Human myoelectric spatial patterns differ among lower limb muscles and locomotion speeds.
ABSTRACT: The spatial distribution of myoelectric activity within lower limb muscles is often nonuniform and can change during different stationary tasks. Recent studies using high-density electromyography (EMG) have suggested that spatial muscle activity may also differ among muscles during locomotion, but contrasting electrode array sizes and experimental designs have limited cross-study comparisons. Here, we sought to determine if spatial EMG patterns differ among lower limb muscles and locomotion speeds. We recorded high-density EMG from the vastus medialis, tibialis anterior, biceps femoris, medial gastrocnemius, and lateral gastrocnemius muscles of 11 healthy subjects while they walked (1.2 and 1.6 m/s) and ran (2.0, 3.0, 4.0, and 5.0 m/s) on a treadmill. To overcome the detrimental effects of cable, electrode, and soft tissue movements on high-density EMG signal quality during locomotion, we applied multivariate signal cleaning methods. From these data, we computed the spatial entropy and center of gravity from the total myoelectric activity within each recording array during the stance or swing phases of the gait cycle. We found heterogeneous spatial EMG patterns evidenced by contrasting spatial entropy among lower limb muscles. As locomotion speed increased, mean entropy values decreased in four of the five recorded muscles, indicating that EMG signal amplitudes were more spatially heterogeneous, or localized, at faster speeds. The EMG center of gravity location also shifted in multiple muscles as locomotion speed increased. Contrasting myoelectric spatial distributions among muscles likely reflect differences in muscle architecture, but increasingly localized activity and spatial shifts in the center of gravity location at faster locomotion speeds could be influenced by preferential recruitment of faster motor units under greater loads.
Project description:Gravity plays a crucial role in shaping patterned locomotor output to maintain dynamic stability during locomotion. The present study aimed to clarify the gravity-dependent regulation of modules that organize multiple muscle activities during walking in humans. Participants walked on a treadmill at seven speeds (1-6 km h<sup>-1</sup> and a subject- and gravity-specific speed determined by the Froude number (Fr) corresponding to 0.25) while their body weight was partially supported by a lift to simulate walking with five levels of gravity conditions from 0.07 to 1 g. Modules, i.e., muscle-weighting vectors (spatial modules) and phase-dependent activation coefficients (temporal modules), were extracted from 12 lower-limb electromyographic (EMG) activities in each gravity (Fr ~ 0.25) using nonnegative matrix factorization. Additionally, a tensor decomposition model was fit to the EMG data to quantify variables depending on the gravity conditions and walking speed with prescribed spatial and temporal modules. The results demonstrated that muscle activity could be explained by four modules from 1 to 0.16 g and three modules at 0.07 g, and the modules were shared for both spatial and temporal components among the gravity conditions. The task-dependent variables of the modules acting on the supporting phase linearly decreased with decreasing gravity, whereas that of the module contributing to activation prior to foot contact showed nonlinear U-shaped modulation. Moreover, the profiles of the gravity-dependent modulation changed as a function of walking speed. In conclusion, reduced gravity walking was achieved by regulating the contribution of prescribed spatial and temporal coordination in muscle activities.
Project description:Advanced motorized prosthetic devices are currently controlled by EMG signals generated by residual muscles and recorded by surface electrodes on the skin. These surface recordings are often inconsistent and unreliable, leading to high prosthetic abandonment rates for individuals with upper limb amputation. Surface electrodes are limited because of poor skin contact, socket rotation, residual limb sweating, and their ability to only record signals from superficial muscles, whose function frequently does not relate to the intended prosthetic function. More sophisticated prosthetic devices require a stable and reliable interface between the user and robotic hand to improve upper limb prosthetic function.Implantable Myoelectric Sensors (IMES(®)) are small electrodes intended to detect and wirelessly transmit EMG signals to an electromechanical prosthetic hand via an electro-magnetic coil built into the prosthetic socket. This system is designed to simultaneously capture EMG signals from multiple residual limb muscles, allowing the natural control of multiple degrees of freedom simultaneously.We report the status of the first FDA-approved clinical trial of the IMES(®) System. This study is currently in progress, limiting reporting to only preliminary results.Our first subject has reported the ability to accomplish a greater variety and complexity of tasks in his everyday life compared to what could be achieved with his previous myoelectric prosthesis.The interim results of this study indicate the feasibility of utilizing IMES(®) technology to reliably sense and wirelessly transmit EMG signals from residual muscles to intuitively control a three degree-of-freedom prosthetic arm.
