Time-frequency analysis of surface myoelectric signals duringathletic movement

Considers muscle activation and fatigue during propulsion of a racing wheelchair. The authors discuss a single case study on the modality of muscle activation during the propulsion of a racing wheelchair. To investigate muscle coordination, muscle fatigue, and the strategies that the subject exploits to counteract the effects of muscle fatigue and keep a high level of performance, the authors first studied the activation intervals of seven trunk and upper limb muscles and then studied the evolution in time of their spectral content by means of two different approaches, according to the statistical properties of their myoelectric signals. Angle, angular velocity, and angular acceleration of the elbow joint have also been considered. This combined approach allowed the authors to obtain different results important to gaining a deeper insight in the differences among the observed muscles in this specific exercise     

EMG-based measures of fatigue during a repetitive squat exercise

We have demonstrated a technique to calculate the EMG instantaneous median frequency to assess muscle fatigue during a dynamic exercise commonly prescribed in patients with ACL deficiency. We used Cohen-Posch time-frequency representations to improve upon the variability of the instantaneous median frequency estimates derived using Cohen Class transformations. The technique was applied to surface EMG data recorded from the quadriceps and hamstring muscles of a control subject and a patient with ACL deficiency during a repetitive squat exercise. Instantaneous median frequency values were derived for the knee-extension phases of the exercise. Ensemble average and standard deviation of the instantaneous median frequency were computed for the portion of the cycle associated with the lowest variability of the mechanics     

Unilateral and bilateral subthalamic nucleus stimulation in Parkinson's disease: effects on EMG signals of lower limb muscles during walking.

The effects of subthalamic nucleus (STN) stimulation on the spatio-temporal organization of locomotor commands directed to lower limb muscles were studied in subjects with idiopathic Parkinson's Disease (PD) by recording the EMG activity produced during steady-state walking in representative thigh (rectus femoris, RF, and semimembranosus, SM) and leg (gatrocnemius medialis, GAM, and tibialis anterior, TA) muscles, under four experimental conditions: basal stimulation OFF, unilateral (right and left) stimulation ON, and bilateral stimulation ON. Locomotor profiles of all of the muscles tested were found to be substantially affected by STN stimulation, either in terms of restoration/enhancement of the main activity bursts or normalization of recruitment timing thereof. Responses showed relatively higher statistical significance in the distal groups (GAM and TA) and, within them, for the EMG components called into action over the ground-contact (ankle dorsiflexors) and midstance (ankle plantarflexors) phases of the stride cycle. In line with data obtained from clinical rating, unilateral stimulation produced less consistent EMG changes compared with bilateral stimulation. However, at variance with clinical effects, which prevailed on the side of the body contralateral to stimulation, EMG responses to unilateral stimulation were usually symmetrical. Results indicate that the impact of STN stimulation on locomotor activation of lower limb muscles in PD is characterized by: 1) substantial effects exhibiting differential topographical (distal versus proximal) and stride-phase (stance versus swing) consistency and 2) absence of the lateralized actions typically observed for the clinical signs of the disease. Interaction with the activity of functionally different executive systems might account for the observed pattern of responsiveness.     

Functional restoration of elbow extension after spinal-cord injury using a neural network-based synergistic FES controller.

Individuals with a C5/C6 spinal-cord injury (SCI) have paralyzed elbow extensors, yet retain weak to strong voluntary control of elbow flexion and some shoulder movements. They lack elbow extension, which is critical during activities of daily living. This research focuses on the functional evaluation of a developed synergistic controller employing remaining voluntary elbow flexor and shoulder electromyography (EMG) to control elbow extension with functional electrical stimulation (FES). Remaining voluntarily controlled upper extremity muscles were used to train an artificial neural network (ANN) to control stimulation of the paralyzed triceps. Surface EMG was collected from SCI subjects while they produced isometric endpoint force vectors of varying magnitude and direction using triceps stimulation levels predicted by a biomechanical model. ANNs were trained with the collected EMG and stimulation levels. We hypothesized that once trained and implemented in real-time, the synergistic controller would provide several functional benefits. We anticipated the synergistic controller would provide a larger range of endpoint force vectors, the ability to grade and maintain forces, the ability to complete a functional overhead reach task, and use less overall stimulation than a constant stimulation scheme.     

