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The aim of this study was to analyze the effect of the level of amputation and various prosthetic devices on the muscle activation of the sound limb in people with unilateral transfemoral and transtibial amputation. We calculated the global coactivation of 12 muscles using the time-varying multimuscle coactivation function method in 37 subjects with unilateral transfemoral amputation (10, 16, and 11 with mechanical, electronic, and bionic prostheses, respectively), 11 subjects with transtibial amputation, and 22 healthy subjects representing the control group. The results highlighted that people with amputation had a global coactivation temporal profile similar to that of healthy subjects. However, amputation increased the level of the simultaneous activation of many muscles during the loading response and push-off phases of the gait cycle and decreased it in the midstance and swing subphases. This increased coactivation probably plays a role in prosthetic gait asymmetry and energy consumption. Furthermore, people with amputation and wearing electronic prosthesis showed lower global coactivation when compared with people wearing mechanical and bionic prostheses. These findings suggest that the global lower limb coactivation behavior can be a useful tool to analyze the motor control strategies adopted and the ability to adapt to the prosthetic device.

The central nervous system (CNS) controls movements and regulates joint stiffness with muscle co-activation, but until now, few studies have examined muscle pairs during running. This study aims to investigate differences in lower limb muscle coactivation during gait at different speeds, from walking to running. Nineteen healthy runners walked and ran at speeds ranging from 0.8 km/h to 9.3 km/h. Twelve lower limb muscles' co-activation was calculated using the time-varying multi-muscle co-activation function (TMCf) with global, flexor–extension, and rostro–caudal approaches. Spatiotemporal and kinematic parameters were also measured. We found that TMCf, spatiotemporal, and kinematic parameters were significantly affected by gait speed for all approaches. Significant differences were observed in the main parameters of each co-activation approach and in the spatiotemporal and kinematic parameters at the transition between walking and running. In particular, significant differences were observed in the global co-activation (CIglob, main effect F(1,17) = 641.04, p < 0.001; at the transition p < 0.001), the stride length (main effect F(1,17) = 253.03, p < 0.001; at the transition p < 0.001), the stride frequency (main effect F(1,17) = 714.22, p < 0.001; at the transition p < 0.001) and the Center of Mass displacement in the vertical (CoMy, main effect F(1,17) = 426.2, p < 0.001; at the transition p < 0.001) and medial–lateral (CoMz, main effect F(1,17) = 120.29 p < 0.001; at the transition p < 0.001) directions. Regarding the correlation analysis, the CoMy was positively correlated with a higher CIglob (r = 0.88, p < 0.001) and negatively correlated with Full Width at Half Maximum (FWHMglob, r = −0.83, p < 0.001), whereas the CoMz was positively correlated with the global Center of Activity (CoAglob, r = 0.97, p < 0.001). Positive and negative strong correlations were found between global co-activation parameters and center of mass displacements, as well as some spatiotemporal parameters, regardless of gait speed. Our findings suggest that walking and running have different co-activation patterns and kinematic characteristics, with the whole-limb stiffness exerted more synchronously and stably during running. The co-activation indexes and kinematic parameters could be the result of global co-activation, which is a sensory-control integration process used by the CNS to deal with more demanding and potentially unstable tasks like running. [ABSTRACT FROM AUTHOR]

Biomechanical overload is considered a significant occupational risk in manufacturing and a potential cause of musculoskeletal disorders. This research aims to introduce new methodologies for the quantitative risk evaluation of biomechanical risk by combining surface electromyography with a motion acquisition system based on inertial measurement units. Due to the lack of experimental data in the literature acquired in a real industrial environment during the working shift, an on-the-field study regarding an automotive assembly line workstation has been carried out in collaboration with Fiat Chrysler Automobiles Italy S.p.A. Data related to the trunk flexion forward and the erector spinae muscle activity have been acquired for several consecutive working cycles by considering three different workers. Data analyses indicated kinematic and muscular activity patterns consistent with those expected and that the proposed wearable technologies can be integrated and used simultaneously during work activities. Furthermore, the results demonstrated data repeatability, strengthening the feasibility and usefulness of the combined use of kinematic and electromyography technologies to assess biomechanical overload in production lines. This study could lay the bases for the future definition of a method for assessing biomechanical overload due to awkward postures. [ABSTRACT FROM AUTHOR]