Project description:This paper presents a dataset of high-density surface EMG signals (HD-sEMG) designed to study patterns of sEMG spatial distribution over upper limb muscles during voluntary isometric contractions. Twelve healthy subjects performed four different isometric tasks at different effort levels associated with movements of the forearm. Three 2-D electrode arrays were used for recording the myoelectric activity from five upper limb muscles: biceps brachii, triceps brachii, anconeus, brachioradialis, and pronator teres. Technical validation comprised a signals quality assessment from outlier detection algorithms based on supervised and non-supervised classification methods. About 6% of the total number of signals were identified as "bad" channels demonstrating the high quality of the recordings. In addition, spatial and intensity features of HD-sEMG maps for identification of effort type and level, have been formulated in the framework of this database, demonstrating better performance than the traditional time-domain features. The presented database can be used for pattern recognition and MUAP identification among other uses.
Project description:<h4>Background</h4>Despite a large increase in robotic exoskeleton research, there are few studies that have examined human performance with different control strategies on the same exoskeleton device. Direct comparison studies are needed to determine how users respond to different types of control. The purpose of this study was to compare user performance using a robotic hip exoskeleton with two different controllers: a controller that targeted a biological hip torque profile and a proportional myoelectric controller.<h4>Methods</h4>We tested both control approaches on 10 able-bodied subjects using a pneumatically powered hip exoskeleton. The state machine controller targeted a biological hip torque profile. The myoelectric controller used electromyography (EMG) of lower limb muscles to produce a proportional control signal for the hip exoskeleton. Each subject performed two 30-min exoskeleton walking trials (1.0 m/s) using each controller and a 10-min trial with the exoskeleton unpowered. During each trial, we measured subjects' metabolic cost of walking, lower limb EMG profiles, and joint kinematics and kinetics (torques and powers) using a force treadmill and motion capture.<h4>Results</h4>Compared to unassisted walking in the exoskeleton, myoelectric control significantly reduced metabolic cost by 13% (<i>p</i> = 0.005) and biological hip torque control reduced metabolic cost by 7% (<i>p</i> = 0.261). Subjects reduced muscle activity relative to the unpowered condition for a greater number of lower limb muscles using myoelectric control compared to the biological hip torque control. More subjects subjectively preferred the myoelectric controller to the biological hip torque control.<h4>Conclusion</h4>Myoelectric control had more advantages (metabolic cost and muscle activity reduction) compared to a controller that targeted a biological torque profile for walking with a robotic hip exoskeleton. However, these results were obtained with a single exoskeleton device with specific control configurations while level walking at a single speed. Further testing on different exoskeleton hardware and with more varied experimental protocols, such as testing over multiple types of terrain, is needed to fully elucidate the potential benefits of myoelectric control for exoskeleton technology.
Project description:Walking is characterized by repetitive limb movements associated with highly structured patterns of muscle activity. The causal relationships between the muscle activities and hindlimb segments of walking are difficult to decipher. This study investigated these particular relationships and clarified whether they are correlated with speed to further understand the neuromuscular control pattern. Four adult female rhesus monkeys (Macaca mulatta) were selected to record gait parameters while walking on a bipedal treadmill at speeds of 0.2, 0.8, 1.4, and 2.0 km/h. We recorded 3 ipsilateral hindlimb muscles by surface recording. In this study, we calculated the correlations between electromyography (EMG) and kinematic parameters (24 EMG*17 kinematic parameters). Of the 408 calculated coefficients, 71.6% showed significant linear correlations. Significant linear correlations were found between muscle activity, such as burst amplitudes and the integral of muscle activity, and the corresponding kinematic parameters of each joint. Most of these relationships were speed independent (91.7% of all variables). Through correlation analysis, this study demonstrated a causal association between kinematic and EMG patterns of rhesus monkey locomotion. Individuals have particular musculoskeletal control patterns, and most of the relationships between hindlimb segments and muscles are speed independent. The current findings may enhance our understanding of neuromusculoskeletal control strategies.
Project description:This paper reports the kinematic, kinetic and electromyographic (EMG) dataset of human locomotion during level walking at different velocities, toe- and heel-walking, stairs ascending and descending. A sample of 50 healthy subjects, with an age between 6 and 72 years, is included. For each task, both raw data and computed variables are reported including: the 3D coordinates of external markers, the joint angles of lower limb in the sagittal, transversal and horizontal anatomical planes, the ground reaction forces and torques, the center of pressure, the lower limb joint mechanical moments and power, the displacement of the whole body center of mass, and the surface EMG signals of the main lower limb muscles. The data reported in the present study, acquired from subjects with different ages, represents a valuable dataset useful for future studies on locomotor function in humans, particularly as normative reference to analyze pathological gait, to test the performance of simulation models of bipedal locomotion, and to develop control algorithms for bipedal robots or active lower limb exoskeletons for rehabilitation.