Study of the control strategy of the quadriceps muscles in anterior knee pain.

Anterior knee pain (AKP) is a common pathological condition, particularly among young people and athletes, associated to an abnormal motion of the patella during the bending of the knee and possibly dependent on a muscular or structural imbalance. A lack of synergy in the quadriceps muscles results in a dynamic misalignment of the patella, which in turn produces pain. AKP rehabilitative therapy consists of conservative treatment whose main objective is to strengthen the Vastus Medialis. The aim of this article is to study the quadriceps muscle control strategy in AKP patients during an isokinetic exercise. Analysis of the muscle activation strategy is important for an objective measurement of the knee functionality in that it helps to diagnose and monitor the rehabilitative treatment. Surface electromyography (EMG) from the three superficial muscles of the femoral quadriceps during a concentric isokinetic exercise has been analyzed along with the signals of knee joint position and torque. A group of 12 AKP patients has been compared with a group of 30 normal subjects. Analysis of the grand ensemble average of the EMG linear envelopes in AKP patients reveals significant modifications in Vastus Medialis activity compared to the other quadriceps muscles. In order to study the synergy of the muscles, temporal identifiers have been associated to the EMG linear envelopes. To this end, EMG linear envelope decomposition in Gaussian pulses turned out to be effective and the results highlight an appreciable delay in the activation of the Vastus Medialis in AKP patients. This muscular unbalance can explain the abnormal motion of the patella.     

Strength and coordination in the paretic leg of individuals following acute stroke.

The goal of this study was to determine whether acute stroke survivors demonstrate abnormal synergy patterns in their affected lower extremity. During maximum isometric contractions with subjects in a standing position, joint torques generated simultaneously at the knee and hip were measured, along with associated muscle activation patterns in eight lower limb muscles. Ten acute stroke survivors and nine age-match controls participated in the study. For all joints tested, stroke subjects demonstrated significantly less maximum isometric torque than age-matched control subjects. However, the synergistic torques generated in directions different than the direction that was being maximized were not significantly different between the two groups. According to electromyography (EMG) data, it was found that stroke subjects activated antagonistic muscle groups significantly higher than the control group subjects, suggesting that deficits in joint torque may be at least partially attributable to co-contraction of antagonistic muscles. Our findings suggest that a primary contributor to lower limb motor impairment in acute hemiparetic stroke is poor volitional torque generating capacity, which is at least partially attributable to co-contraction of antagonistic muscles. Furthermore, while we did not observe abnormal torque synergy patterns commonly found in the upper limbs, muscle activation patterns differed between groups for many of the directions tested indicating changes in the motor control strategies of acute stroke survivors.     

A simple device to monitor flexion and lateral bending of the lumbar spine.

Monitoring compliance with exercise and motivating patients with lower back pain to perform prescribed exercise regimens are considerable tasks. The objective of this study was to develop and test a low-cost device that can be used by a patient at home to both record and provide real-time biofeedback of lumbar position in the midsagittal and frontal planes during exercises. Our device utilizes strain gages on a thin stainless steel beam to measure lumbar flexion-extension and an optical mouse sensor attached to the end of the blade to measure lateral bending. In comparison tests with a standard electrogoniometer, our device was shown to be accurate within 3 degrees in both the sagittal and frontal planes in healthy subjects. Furthermore, users were capable of reapplying the device themselves and obtaining measurements that were repeatable within 4 degrees in both planes. The capability of this simple device to accurately measure lumbar spine position in a nonlaboratory setting makes it well suited as a tool for providing feedback on exercise performance to both patients and clinicians.     

基于表面肌电信号及肌肉疲劳的上肢肌力预测

为解决目前肌肉力测量时用肢体末端力表示实际肌肉力大小,以及未将肌肉疲劳程度考虑在内的问题,本文提出了一种基于表面肌电信号和肌肉疲劳的上肢肌肉力预测方法。利用AnyBody软件建立上肢肌肉骨骼模型,并将上肢末端力经过仿真得到单块肌肉的肌力大小;采用肌肉等长收缩的时间来表征肌肉疲劳程度。10名健康男性受试者进行上肢等长收缩实验,提取实验过程中肱二头肌肌电信号的积分肌电值、均方根、中值频率、平均功率频率、最大小波系数及其对应频率六个特征值;将肌肉力与特征值、肌肉疲劳程度进行分析后发现三者之间高度相关。采用麻雀搜索算法优化BP神经网络的权值和阈值,构造并训练上肢肌力预测模型。经测试集检验结果表明,该方法的误差小于12%,可以对肌力进行较为准确的预测。     

Influence of pedaling rate on muscle mechanical energy in low power recumbent pedaling using forward dynamic simulations.

