The recruitment and firing rate of biceps brachii (BB) and brachioradialis (BR) motor units (MUs) were studied in the course of fatiguing isometric contractions at 20%-30% of maximal voluntary contraction (MVC). MU recruitment generally occurred throughout the maintained contraction and was similar for BB and BR muscles. Newly recruited MUs started to discharge in the form of bursts, the duration of which increased until a continuous rhythmical firing was achieved. Within each burst, the first interval between two consecutive discharges was usually the shortest. MU threshold was lowered just after the limit time of the maintained contraction. The MU's firing rate either increased or remained stable as a function of the elapsed time. It is concluded that (1) in fatiguing isometric contractions at 20%-30% MVC contractile failure is mainly compensated for by MU recruitment and a lowered MU threshold and (2) differences between in surface changes in the electromyogram of BB and BR muscles cannot easily be explained by related differences in MU firing rate and recruitment.

Spectral electromyographic (EMG) changes in human quadriceps muscles were studied to reinvestigate discrepant results concerning mean power frequency (MPF) changes during dynamic exercise. An incremental test consisting of a quasi-linear increase in mechanical power on a bicycle ergometer (for 20-100% of maximal aerobic power) was performed by forty subjects. During this test, surface EMGs from the quadriceps muscles showed that EMG total power (PEMG) increased with a curvilinear pattern for every subject, whereas MPF kinetics varied from one subject to another. PEMG changes had the same shape, which would lead to disappointing results in terms of discrimination between subjects. The ability of normalized MPF kinetics to define significant clusters of subjects was tested using a principal component analysis. This analysis led to the projection of all experiments onto a plane and revealed a relevant grouping of MPF profiles. Differences in MPF kinetics between clusters are interpreted in terms of various possibilities of balance between physiological events leading to an increase or a decrease in MPF.

During an external isometric constant torque (25% of the maximal voluntary contraction) maintained until the maximal endurance time (limit time), we analysed and compared the changes in electromyographic (EMG) activity illustrating muscular fatigue simultaneously with mechanical activity (the tangential acceleration theta") related to physiological tremor. The EMG activities recorded were of two agonistic flexors, the biceps brachii (BB) and the brachioradialis (BR) muscles and one of the main extensors, the triceps brachii (TB). The integrated EMG increase and the mean power frequency (MPF) of the power spectrum density function (PSDF) decrease were larger for BR than for BB activity. These two findings suggested a greater BR fatigability. However, it is shown that differences between BB and BR MPF changes could be related to differences in the PSDF upper frequency limit of the two muscles and also to the relative magnitude of their tremor component.

The purpose of this study was to quantify the neuromuscular cervical adaptations to an 8 week strength training programme. Seven healthy men, with no pathological conditions of the neck, performed a lateral flexion isometric resistance-training programme three times a week. The training sessions consisted of one set of ten contractions, each of 6 s duration, at 60% of the predetermined maximal voluntary isometric torque (MVTim) (warm-up) and two sets of eight contractions, each of 6 s duration, at 80% MVTim. The training effects were evaluated in three ways: muscle size, strength and fatigability. The cross-sectional areas (CSA) of the trapezius (TRP) and sternocleidomastoideus (SCM) muscles were determined using a computerised tomographic scanner. Results showed an increase in the CSA of TRP and SCM muscles after training, 8.8% at C5 level and 6.4% at C7 level for SCM muscle and 12.2% at C7 level for TRP muscle. Strength increased significantly under both isometric and isokinetic conditions (35% and 20%, respectively). Muscle fatigability in lateral flexion was quantified during a sustained isometric contraction at 50% of MVTim. The shift of the mean power frequency of the electromyogram power spectrum density function of SCM muscle toward lower frequencies was less after training (14.6% compared to 6.8%). These results indicate the beneficial effect of a strength-training programme which increases neck muscle size and strength during lateral flexion, and decreases the fatigability of the superficial muscles of the neck.

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject’s movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

During incremental exercise on a cycle ergometer a study was made of the reproducibility of changes in electromyographic activity (EMG) of human quadriceps muscles. Seven subjects performed three periods of incremental exercise either every 2 weeks (G1: four subjects) or 6 weeks (G2: three subjects). Each test was normalized with respect to the maximal aerobic power (MAP) of the subject. It consisted of a quasilinear increase in mechanical power (from 20% to 100% MAP) during 8 min. For rectus femoris muscle activity, changes in total power spectrum (PEMG) and in mean power frequency (MPF) were fitted by a 3rd order polynomial function (named profile) and normalized with respect to the maximal value for PEMG and to the mean value for MPF. A curvilinear increase was found for PEMG. The MPF kinetics varied from one subject to another. These changes were either a continuous increase, or a continuous decrease, or an increase followed by a decrease. Only for G2, was MAP determined before each test in order to update the limits of the test. A good reproducibility of PEMG was shown by its mean magnitude [95.88%, (SD 3.92)] and by computing a mean correlation coefficient between profiles two by two [r2 = 0.948 (SD 0.028) n = 21]. Intraclass coefficient correlation (ICC) calculated for each subject indicated a high level of reproducibility for five of the seven subjects (ICC > 0.80). No clear effect of MAP updating on PEMG and MPF profile reproducibility was observed. Thus it is suggested that MPF kinetics may characterize a subject at a given moment while PEMG kinetics may illustrate a normal profile, and they may both characterize EMG changes for a population during incremental exercise.

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A technique is proposed that allows automatic decomposition of electromyographic (EMG) signals into their constituent motor unit action potential trains (MUAPTs). A specific iterative algorithm with a classification method using fuzzy-logic techniques was developed. The proposed classification method takes into account imprecise information, such as waveform instability and irregular firing patterns, that is often encountered in EMG signals. Classification features were determined by the combining of time position and waveform information. Statistical analysis of inter-pulse intervals and spike amplitude provided an accurate estimation of features used in the classification step. Algorithm performance was evaluated using simulated EMG signals composed of up to six different discharging motor units corrupted with white noise. The algorithm was then applied to real signals recorded by a high spatial resolution surface EMG device based on a Laplacian spatial filter. On six groups of 20 simulated signals, the decomposition algorithm performed with a maximum and an average mean error rate of 2.13% and 1.37%, respectively. On real surface EMG signals recorded at different force levels (from 10% to 40% of the maximum voluntary contraction), the algorithm correctly identified 21 MUAPTs, compared with the 29 MUAPTs identified by an experienced neurophysiologist. The efficiency of the decomposition on surface EMG signals makes this method very attractive for non-invasive investigation of physiological muscle properties. However, it can also be used to decompose intramuscularly recorded EMG signals.