Project description:Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity ([Formula: see text]) and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity.
Project description:Turtles use their limbs during both aquatic and terrestrial locomotion, but water and land impose dramatically different physical requirements. How must musculoskeletal function be adjusted to produce locomotion through such physically disparate habitats? We addressed this question by quantifying forelimb kinematics and muscle activity during aquatic and terrestrial locomotion in a generalized freshwater turtle, the red-eared slider (Trachemys scripta), using digital high-speed video and electromyography (EMG). Comparisons of our forelimb data to previously collected data from the slider hindlimb allow us to test whether limb muscles with similar functional roles show qualitatively similar modulations of activity across habitats. The different functional demands of water and air lead to a prediction that muscle activity for limb protractors (e.g. latissimus dorsi and deltoid for the forelimb) should be greater during swimming than during walking, and activity in retractors (e.g. coracobrachialis and pectoralis for the forelimb) should be greater during walking than during swimming. Differences between aquatic and terrestrial forelimb movements are reflected in temporal modulation of muscle activity bursts between environments, and in some cases the number of EMG bursts as well. Although patterns of modulation between water and land are similar between the fore- and hindlimb in T. scripta for propulsive phase muscles (retractors), we did not find support for the predicted pattern of intensity modulation, suggesting that the functional demands of the locomotor medium alone do not dictate differences in intensity of muscle activity across habitats.
Project description:The degree of automaticity of locomotion in primates compared with other mammals remains unclear. Here, we examine the possibility for activation of the spinal locomotor circuitry in noninjured humans by spinal electromagnetic stimulation (SEMS). SEMS (3 Hz and 1.3-1.82 tesla) at the T11-T12 vertebrae induced involuntary bilateral locomotor-like movements in the legs of individuals placed in a gravity-neutral position. The formation of locomotor-like activity during SEMS started with a latency of 0.68 +/- 0.1 s after delivering the first stimulus, unlike continuous vibration of muscles, which requires several seconds. The first EMG burst in response to SEMS was observed most often in a proximal flexor muscle. We speculate that SEMS directly activates the circuitry intrinsic to the spinal cord, as suggested by the immediate response and the electrophysiological observations demonstrating an absence of strictly time-linked responses within the EMG burst associated with individual stimuli during SEMS. SEMS in the presence of vibration of the leg muscles was more effective in facilitating locomotor-like activity than SEMS alone. The present results suggest that SEMS could be an effective noninvasive clinical tool to determine the potential of an individual to recover locomotion after a spinal cord injury, as well as being an effective rehabilitation tool itself.
Project description:Without high impact forces, it is not clear how humans can utilize tendon elasticity during low-impact activities. The purpose of the present study was to examine the muscle-tendon behavior together with the electromyographic (EMG) activities of the vastus lateralis (VL) muscle during the human dolphin-kicking. In a swimming pool, each subject (n = 11) swam the 25 m dolphin-kicking at two different speeds (NORMAL and FAST). Surface EMGs were recorded from the VL and biceps femoris (BF) muscles. Simultaneous recordings of the knee joint angle by electro-goniometer and of the VL fascicle length by ultrasonography were used to calculate the muscle-tendon unit and tendinous length of VL (LMTU and LTT, respectively). In the dolphin-kicking, the stretching and shortening amplitudes of VL LMTU did not differ significantly between the two kicking speed conditions. However, both stretching and shortening amplitudes of the VL fascicle length were lower at FAST than at NORMAL speed whereas the opposite was found for the VL LTT values. At FAST, the contribution of the VL tendinous length to the entire VLMTU length changes increased. The EMG analysis revealed at FAST higher agonist VL activation from the late up-beat (MTU stretching) to the early down-beat phases as well as increased muscle co-activation of VL and BF muscles from the late down-beat to early up-beat phases of dolphin-kicking. These results suggest that at increasing kicking speeds, the VL fascicles and tendinous tissues during aquatic movements can utilize tendon elasticity in a similar way than in terrestrial forms of locomotion. However, these activation profiles of VL and BF muscles may differ from their activation pattern in terrestrial locomotion.