An understanding of the muscle power contributions to the crank and limb segments in recumbent pedaling would be useful in the development of rehabilitative pedaling exercises. The objectives of this work were to 1) quantify the power contributions of the muscles to driving the crank and limb segments using a forward dynamic simulation of low-power pedaling in the recumbent position, and 2) determine whether there were differences in the muscle power contributions at three different pedaling rates. A forward dynamic model was used to determine the individual muscle excitation amplitude and timing to drive simulations that best replicated experimental kinematics and kinetics of recumbent pedaling. The segment kinematics, pedal reaction forces, and electromyograms (EMG) of 10 muscles of the right leg were recorded from 16 subjects as they pedaled a recumbent ergometer at 40, 50, and 60 rpm and a constant 50 W workrate. Intersegmental joint moments were computed using inverse dynamics and the muscle excitation onset and offset timing were determined from the EMG data. All quantities were averaged across ten cycles for each subject and averaged across subjects. The model-generated kinematic and kinetic quantities tracked almost always within 1 standard deviation (SD) of the experimental data for all three pedaling rates. The uniarticular hip and knee extensors generated 65% of the total mechanical work in recumbent pedaling. The triceps surae muscles transferred power from the limb segments to the crank and the bi-articular muscles that crossed the hip and knee delivered power to the crank during the leg transitions between flexion and extension. The functions of the individual muscles did not change with pedaling rate, but the mechanical energy generated by the knee extensors and hip flexors decreased as pedaling rate increased. By varying the pedaling rate, it is possible to manipulate the individual muscle power contributions to the crank and limb segments in recumbent pedaling and thereby design rehabilitative pedaling exercises to meet specific objectives.     

Electromyography

The use of electromyography (EMG) to determine the cause of lower back pain is examined. The source and properties of the EMG signal and its analysis are discussed. The fatigue properties of back muscles and their role in back pain are considered. A typical back analysis system is described, and some study results are presented     

The use of splines to calculate jerk for a lifting task involving chronic lower back pain patients

Motion differences in a repetitive lifting task have been described previously using differences in the timing of body angle changes during the lift. These timing changes relied on small differences of motion and are difficult to measure. The purpose of this study was to evaluate shoulder jerk (rate of change of acceleration) in a repetitive lifting task as an alternative parameter to detect differences of motion between controls and chronic lower back pain (CLBP) patients and to measure the impact of a rehabilitation program on jerk. The jerk calculation was a noisy measure, since jerk is the third derivative of position; consequently a simulation was performed to evaluate smoothing methods. Woltring's generalized cross-validation spline produced the best estimates of the third derivative and was fit to subject data. The root mean square (rms) amplitude of jerk was used for comparison. Significant group differences were found. CLBP patients performed lifts with lower jerk values than controls and, as the task progressed, both groups increased jerk. After completion of a rehabilitation program, CLBP patients performed lifts with greater rms jerk. In general, patients performed lifts with lower jerk values than controls, suggesting that pain impacts lifting style.     

EMG-based prediction of shoulder and elbow kinematics in able-bodied and spinal cord injured individuals.

We have evaluated the ability of a time-delayed artificial neural network (TDANN) to predict shoulder and elbow motions using only electromyographic (EMG) signals recorded from six shoulder and elbow muscles as inputs, both in able-bodied subjects and in subjects with tetraplegia arising from C5 spinal cord injury. For able-bodied subjects, all four joint angles (elbow flexion-extension and shoulder horizontal flexion-extension, elevation-depression, and internal-external rotation) were predicted with average root-mean-square (rms) errors of less than 20 degrees during movements of widely different complexities performed at different speeds and with different hand loads. The corresponding angular velocities and angular accelerations were predicted with even lower relative errors. For individuals with C5 tetraplegia, the absolute rms errors of the joint angles, velocities, and accelerations were actually smaller than for able-bodied subjects, but the relative errors were similar when the smaller movement ranges of the C5 subjects were taken into account. These results indicate that the EMG signals from shoulder and elbow muscles contain a significant amount of information about arm moVement kinematics that could be exploited to develop advanced control systems for augmenting or restoring shoulder and elbow movements to individuals with tetraplegia using functional neuromuscular stimulation of paralyzed muscles.     

