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This review follows two previous papers [Farina et al. Appl Physiol (1985) 96: 1486–1495, 2004; Farina et al. J Appl Physiol (1985) 117: 1215–1230, 2014] in which we reflected on the use of surface electromyography (EMG) in the study of the neural control of movement. This series of papers began with an analysis of the indirect approaches of EMG processing to infer the neural control strategies and then closely followed the progress in EMG technology. In this third paper, we focus on three main areas: surface EMG modeling; surface EMG processing, with an emphasis on decomposition; and interfacing applications of surface EMG recordings. We highlight the latest advances in EMG models that allow fast generation of simulated signals from realistic volume conductors, with applications ranging from validation of algorithms to identification of nonmeasurable parameters by inverse modeling. Surface EMG decomposition is currently an established state-of-the-art tool for physiological investigations of motor units. It is now possible to identify large samples of motor units, to track motor units over multiple sessions, to partially compensate for the nonstationarities in dynamic contractions, and to decompose signals in real time. The latter achievement has facilitated advances in myocontrol, by using the online decoded neural drive as a control signal, such as in the interfacing of prostheses. Looking back over the 20 yr since our first review, we conclude that the recording and analysis of surface EMG signals have seen breakthrough advances in this period. Although challenges in its application and interpretation remain, surface EMG is now a solid and unique tool for the study of the neural control of movement. [ABSTRACT FROM AUTHOR]

The aim of our study was to compare the effects of two different plyometric training programs (targeting knee extensors or plantar flexors) on jump height and strength of leg muscles. Twenty‐nine male basketball players were assigned to the knee‐flexed (KF), knee‐extended (KE), or control groups. In addition to regular training, the KF group performed plyometric jumps (10 sets of 10 jumps, 3 sessions/week, 4 weeks) from 50 cm boxes with the knee flexed (90°–120°), whereas the KE group performed the jumps from 30 cm boxes with the knee much more extended (130°–170°). Jumping ability was evaluated with squat jumps (SJs), countermovement jumps (CMJs), and drop jumps from 20 cm (DJ20) and 40 cm (DJ40). Knee and ankle muscles were assessed during maximal isokinetic and isometric tests, and EMG activity was recorded from vastus lateralis and medial gastrocnemius. The KF group increased SJ (+10%, d = 0.86) and CMJ (+11%, d = 0.70) but decreased DJ40 height (−7%, d = −0.40). Conversely, the KE group increased DJ20 (+10%, d = 0.74) and DJ40 (+12%, d = 0.77) but decreased SJ height (−4%, d = −0.23). The reactivity index during DJs increased (+10% for DJ20, d = 0.47; +20% for DJ40, d = 0.91) for the KE group but decreased (−10%, d = −0.48) for the KF group during DJ40. Plantar flexor strength increased for the KE group (d = 0.72–1.00) but not for the KF group. Negative transfer across jumps is consistent with the principle of training specificity. Basketball players interested to perform fast rebounds in their training should avoid plyometric jumps with large knee flexions and long contact times. Highlights: Plyometric training specificity: different jump techniques (knee flexed vs. knee extended) elicited specific adaptations in jumping performance. Training with the knees flexed improved squat jump and countermovement jump height, whereas training with the knees extended augmented drop jump height.Negative transfer: the different jump techniques can have a negative influence on jump height and reactivity index. Drop jump height declined after knee‐flexed training, whereas squat jump height decreased after knee‐extended training.Plyometric training exercises should be aligned with sport‐specific movements to optimize performance. Basketball players who perform fast, powerful movements should avoid plyometric jumps with large knee flexions and long contact times. [ABSTRACT FROM AUTHOR]

The aim of our study was to compare the force steadiness and the discharge characteristics of motor units in the tibialis anterior (TA) during ankle dorsiflexion and foot adduction produced by submaximal isometric contractions with the dominant and non-dominant foot. Fifteen young men performed maximal and submaximal contractions at five target forces with both legs, and motor unit activity in TA was recorded using high-density electromyography. Maximal force and the fluctuations in force during submaximal contractions were similar between the two legs (p > 0.05). Motor unit activity was characterized by measures of mean discharge rate (MDR), coefficient of variation for interspike interval (CoV for ISI), and standard deviation of the filtered cumulative spike train (SD of fCST). There were no statistically significant differences in motor unit activity between legs during ankle dorsiflexion. In contrast, the MDR and the CoV for ISI but not the SD of fCST, were greater for the non-dominant foot compared with the dominant foot during foot adduction. Nonetheless, these differences in motor unit activity were not sufficient to influence the force fluctuations during the submaximal contractions. These results indicate that control of the force produced by TA during the two actions was not influenced by limb dominance. [ABSTRACT FROM AUTHOR]

The purpose of our study was to investigate the influence of a stretch intervention on the common modulation of discharge rate among motor units in the calf muscles during a submaximal isometric contraction. The current report comprises a computational analysis of a motor unit dataset that we published previously (Mazzo et al., 2021). Motor unit activity was recorded from the three main plantar flexor muscles while participants performed an isometric contraction at 10% of the maximal voluntary contraction force before and after each of two interventions. The interventions were a control task (standing balance) and static stretching of the plantar flexor muscles. A factorization analysis on the smoothed discharge rates of the motor units from all three muscles yielded three modes that were independent of the individual muscles. The composition of the modes was not changed by the standing‐balance task, whereas the stretching exercise reduced the average correlation in the second mode and increased it in the third mode. A centroid analysis on the correlation values showed that most motor units were associated with two or three modes, which were presumed to indicate shared synaptic inputs. The percentage of motor units adjacent to the seven centroids changed after both interventions: Control intervention, mode 1 decreased and the shared mode 1 + 2 increased; stretch intervention, shared modes either decreased (1 + 2) or increased (1 + 3). These findings indicate that the neuromuscular adjustments during both interventions were sufficient to change the motor unit modes when the same task was performed after each intervention. Key points: Based on covariation of the discharge rates of motor units in the calf muscles during a submaximal isometric contraction, factor analysis was used to assign the correlated discharge trains to three motor unit modes.The motor unit modes were determined from the combined set of all identified motor units across the three muscles before and after each participant performed a control and a stretch intervention.The composition of the motor unit modes changed after the stretching exercise, but not after the control task (standing balance).A centroid analysis on the distribution of correlation values found that most motor units were associated with a shared centroid and this distribution, presumably reflecting shared synaptic input, changed after both interventions.Our results demonstrate how the distribution of multiple common synaptic inputs to the motor neurons innervating the plantar flexor muscles changes after a brief series of stretches. [ABSTRACT FROM AUTHOR]