Influence of amplitude cancellation on the accuracy of determining the onset of muscle activity from the surface electromyogram

Influence of foam thickness on the control of EMG activity during a step-down task in females

Compliant foams can be used to mitigate ground reaction forces. However, it is unknown how foam surfaces influence the modulation of leg muscle activity. Thus, the current study aimed to investigate how the neuromuscular system managed changes in expected loading due to various thickness of foam placed on the landing surface during a step down task. The surface electromyographic signal (sEMG) pre-activation duration and the root mean square (RMS) amplitude of tibialis anterior (TA), lateral gastrocnemius (LG), and vastus medialis (VM) of 10 active females were measured as they stepped-down with a single leg onto polyurethane foam slabs of varying thickness (0-50 mm). Pre-activation duration was not affected by the thickness of the foam padding. LG RMS amplitude was less in the foam conditions than the control (no- foam) condition, with the greatest reduction observed for the 50 mm foam condition. In some trials, the muscles remained active throughout the step-down task. In such instances, a sEMG onset time and thus a pre-activation duration could not be determined. All foam conditions significantly increased the odds of continuous muscle activity above that of the no-foam condition. The results indicate that foam surfaces may alter the modulation of muscle activity during step-down tasks.

Estimation of Muscle Co-Activations in Wrist Rehabilitation After Stroke is Sensitive to Motor Unit Distribution and Action Potential Shapes

We evaluated different muscle excitation estimation techniques, and their sensitivity to Motor Unit (MU) distribution in muscle tissue. For this purpose, the Convolution Kernel Compensation (CKC) method was used to identify the MU spike trains from High-Density ElectroMyoGrams (HDEMG). Afterwards, Cumulative MU Spike Train (CST) was calculated by summing up the identified MU spike trains. Muscle excitation estimation from CST was compared to the recently introduced Cumulative Motor Unit Activity Index (CAI) and classically used Root-Mean-Square (RMS) amplitude envelop of EMG. To emphasize their dependence on the MU distribution further, all three muscle excitation estimates were used to calculate the agonist-antagonist co-activation index. We showed on synthetic HDEMG that RMS envelopes are the most sensitive to MU distribution (10 % dispersion around the real value), followed by the CST (7 % dispersion) and CAI (5 % dispersion). In experimental HDEMG from wrist extensors and flexors of post-stroke subjects, RMS envelopes yielded significantly smaller excitations of antagonistic muscles than CST and CAI. As a result, RMS-based co-activation estimates differed significantly from the ones produced by CST and CAI, illuminating the problem of large diversity of muscle excitation estimates when multiple muscles are studied in pathological conditions. Similar results were also observed in experimental HDEMG of six intact young males.

Improved Assessment of Muscle Excitation From Surface Electromyograms in Isometric Muscle Contractions

We introduce two novel methods for the estimation of muscle excitation from surface electromyograms (EMGs), the so called cumulative motor unit activity index (CAI) and robust CAI (rCAI). Both methods aim to remove the detected motor unit action potential (MUAP) contributions from EMG but do not assess the individual motor unit spike trains. Instead, they directly estimate the cumulative motor unit spike train (CST). We compared the methods with the spatially averaged root-mean-square (RMS) envelope of the EMG signals and with the CST, estimated by the previously introduced convolution kernel compensation (CKC) method. The tests on synthetic EMG with known muscle excitation profiles demonstrated superior accuracy of newly introduced methods. In the case of 64 EMG channels and 20-dB noise, the RMS, CAI, rCAI, and CKC estimators, calculated on 0.125-s-long signal epochs, yielded the normalized RMS error (NRMSE) of 14.5% ± 2.8%, 4.4% ± 3.2%, 4.1% ± 1.8%, and 6.3% ± 4.6%, respectively. In the experimental signals from wrist extensors and flexors, the RMS, CAI, rCAI, and CKC estimations were compared to exerted muscle force. When calculated on 0.125-s-long signal epochs, they yielded the NRMSE of 11.2% ± 3.5%, 8% ± 5.6%, 10.7% ± 6.8%, and 9.0% ± 4.9%, respectively. Therefore, the newly introduced methods exhibit accuracy that is comparable to at least 200-times slower CKC method.

An Insulated Flexible Sensor for Stable Electromyography Detection: Applicationto Prosthesis Control

Electromyography (EMG), the measurement of electrical muscle activity, is used in a variety of applications, including myoelectric upper-limb prostheses, which help amputees to regain independence and a higher quality of life. The state-of-the-art sensors in prostheses have a conductive connection to the skin and are therefore sensitive to sweat and require preparation of the skin. They are applied with some pressure to ensure a conductive connection, which may result in pressure marks and can be problematic for patients with circulatory disorders, who constitute a major group of amputees. Due to their insulating layer between skin and sensor area, capacitive sensors are insensitive to the skin condition, they require neither conductive connection to the skin nor electrolytic paste or skin preparation. Here, we describe a highly stable, low-power capacitive EMG measurement set-up that is suitable for real-world application. Various flexible multi-layer sensor set-ups made of copper and insulating foils, flex print and textiles were compared. These flexible sensor set-ups adapt to the anatomy of the human forearm, therefore they provide high wearing comfort and ensure stability against motion artifacts. The influence of the materials used in the sensor set-up on the magnitude of the coupled signal was demonstrated based on both theoretical analysis and measurement.The amplifier circuit was optimized for high signal quality, low power consumption and mobile application. Different shielding and guarding concepts were compared, leading to high SNR.

