants performed repetitive submaximal (60% MVIC) grip muscle contractions to induce muscle fatigue and the results were analyzed during the pre- and post-fatigue MVIC. MMG signals were recorded on the extensor digitorum (ED), extensor carpi radialis longus (ECRL), flexor digitorum superficialis (FDS) and flexor carpi radialis (FCR) muscles. The cross-correlation coefficient was used to quantify the cross-talk values in forearm muscle pairs (MP1, MP2, MP3, MP4, MP5 and MP6). In addition, the MMG RMS and MMG MPF were calculated to determine force production and muscle fatigue level, respectively.

    RESULTS: The fatigue effect significantly increased the cross-talk values in forearm muscle pairs except for MP2 and MP6. While the MMG RMS and MMG MPF significantly decreased (p<0.05) based on the examination of the mean differences from pre- and post-fatigue MVIC.

    CONCLUSION: The presented results can be used as a reference for further investigation of cross-talk on the fatigue assessment of extensor and flexor muscles' mechanic.

    Matched MeSH terms: Muscle Fatigue
  15. Mohamad NZ, Hamzaid NA, Davis GM, Abdul Wahab AK, Hasnan N
    Sensors (Basel), 2017 Jul 14;17(7).
    PMID: 28708068 DOI: 10.3390/s17071627
    A mechanomyography muscle contraction (MC) sensor, affixed to the skin surface, was used to quantify muscle tension during repetitive functional electrical stimulation (FES)-evoked isometric rectus femoris contractions to fatigue in individuals with spinal cord injury (SCI). Nine persons with motor complete SCI were seated on a commercial muscle dynamometer that quantified peak torque and average torque outputs, while measurements from the MC sensor were simultaneously recorded. MC-sensor-predicted measures of dynamometer torques, including the signal peak (SP) and signal average (SA), were highly associated with isometric knee extension peak torque (SP: r = 0.91, p < 0.0001), and average torque (SA: r = 0.89, p < 0.0001), respectively. Bland-Altman (BA) analyses with Lin's concordance (ρC) revealed good association between MC-sensor-predicted peak muscle torques (SP; ρC = 0.91) and average muscle torques (SA; ρC = 0.89) with the equivalent dynamometer measures, over a range of FES current amplitudes. The relationship of dynamometer torques and predicted MC torques during repetitive FES-evoked muscle contraction to fatigue were moderately associated (SP: r = 0.80, p < 0.0001; SA: r = 0.77; p < 0.0001), with BA associations between the two devices fair-moderate (SP; ρC = 0.70: SA; ρC = 0.30). These findings demonstrated that a skin-surface muscle mechanomyography sensor was an accurate proxy for electrically-evoked muscle contraction torques when directly measured during isometric dynamometry in individuals with SCI. The novel application of the MC sensor during FES-evoked muscle contractions suggested its possible application for real-world tasks (e.g., prolonged sit-to-stand, stepping,) where muscle forces during fatiguing activities cannot be directly measured.
    Matched MeSH terms: Muscle Fatigue
  16. Ibitoye MO, Estigoni EH, Hamzaid NA, Wahab AK, Davis GM
    Sensors (Basel), 2014;14(7):12598-622.
    PMID: 25025551 DOI: 10.3390/s140712598
    The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05) between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population.
    Matched MeSH terms: Muscle Fatigue*
  17. Ajit Singh DK, Bailey M, Lee R
    Muscle Nerve, 2011 Jul;44(1):74-9.
    PMID: 21488056 DOI: 10.1002/mus.21998
    Loss of lumbar extensor muscle strength and fatigue resistance may contribute to functional disability.
    Matched MeSH terms: Muscle Fatigue/physiology*
  18. Zadry HR, Dawal SZ, Taha Z
    Int J Occup Saf Ergon, 2011;17(4):373-84.
    PMID: 22152503
    A study was conducted to investigate the effects of repetitive light tasks of low and high precision on upper limb muscles and brain activities. Surface electromyography (EMG) and electroencephalography (EEG) were used to measure the muscle and brain activity of 10 subjects. The results show that the root-mean-square (RMS) and mean power frquency (MPF) of the muscle activity and the mean power of the EEG alpha bands were higher on the high-precision task than on the low-precision one. There was also a high and significant correlation between upper limb muscle and brain activity during the tasks. The longer the time and the more precise the task, the more the subjects become fatigued both physically and mentally. Thus, these results could be potentially useful in managing fatigue, especially fatique related to muscle and mental workload.
    Matched MeSH terms: Muscle Fatigue/physiology
  19. Zadry HR, Dawal SZ, Taha Z
    Int J Occup Saf Ergon, 2016 Sep;22(3):374-83.
    PMID: 27053140 DOI: 10.1080/10803548.2016.1150094
    This study was conducted to develop muscle and mental activities on repetitive precision tasks. A laboratory experiment was used to address the objectives. Surface electromyography was used to measure muscle activities from eight upper limb muscles, while electroencephalography recorded mental activities from six channels. Fourteen university students participated in the study. The results show that muscle and mental activities increase for all tasks, indicating the occurrence of muscle and mental fatigue. A linear relationship between muscle activity, mental activity and time was found while subjects were performing the task. Thus, models were developed using those variables. The models were found valid after validation using other students' and workers' data. Findings from this study can contribute as a reference for future studies investigating muscle and mental activity and can be applied in industry as guidelines to manage muscle and mental fatigue, especially to manage job schedules and rotation.
    Matched MeSH terms: Muscle Fatigue/physiology
  20. Naeem J, Hamzaid NA, Islam MA, Azman AW, Bijak M
    Med Biol Eng Comput, 2019 Jun;57(6):1199-1211.
    PMID: 30687901 DOI: 10.1007/s11517-019-01949-4
    Patients with spinal cord injury (SCI) benefit from muscle training with functional electrical stimulation (FES). For safety reasons and to optimize training outcome, the fatigue state of the target muscle must be monitored. Detection of muscle fatigue from mel frequency cepstral coefficient (MFCC) feature of mechanomyographic (MMG) signal using support vector machine (SVM) classifier is a promising new approach. Five individuals with SCI performed FES cycling exercises for 30 min. MMG signals were recorded on the quadriceps muscle group (rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM)) and categorized into non-fatigued and fatigued muscle contractions for the first and last 10 min of the cycling session. For each subject, a total of 1800 contraction-related MMG signals were used to train the SVM classifier and another 300 signals were used for testing. The average classification accuracy (4-fold) of non-fatigued and fatigued state was 90.7% using MFCC feature, 74.5% using root mean square (RMS), and 88.8% with combined MFCC and RMS features. Inter-subject prediction accuracy suggested training and testing data to be based on a particular subject or large collection of subjects to improve fatigue prediction capacity. Graphical abstract ᅟ.
    Matched MeSH terms: Muscle Fatigue/physiology*
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