Low-back disorders (LBDs) are the most common and costly musculoskeletal problem. Muscle co-activation, a mechanism that stabilises the spine, is adopted by the central nervous system to provide added protection and avoid LBDs. However, during high-risk lifting tasks, the compressive load on the spine grows owing to increased co-activation. The aim of this study was to develop a method for the sample-by-sample monitoring of the co-activation of more than two muscles, and to compare this method with agonist–antagonist methods. We propose a time-varying multi-muscle co-activation function that considers electromyographic (EMG) signals as input. EMG data of 10 healthy subjects were recorded while they manually lifted loads at three progressively heavier conditions. The repeated measures ANOVA revealed a significant effect of lifting condition on our co-activation index. Heavier conditions resulted in higher muscle co-activation values. Significant correlations were found between the time-varying multi-muscle co-activation index and other agonist–antagonist methods. Practitioner Summary:We have developed a method to quantify muscle co-activation during the execution of a lifting task. To do this we used surface electromyography. Our algorithm provides a measure of time-varying co-activation between more than two muscles. [ABSTRACT FROM AUTHOR]

Low back pain (LBP) is a leading cause of disability in the workplace, often caused by manually lifting of heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk of lifting activities. This study aims to verify that, during the execution of fatiguing frequency-dependent lifting, high-density surface electromyography (HDsEMG) allows the discrimination of healthy controls (HC) versus people with LBP and biomechanical risk levels. Fifteen HC and eight people with LBP performed three lifting tasks with a progressively increasing lifting index, each lasting 15 min. Erector spinae (ES) activity was recorded using HDsEMG and amplitude parameters were calculated to characterize the spatial distribution of muscle activity. LBP group showed a less ES activity than HC (lower root mean square across the grid and of the activation region) and an involvement of the same muscular area across the task (lower coefficient of variation of the center of gravity of muscle activity). The results indicate the usefulness of HDsEMG parameters to classify risk levels for both HC and LBP groups and to determine differences between them. The findings suggest that the use of HDsEMG could expand the capabilities of existing instrumental-based tools for biomechanical risk classification during lifting activities. [ABSTRACT FROM AUTHOR]

Background The aim of this study was to investigate the lower limb muscle coactivation and its relationship with muscles spasticity, gait performance, and metabolic cost in patients with hereditary spastic paraparesis. Methods Kinematic, kinetic, electromyographic and energetic parameters of 23 patients and 23 controls were evaluated by computerized gait analysis system. We computed ankle and knee antagonist muscle coactivation indexes throughout the gait cycle and during the subphases of gait. Energy consumption and energy recovery were measured as well. In addition to the correlation analysis between coactivation indexes and clinical variables, correlations between coactivation indexes and time–distance, kinematic, kinetic, and energetic parameters were estimated. Findings Increased coactivity indexes of both knee and ankle muscles throughout the gait cycle and during the subphases of gait were observed in patients compared with controls. Energetic parameters were significantly higher in patients than in controls. Both knee and ankle muscle coactivation indexes were positively correlated with knee and ankle spasticity (Ashworth score), respectively. Knee and ankle muscle coactivation indexes were both positively correlated with energy consumption and both negatively correlated with energy recovery. Interpretation Positive correlations between the Ashworth score and lower limb muscle coactivation suggest that abnormal lower limb muscle coactivation in patients with hereditary spastic paraparesis reflects a primary deficit linked to lower limb spasticity. Furthermore, these abnormalities influence the energetic mechanisms during walking. Identifying excessive muscle coactivation may be helpful in individuating the rehabilitative treatments and designing specific orthosis to restrain spasticity. [ABSTRACT FROM AUTHOR]

Workers often develop low back pain due to manually lifting heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk in lifting activities. This study aims to verify the hypothesis that high-density surface electromyography (HDsEMG) allows an optimized discrimination of risk levels associated with different fatiguing lifting conditions compared to traditional bipolar sEMG. 15 participants performed three lifting tasks with a progressively increasing lifting index (LI) each lasting 15 min. Erector spinae (ES) activity was recorded using both bipolar and HDsEMG systems. The amplitude of both bipolar and HDsEMG can significantly discriminate each pair of LI. HDsEMG data could discriminate across the different LIs starting from the fourth minute of the task while bipolar sEMG could only do so towards the end. The higher discriminative power of HDsEMG data across the lifting tasks makes such methodology a valuable tool to be used to monitor fatigue while lifting and could extend the possibilities offered by currently available instrumental-based tools. [ABSTRACT FROM AUTHOR]