Displaying all 7 publications

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  1. Li W, Hadizadeh M, Yusof A, Naharudin MN
    Sci Rep, 2024 Feb 27;14(1):4736.
    PMID: 38413632 DOI: 10.1038/s41598-024-54789-0
    The effects of IT and R.I.C.E. treatment on arm muscle performance in overhead athletes with elbow pain (EP) have been partially validated. However, there is a lack of research evidence regarding the efficacy of these two methods on arm muscle performance among swimmers with EP. The aim of this study was to investigate the trends and differences in the effects of IT and R.I.C.E. treatment on arm muscle performance among swimmers with EP. The main outcomes were the time effects and group effects of interventions on muscle voluntary contraction (MVC). Sixty elite freestyle swimmers from Tianjin, China, voluntarily participated in the study and completed a 10-week intervention program. Swimmers with EP in the IT group showed a positive trend in MVC, with an approximately 2% increase, whereas the MVC of subjects in the R.I.C.E. treatment group and control group decreased by approximately 4% and 5%, respectively. In comparison, the effects of the IT intervention on the MVC of the triceps and brachioradialis muscles in swimmers with EP were significant (p = 0.042 
    Matched MeSH terms: Isometric Contraction/physiology
  2. 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: Isometric Contraction/physiology*
  3. Ali MA, Sundaraj K, Ahmad RB, Ahamed NU, Islam MA, Sundaraj S
    Technol Health Care, 2014;22(4):617-25.
    PMID: 24990168 DOI: 10.3233/THC-140833
    Normally, surface electromyography electrodes are used to evaluate the activity of superficial muscles during various kinds of voluntary contractions of muscle fiber. The objective of the present study was to investigate the effect of repetitive isometric contractions on the three heads of the triceps brachii muscle during handgrip force exercise.
    Matched MeSH terms: Isometric Contraction/physiology*
  4. Islam MA, Sundaraj K, Ahmad RB, Sundaraj S, Ahamed NU, Ali MA
    PLoS One, 2014;9(5):e96628.
    PMID: 24802858 DOI: 10.1371/journal.pone.0096628
    This study aimed: i) to examine the relationship between the magnitude of cross-talk in mechanomyographic (MMG) signals generated by the extensor digitorum (ED), extensor carpi ulnaris (ECU), and flexor carpi ulnaris (FCU) muscles with the sub-maximal to maximal isometric grip force, and with the anthropometric parameters of the forearm, and ii) to quantify the distribution of the cross-talk in the MMG signal to determine if it appears due to the signal component of intramuscular pressure waves produced by the muscle fibers geometrical changes or due to the limb tremor.
    Matched MeSH terms: Isometric Contraction/physiology*
  5. Loh PY, Hayashi K, Nasir N, Muraki S
    J Mot Behav, 2020;52(5):634-642.
    PMID: 31571525 DOI: 10.1080/00222895.2019.1670128
    This study investigated the muscle activity and force variability in response to perturbation of assistive force during isometric elbow flexion. Sixteen healthy right-handed young men (age: 22.0 ± 1.1 years; height: 171.9 ± 4.8 cm; weight 68.4 ± 11.2 kg) were recruited and the muscle activity of biceps brachii and triceps brachii were assessed using surface electromyography. Workload force and assistive force applied on isometric elbow flexion significantly affected the changes in both biceps and triceps muscle activities. A higher assistive force was shown to result in reduced biceps muscle activity compared to the unassisted period. In contrast, the efficiency of the assistive force acting on the biceps decreased as the assistive force increased. In general, the force variability of the biceps muscle remained approximately the same at lower workload force conditions than that at higher workload force conditions. In conclusion, higher assistive force may not yield a higher performance efficiency in human-assistive force interaction.
    Matched MeSH terms: Isometric Contraction/physiology*
  6. Talib I, Sundaraj K, Lam CK
    J Musculoskelet Neuronal Interact, 2020 06 01;20(2):194-205.
    PMID: 32481235
    OBJECTIVE: To analyse the influence of muscle fibre axis on the degree of crosstalk in mechanomyographic (MMG) signals during sustained isometric forearm flexion, pronation and supination exercises performed at 80% maximum voluntary contraction (MVC) at an elbow joint angle of 90°.

    METHODS: MMG signals in longitudinal, lateral and transverse directions of muscle fibres were recorded from the elbow flexors of twenty-five male subjects using triaxial accelerometers. Cross-correlation coefficients were used to quantify the degree of crosstalk in all nine possible pairs of fibre axes, all muscle pairs and all exercises.

    RESULTS: MMG root mean square (RMS) was statistically significant among the fibre axes (p<0.05, η2=0.17- 0.34) except for biceps brachii and brachioradialis in supination and brachialis in flexion. Overall mean crosstalk values in the three muscle pairs (biceps brachii & brachialis, brachialis & brachioradialis and brachioradialis & biceps brachii) were found to be 6.09-52.17%, 4.01-61.42% and 2.16-51.85%, respectively. Crosstalk values showed statistical significance among all nine axes pairs (p<0.05, η2=0.16-0.51) except for biceps brachii & brachialis during pronation. The transverse axes pair generated the lowest mean crosstalk values (2.16-9.14%).

    CONCLUSION: MMG signals recorded using accelerometers from the transverse axes of muscle fibres in the elbow flexors are unique and yield the least amount of crosstalk.

    Matched MeSH terms: Isometric Contraction/physiology*
  7. Nazmi N, Abdul Rahman MA, Yamamoto S, Ahmad SA, Zamzuri H, Mazlan SA
    Sensors (Basel), 2016 Aug 17;16(8).
    PMID: 27548165 DOI: 10.3390/s16081304
    In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and 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 would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.
    Matched MeSH terms: Isometric Contraction/physiology*
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