Patients with sacroiliac joint dysfunction exhibit altered movement strategies when performing a sit-to-stand task

OF BACKGROUND DATA

The ability to rise from a chair is a basic functional task that is frequently compromised in individuals diagnosed with orthopedic disorders in the low back and hip. There is no published literature that describes how this task is altered by sacroiliac joint dysfunction (SIJD).

PURPOSE

The objective of this study was to compare lower extremity biomechanics and the onset of muscle activity when rising from a chair in subjects with SIJD and in healthy persons.

STUDY DESIGN

Six women with unilateral SIJD and six age-matched healthy controls performed a sit-to-stand task while we measured kinematics, kinetics, and muscle activity.

MATERIALS AND METHODS

Subjects stood up at a preferred speed from a seated position on an armless and backless adjustable stool. We measured kinematics with a 10-camera motion capture system, ground reaction forces for each leg with force plates, and muscle activity with surface electromyography. Joint angles and torques were calculated using inverse dynamics. Leg-loading rate was quantified as the average slope of vertical ground reaction (VGRF) force during the 500-millisecond interval preceding maximal knee extension.

RESULTS

Between-leg differences in loading rates and peak VGRFs were significantly greater for the SIJD group than for the control group. Maximal hip angles were significantly less for the SIJD group (p=.001). Peak hip moment in the SIJD group was significantly greater in the unaffected leg (0.75±0.22 N⋅m/kg) than in the affected leg (0.47±0.29 N⋅m/kg, p=.005). There were no between-leg or between-group differences for peak knee or ankle moments. The onset of activity in the latissimus dorsi muscle on the affected side was delayed and the erector spinae muscles were activated earlier in the SIJD group than in the control group.

CONCLUSIONS

Subjects with SIJD have a greater VGRF on the unaffected leg, generate a greater peak hip moment in the unaffected leg, use a smaller range of motion at the hip joint of the affected leg, and delay the onset of a key muscle on the affected side when rising from a seated position.

Force steadiness as a predictor of time to complete a pegboard test of dexterity in young men and women

The purpose of the study was to evaluate the capacity of an expanded set of force steadiness tasks to explain the variance in the time it takes young men and women to complete the grooved pegboard test. In a single experimental session, 30 participants (mean ± SD) (24.2 ± 4.0 yr; 15 women) performed the grooved pegboard test, two tests of hand speed, measurements of muscle strength, and a set of submaximal, steady contractions. The steadiness tasks involved single and double actions requiring isometric contractions in the directions of wrist extension, a pinch between the index finger and thumb, and index finger abduction. Time to complete the grooved pegboard test ranged from 41.5 to 67.5 s. The pegboard times (53.9 ± 6.2 s) were not correlated with any of the strength measurements or the reaction time test of hand speed. A stepwise, multiple-regression analysis indicated that much of the variance (R(2) = 0.70) in pegboard times could be explained by a model that comprised two predictor variables derived from the steadiness tasks: time to match the target during a rapid force-matching task and force steadiness (coefficient of variation for force) during a single-action task. Moreover, the pegboard times were significantly faster for women (51.7 ± 6.8 s) than men (56.1 ± 4.9 s). Participants with slower pegboard times seemed to place a greater emphasis on accuracy than speed as they had longer times to match the target during the rapid force-matching task and exhibited superior force steadiness during the single-action task.

Modulation of motor unit activity in biceps brachii by neuromuscular electrical stimulation applied to the contralateral arm

The purpose of the study was to determine the influence of neuromuscular electrical stimulation (NMES) current intensity and pulse width applied to the right elbow flexors on the discharge characteristics of motor units in the left biceps brachii. Three NMES current intensities were applied for 5 s with either narrow (0.2 ms) or wide (1 ms) stimulus pulses: one at 80% of motor threshold and two that evoked contractions at either ∼10% or ∼20% of maximal voluntary contraction (MVC) force. The discharge times of 28 low-threshold (0.4-21.6% MVC force) and 16 high-threshold (31.7-56.3% MVC force) motor units in the short head of biceps brachii were determined before, during, and after NMES. NMES elicited two main effects: one involved transient deflections in the left-arm force at the onset and offset of NMES and the other consisted of nonuniform modulation of motor unit activity. The force deflections, which were influenced by NMES current intensity and pulse width, were observed only when low-threshold motor units were tracked. NMES did not significantly influence the discharge characteristics of tracked single-threshold motor units. However, a qualitative analysis indicated that there was an increase in the number of unique waveforms detected during and after NMES. The findings indicate that activity of motor units in the left elbow flexors can be modulated by NMES current and pulse width applied to right elbow flexors, but the effects are not distributed uniformly to the involved motor units.

The extraction of neural strategies from the surface EMG: an update

A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue.

The role of muscle synergies in myoelectric control: trends and challenges for simultaneous multifunction control

Myoelectric control is filled with potential to significantly change human-robot interaction due to the ability to non-invasively measure human motion intent. However, current control schemes have struggled to achieve the robust performance that is necessary for use in commercial applications. As demands in myoelectric control trend toward simultaneous multifunctional control, multi-muscle coordinations, or synergies, play larger roles in the success of the control scheme. Detecting and refining patterns in muscle activations robust to the high variance and transient changes associated with surface electromyography is essential for efficient, user-friendly control. This article reviews the role of muscle synergies in myoelectric control schemes by dissecting each component of the scheme with respect to associated challenges for achieving robust simultaneous control of myoelectric interfaces. Electromyography recording details, signal feature extraction, pattern recognition and motor learning based control schemes are considered, and future directions are proposed as steps toward fulfilling the potential of myoelectric control in clinically and commercially viable applications.