Narrow Results

Muscle moment arm defines the function of the muscle. To date, moment arms of the arm muscles at the glenohumeral joint using the tendon excursion method have not been reported. As the functions of these muscles at the shoulder joint are controversial, this study was undertaken to determine the moment arms of the long and short heads of the biceps (LHB, SHB), the coracobrachialis, and the long head of the triceps muscles. The moment arms were determined in 10 cadaveric shoulders by measuring the tendon excursion when the arm was rotated by 1 radian (57.3°) in 22 different motions. The LHB was a flexor, horizontal flexor, and abductor. The SHB and coracobrachialis were flexors, horizontal flexors, and adductors. The long head of the triceps was an extensor and adductor. Arm rotation significantly affected the function of the LHB only: it was an internal rotator in flexion and an external rotator in abduction. This study clarifies the individual function of the arm muscles at the glenohumeral joint.

The analysis of surface electromyography (sEMG) signals is significant in the detection of muscle fatigue. These signals exhibit a great degree of complexity, nonlinearity, and chaos. Also, presence of high degree of fluctuations in the signal makes its analysis a difficult task. This study aims to analyze the nonlinear dynamics of muscle fatigue conditions using Fuzzy recurrence networks (FRN). Dynamic sEMG signals are measured from biceps brachii muscle of 45 normal subjects referenced to 50% of maximal voluntary contractions (MVC) for this. Recorded signals are then pre-processed and divided into ten equal parts. FRNs are transformed from the signals. The network features, namely average weighted degree (AWD) and Closeness centrality (CC) are extracted to analyze the muscle dynamics during fatiguing conditions. The decrease in these features during fatigue indicates a reduction in signal complexity and an increase in complex network stiffness. Both AWD and CC features are statistically significant with $p<0.05$. Further, these features are classified using Naïve Bayes (NB), k nearest neighbor (kNN) and random forest (RF) algorithms. Maximum accuracy of 96.90% is achieved using kNN classifier for combined FRN features. Thus, the proposed features provide high-quality inputs to the neural networks that may be helpful in analyzing the complexity and stiffness of neuromuscular system under various myoneural conditions.

Magnetic resonance images and ultrasound images were used to examine the architecture of the distal biceps brachii muscle in 12 unimpaired subjects. The distal biceps brachii tendon continued as an internal aponeurosis that spanned 34± 4% of the length of the biceps brachii long head muscle on average. The distal muscle fascicles inserted at angles to this aponeurosis; fascicles anterior to the aponeurosis inserted at a significantly greater (p ≤ 0.05) angle (17°) than the fascicles posterior to the aponeurosis (14°) in the distal 2 cm of muscle when the elbow was extended. Mean fascicle insertion angles were on average 3–4° greater with the elbow flexed 90° against a 5% maximum voluntary contraction load as compared to their values with the elbow extended. These data provide the basis for designing experiments to measure muscle and tendon motion in vivo.

Although clinicians judge muscle tenseness by palpation, methods to quantify this have not become established. We examined the reliability and validity of a commercially available myotonometer to assess the biceps brachii and brachioradialis. Torques ranging from 0–72% of maximum effort were isometrically resisted in five men and five women, all healthy and 21–23 years of age. Root-mean-square of surface electromyographic response was also measured. Intraclass correlations were 0.80 or higher within sessions but decreased to 0.57 between sessions except for myotonometry of the biceps brachii. Correlation with isometric load was 0.79 or higher for both myotonometry and electromyography, but these relations were consistently curvilinear. The myotonometer is more useful for fleshy muscles like the biceps brachii than for thin muscles like the brachioradialis. Because hardness has a curvilinear relation with tension in the muscle, hardness cannot be considered strictly equivalent to tension.

In this paper, an attempt has been made to analyze surface electromyography (sEMG) signals under non-fatigue and fatigue conditions using time-frequency based features. The sEMG signals are recorded from biceps brachii muscle of 50 healthy volunteers under well-defined protocol. The pre-processed signals are divided into six equal epochs. The first and last segments are considered as non-fatigue and fatigue zones respectively. Further, these signals are subjected to B-distribution based quadratic time-frequency distribution (TFD). Time frequency based features such as instantaneous median frequency (IMDF) and instantaneous mean frequency (IMNF) are extracted. The expression of spectral entropy is modified to obtain instantaneous spectral entropy (ISPEn) from the time-frequency spectrum. The results show that all the extracted features are distinct in both conditions. It is also observed that the values of all features are higher in non-fatigue zone compared to fatigue condition. It appears that this method is useful in analysing various neuromuscular conditions using sEMG signals.

Viscoelastic properties of skeletal muscle tissue are known to be impacted by fatiguing contractions. In this study, an attempt has been made to utilize myotonometry for analyzing the relationship between muscle viscoelasticity and contractile behaviors in a fatiguing task. For this purpose, thirteen young healthy volunteers are recruited to perform the fatiguing isometric task and the time to task failure (TTF) is recorded. Myotonometric parameters and simultaneous surface electromyographic (sEMG) signals are recorded from the Biceps Brachii muscle of the flexed arm. The correlation between myotonometric parameters and TTF is further analyzed. Cross-validation with sEMG features is also performed. Stiffness of muscle has a positive correlation with TTF in the left hand ($p<0.05$). Damping property of the nonfatigued muscle is positively associated with the fatigue-induced changes in amplitude features of sEMG signal in the right hand ($p<0.05$). The normalized rate of change of mean frequency of sEMG signal has a positive correlation with stiffness values in both of the hands ($p<0.05$). Muscle viscoelasticity is demonstrated to influence the progression of fatigue, although the difference in motor control due to handedness is also found to be an important factor. The results are promising to improve the understanding of the effect of muscle mechanics in fatigue-induced task failure.

Restoration of finger extension in mutilating hand injuries is crucial for restoring prehension and independent use of the hand. Patients often express desire to restore finger extension once finger flexion is achieved. However, the extensive forearm injury precludes use of any of conventional donors like the wrist or finger flexors for transfer to restore finger extension. Two patients with sequelae of mangled forearm injuries, underwent biceps and long head of triceps transfer to the finger extensors to improve opening up of the fingers. We discuss the treatment considerations while planning these transfers and provide the technical details, rehabilitation and outcome of these patients. Both the patients expressed dramatic improvement of their hand function and were satisfied with the outcome. Biceps and long head of triceps could serve as an effective second-line donor for restoration of finger extension when the conventional donors are not available.

Level of Evidence: Level V (Therapeutic)