Evaluation of Head Orientation and Neck Muscle EMG Signals as Command Inputs to a Human–Computer Interface for Individuals With High Tetraplegia

We investigated the performance of three user interfaces for restoration of cursor control in individuals with tetraplegia: head orientation, electromyography (EMG) from face and neck muscles, and a standard computer mouse (for comparison). Subjects engaged in a 2-D, center-out, Fitts' Law style task and performance was evaluated using several measures. Overall, head orientation commanded motion resembled mouse commanded cursor motion (smooth, accurate movements to all targets), although with somewhat lower performance. EMG commanded movements exhibited a higher average speed, but other performance measures were lower, particularly for diagonal targets. Compared to head orientation, EMG as a cursor command source was less accurate, was more affected by target direction and was more prone to overshoot the target. In particular, EMG commands for diagonal targets were more sequential, moving first in one direction and then the other rather than moving simultaneous in the two directions. While the relative performance of each user interface differs, each has specific advantages depending on the application.      

Preliminary evaluation of a controlled-brake orthosis for FES-aided gait

A hybrid functional-electrical stimulation (FES) gait system that incorporates a computer-controlled orthosis system has been developed to address the problems of rapid muscle fatigue and poor movement control that are characteristic of FES-aided gait. The orthosis is a long-leg brace that contains controllable friction brakes at both hip and knee joints. The system achieves desirable limb trajectories by utilizing the stimulated muscles as a source of unregulated power and regulating the power at each joint by computer control of the friction brakes. Muscle fatigue is reduced by locking the controllable brakes to provide the isometric joint torques necessary during stance. The hybrid gait system was evaluated and compared to conventional four channel FES-aided gait using four subjects with paraplegia. The results demonstrated significant reduction in muscle fatigue and improvement in trajectory control when using the orthosis combined with FES compared to using FES alone. Results for distance and speed improvements varied across subjects. Considerable work remains in the design of the hardware before the system is feasible for use outside the laboratory.     

Multidimensional EMG-based assessment of walking dynamics

The electromyogram (EMG) provides a measure of a muscle's involvement in the execution of a motor task. Successful completion of an activity, such as walking, depends on the efficient motor control of a group of muscles. In this paper, we present a method to quantify the intricate phasing and activation levels of a group of muscles during gait. At the core of our method is a multidimensional representation of the EMG activity observed during a single stride. This representation is referred to as a "trajectory." A hierarchical clustering procedure is used to identify representative classes of muscle activity patterns. The relative frequencies with which these motor patterns occur during a session (i.e., a series of consecutive strides) are expressed as histograms. Changes in walking strategy will be reflected as changes in the relative frequency with which specific gait patterns occur. This method was evaluated using EMG data obtained during walking on a level and a moderately-inclined treadmill. It was found that the histogram changes due to artificially altered gait are significantly larger than the changes due to normal day-to-day variability.     

Clinician's view: dynamic EMG

The research into a correlation between joint biomechanics and the action of muscles that act on the limb segment involved during movement has become very important in recent years. However, while the techniques for elaborating the EMG signal and its relationship with the dynamics of movement are described in detail in the literature, from a clinical point of view publications on how these techniques are used for clinical gait analysis applications are scarce. The purpose of dynamic EMG in clinical gait analysis is essentially to define the muscular activity that controls joint movement during gait, as shown by studies carried out on children with cerebral palsy, in which the abnormal pattern of muscle activation is used, for example, as an indication for surgical tendon transfer or lengthening     

EMG and metabolite-based prediction of force in paralyzed quadriceps muscle under interrupted stimulation.

