Displaying all 5 publications

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  1. Selvanayagam VS, Riek S, DE Rugy A, Carroll TJ
    Med Sci Sports Exerc, 2016 09;48(9):1835-46.
    PMID: 27116648 DOI: 10.1249/MSS.0000000000000956
    PURPOSE: Goal-directed movements tend to resemble the characteristics of previously executed actions. Here we investigated whether a single bout of strength training, which typically involves stereotyped actions requiring strong neural drive, can bias subsequent aiming behavior toward the direction of trained forces.

    METHODS: In experiment 1 (n = 10), we tested the direction of force exerted in an isometric aiming task before and after 40 repetitions of 2-s maximal-force ballistic contractions toward a single directional target. In experiment 2 (n = 12), each participant completed three training conditions in a counterbalanced crossover design. In two conditions, both the aiming task and the training were conducted in the same (neutral) forearm posture. In one of these conditions, the training involved weak forces to determine whether the level of neural drive during training influences the degree of bias. In the third condition, high-force training contractions were performed in a 90° pronated forearm posture, whereas the low-force aiming task was performed in a neutral forearm posture. This dissociated the extrinsic training direction from the pulling direction of the trained muscles during the aiming task.

    RESULTS: In experiment 1, we found that aiming direction was biased toward the training direction across a large area of the work space (approximately ±135°; tested for 16 targets spaced 22.5° apart), whereas in experiment 2, we found systematic bias in aiming toward the training direction defined in extrinsic space, but only immediately after high-force contractions.

    CONCLUSION: Our findings suggest that bias effects of training involving strong neural drive generalize broadly to untrained movement directions and are expressed according to extrinsic rather than muscle-based coordinates.

    Matched MeSH terms: Forearm/physiology
  2. Uwamahoro R, Sundaraj K, Feroz FS
    Sensors (Basel), 2023 Sep 29;23(19).
    PMID: 37836995 DOI: 10.3390/s23198165
    Neuromuscular electrical stimulation plays a pivotal role in rehabilitating muscle function among individuals with neurological impairment. However, there remains uncertainty regarding whether the muscle's response to electrical excitation is affected by forearm posture, joint angle, or a combination of both factors. This study aimed to investigate the effects of forearm postures and elbow joint angles on the muscle torque and MMG signals. Measurements of the torque around the elbow and MMG of the biceps brachii (BB) muscle were conducted in 36 healthy subjects (age, 22.24 ± 2.94 years; height, 172 ± 0.5 cm; and weight, 67.01 ± 7.22 kg) using an in-house elbow flexion testbed and neuromuscular electrical stimulation (NMES) of the BB muscle. The BB muscle was stimulated while the forearm was positioned in the neutral, pronation, or supination positions. The elbow was flexed at angles of 10°, 30°, 60°, and 90°. The study analyzed the impact of the forearm posture(s) and elbow joint angle(s) on the root-mean-square value of the torque (TQRMS). Subsequently, various MMG parameters, such as the root-mean-square value (MMGRMS), the mean power frequency (MMGMPF), and the median frequency (MMGMDF), were analyzed along the longitudinal, lateral, and transverse axes of the BB muscle fibers. The test-retest interclass correlation coefficient (ICC21) for the torque and MMG ranged from 0.522 to 0.828. Repeated-measure ANOVAs showed that the forearm posture and elbow flexion angle significantly influenced the TQRMS (p < 0.05). Similarly, the MMGRMS, MMGMPF, and MMGMDF showed significant differences among all the postures and angles (p < 0.05). However, the combined main effect of the forearm posture and elbow joint angle was insignificant along the longitudinal axis (p > 0.05). The study also found that the MMGRMS and TQRMS increased with increases in the joint angle from 10° to 60° and decreased at greater angles. However, during this investigation, the MMGMPF and MMGMDF exhibited a consistent decrease in response to increases in the joint angle for the lateral and transverse axes of the BB muscle. These findings suggest that the muscle contraction evoked by NMES may be influenced by the interplay between actin and myosin filaments, which are responsible for muscle contraction and are, in turn, influenced by the muscle length. Because restoring the function of limbs is a common goal in rehabilitation services, the use of MMG in the development of methods that may enable the real-time tracking of exact muscle dimensional changes and activation levels is imperative.
    Matched MeSH terms: Forearm/physiology
  3. 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: Forearm/physiology*
  4. Talib I, Sundaraj K, Lam CK
    Sci Rep, 2019 11 07;9(1):16166.
    PMID: 31700129 DOI: 10.1038/s41598-019-52536-4
    This study aimed to quantify the association of four anthropometric parameters of the human arm, namely, the arm circumference (CA), arm length (LA), skinfold thickness (ST) and inter-sensor distance (ISD), with amplitude (RMS) and crosstalk (CT) of mechanomyography (MMG) signals. Twenty-five young, healthy, male participants were recruited to perform forearm flexion, pronation and supination torque tasks. Three accelerometers were employed to record the MMG signals from the biceps brachii (BB), brachialis (BRA) and brachioradialis (BRD) at 80% maximal voluntary contraction (MVC). Signal RMS was used to quantify the amplitude of the MMG signals from a muscle, and cross-correlation coefficients were used to quantify the magnitude of the CT among muscle pairs (BB & BRA, BRA & BRD, and BB & BRD). For all investigated muscles and pairs, RMS and CT showed negligible to low negative correlations with CA, LA and ISD (r = -0.0001--0.4611), and negligible to moderate positive correlations with ST (r = 0.004-0.511). However, almost all of these correlations were statistically insignificant (p > 0.05). These findings suggest that RMS and CT values for the elbow flexor muscles recorded and quantified using accelerometers appear invariant to anthropometric parameters.
    Matched MeSH terms: Forearm/physiology*
  5. 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: Forearm/physiology
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