A major issue associated with functional electrical stimulation (FES) of a paralyzed limb is the decay with time of the muscle force as a result of fatigue. A possible means to reduce fatigue during FES is by using interrupted stimulation, in which fatigue and recovery occur in sequence. In this study, we present a model which enables us to evaluate the temporal force generation capacity within the electrically activated muscle during first stimulation fatigue, i.e., when the muscle is activated from unfatigued initial conditions, and during postrest stimulation, i.e., after different given rest durations. The force history of the muscle is determined by the activation as derived from actually measured electromyogram (EMG) data, and by the metabolic fatigue function expressing the temporal changes of muscle metabolites, from existing data acquired by in vivo 31P MR spectroscopy in terms of the inorganic phosphorus variables, Pi or H2PO4-, and by the intracellular pH. The model was solved for supra-maximal stimulation in isometric contractions separated by rest periods, and compared to experimentally obtained measurements. EMG data were fundamental for prediction of the ascending force during its posttetanic response. On the other hand, prediction of the decaying phase of the force was possible only by means of the metabolite-based fatigue function. The prediction capability of the model was assessed by means of the error between predicted and measured force profiles. The predicted force obtained from the model in first stimulation fatigue fits well with the experimental one. In postrest stimulation fatigue, the different metabolites provided different prediction capabilities of the force, depending on the duration of the rest period. Following rest duration of 1 min, Pi provided the best prediction of force; H2PO4- extended the prediction capacity of the model to up to 6 min and pH provided a reliable prediction for rest durations longer than 12 min. The results presented shed light on the roles of EMG and of metabolites in prediction of the force history of a paralyzed muscle under conditions where fatigue and recovery occur in sequence.     

Spectral compression of the electromyographic signal due to decreasing muscle fiber conduction velocity.

Spectral compression of the electromyographic (EMG) signal, due largely to decreasing muscle fiber conduction velocity, is commonly used as an indication of muscle fatigue. Current methods of estimating conduction velocity using characteristic frequencies such as the median frequency of the power spectrum, are based on an assumption of uniform spectral compression. To examine changes in the EMG frequency spectrum during fatigue, muscle fiber conduction velocity was measured during sustained, isometric contractions of the biceps brachii. Compression of the EMG power and amplitude spectra was simultaneously examined using the median frequency and an alternative method-the spectral distribution technique. The spectral distribution technique consistently gave a better estimate of the relative change in muscle fiber conduction velocity than either of the median frequencies. This was further examined using a physiologically based EMG simulation model, which confirmed these findings. The model indicated that firing statistics can significantly influence spectral compression, particularly the behavior of characteristic frequencies in the vicinity of the firing rates. The relative change in the median frequency, whether of the amplitude or frequency spectrum, was consistently greater than the relative change in conduction velocity. The most accurate indication of the relative change in conduction velocity was obtained by calculating the mean shift in the midfrequency region of the EMG amplitude spectrum using the spectral distribution technique.     

A Deep Neural Network Model for Upper Limb Swing Pattern to Control an Active Bionic Leg

Leg amputations are common in accidents and diseases. The present active bionic legs use Electromyography (EMG) signals in lower limbs (just before the location of the amputation) to generate active control signals. The active con-trol with EMGs greatly limits the potential of using these bionic legs because most accidents and diseases cause se-vere damages to tissues/muscles which originates EMG signals. As an alternative, the present research attempted to use an upper limb swing pattern to control an active bionic leg. A deep neural network (DNN) model is implemented to recognize the patterns in upper limb swing, and it is used to translate these signals into active control input of a bionic leg. The proposed approach can generate a full gait cycle within 1082 milliseconds, and it is comparable to the normal (a person without any disability) 1070 milliseconds gait cycle.     

Simultaneous and proportional estimation of hand kinematics from EMG during mirrored movements at multiple degrees-of-freedom

This paper proposes and tests on able-bodied subjects a control strategy that can be practically applied in unilateral transradial amputees for simultaneous and proportional control of multiple degrees-of-freedom (DOFs). We used artificial neural networks to estimate kinematics of the complex wrist/hand from high-density surface electromyography (EMG) signals of the contralateral limb during mirrored bilateral movements in free space. The movements tested involved the concurrent activation of wrist flexion/extension, radial/ulnar deviation, forearm pronation/supination, and hand closing. The accuracy in estimation was in the range 79%-88% (r(2) index) for the four DOFs in six able-bodied subjects. Moreover, the estimation of the pronation/supination angle (wrist rotation) was influenced by the reduction in the number of EMG channels used for the estimation to a greater extent than the other DOFs. In conclusion, the proposed method and set-up provide a viable means for proportional and simultaneous control of multiple DOFs for hand prostheses.