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Objective Using the Twente Medical Systems international B.V. (TMSi) electromyography (EMG) system, active signal shielding was applied to clean signals and create data without interference and cable movement artifacts. TMSi, used in high-density surface EMG pattern recognition, controls myoelectric rehabilitation robots, yet few have studied how active signal shielding influences pattern recognition. This study aimed to investigate how active signal shielding used within the TMSi influenced motion pattern recognition. Methods Surface EMG of dominant side forearm and hand muscles was studied in eight healthy participants. The common component’s influence was accessed by the classification performance of wrist and hand functional movements. Results The classification performance of EMG signals with the common component was obviously lower than signals without the common component using one to five electrodes. Conversely, a higher motion classification performance was achieved using signals with the common component using over 12 electrodes. Optimal channel distribution was examined based on the sequential feed-forward selection method, showing that the common component affected the optimal channel location. Conclusions Active signal shielding in the TMSi improved classification accuracy in motion pattern recognition when over 12 electrodes were used. The optimal channel distribution was related to the common component when using the TMSi.

Surface electromyography (EMG) signal from trunk muscles is often contaminated by electrocardiography (ECG) artifacts. This study presents a novel method for muscle activity onset detection by processing surface EMG against ECG artifacts. The method does not require removal of ECG artifacts from raw surface EMG signals. Instead, it applies the sample entropy (SampEn) analysis to highlight EMG activity and suppress ECG artifacts in the signal complexity domain. A SampEn threshold can then be determined for detection of muscle activity. The performance of the proposed method was examined with different SampEn analysis window lengths, using a series of combinations of 'clean' experimental EMG and ECG recordings over a wide range of signal to noise ratios (SNRs) from -10 to 10 dB. For all the examined SNRs, the window length of 128 ms yielded the best performance among all the tested lengths. Compared with the conventional amplitude thresholding and integrated profile methods, the SampEn analysis based method achieved significantly better performance, demonstrated as the shortest average latency or error among the three methods (p < 0.001 for any of the examined SNRs except 10 dB).

The objective was to re-evaluate the controversial reports of EMG-torque relation between impaired and non-impaired sides using linear electrode array EMG recordings. Ten subjects with chronic stroke performed a series of submaximal isometric elbow flexion tasks. A 20-channel linear array was used to record surface EMG of the biceps brachii muscles from both impaired and non-impaired sides. M-wave recordings for bilateral biceps brachii muscles were also made. Distribution of the slope of the EMG-torque relations for the individual channels showed a quasi-symmetrical “M” shaped pattern. The lowest value corresponded to the innervation zone (IZ) location. The highest value from the slope curve for each side was selected for comparison to minimize the effect of electrode placement and IZ asymmetry. The slope was greater on the impaired side in 4 of 10 subjects. There were a weak correlation between slope ratio and strength ratio and a moderate to high correlation between slope ratio and M-wave ratio between two sides. These findings suggest that the EMG-torque relations are likely mediated and influenced by multiple factors. Our findings emphasize the importance of electrode placement and suggest the primary role of peripheral adaptive changes in the EMG-torque relations in chronic stroke.

The motor unit number index (MUNIX) technique has provided a quick and convenient approach to estimating motor unit population changes in a muscle. Reduction in motor unit action potential (MUAP) amplitude can lead to underestimation of motor unit numbers using the standard MUNIX technique. This study aims to overcome this limitation by developing a modified MUNIX (mMUNIX) technique. The mMUNIX uses a variable that is associated with the area of compound muscle action potential (CMAP) rather than an arbitrary fixed value (20 mV ms) as used in the standard MUNIX to define the output. The performance of the mMUNIX was evaluated using motoneuron pool and surface electromyography (EMG) models. With a fixed motor unit number, the mMUNIX output remained relatively constant with varying degrees of MUAP amplitude changes, while the standard MUNIX substantially underestimated the motor unit number in such cases. However, when MUAP amplitude remained unchanged, the mMUNIX showed less sensitivity than the standard MUNIX in tracking motor unit loss. The current simulation study demonstrated both the advantages and limitations of the standard and modified MUNIX techniques, which can help guide appropriate application and interpretation of MUNIX measurements.

A novel spatiotemporal muscle activity imaging (sMAI) approach has been developed using the Extended Kalman Filter (EKF) to reconstruct internal muscle activities from non-invasive multi-channel surface electromyogram (sEMG) recordings. A distributed bioelectric dipole source model is employed to describe the internal muscle activity space, and a linear relationship between the muscle activity space and the sEMG measurement space is then established. The EKF is employed to recursively solve the ill-posed inverse problem in the sMAI approach, in which the weighted minimum norm (WMN) method is utilized to calculate the initial state and a new nonlinear method is developed based on the propagating features of muscle activities to predict the recursive state. A series of computer simulations was conducted to test the performance of the proposed sMAI approach. Results show that the localization error rapidly decreases over 35% and the overlap ratio rapidly increases over 45% compared to the results achieved using the WMN method only. The present promising results demonstrate the feasibility of utilizing the proposed EKF-based sMAI approach to accurately reconstruct internal muscle activities from non-invasive sEMG recordings.

We examined surface electromyogram (EMG) characteristics during voluntary isometric activation of the first dorsal interosseous (FDI) muscle in stroke survivors. Five stroke subjects participated in the study. They were instructed to generate isometric contraction at different force levels. The recording was performed in both paretic and contralateral muscles using a matched force protocol. Comparisons of the spike amplitude distribution of the surface EMG signals were made between paretic and contralateral muscles. For a given contraction level, a widened or narrowed spike amplitude distribution was observed in paretic muscles of stroke subjects. Such differences may be induced by degeneration of some spinal motoneurons and/or disorganization of motor unit control properties after stroke.

Hemispheric brain injury resulting from a stroke is often accompanied by weakness in contralateral limbs. Appropriate motoneuronal recruitment and rate modulation is necessary to optimize muscle force production utilizing residual neuromuscular elements. We sought to determine whether weakness in a hand muscle in stroke survivors is partially attributable to alterations in the control of the motor units in the affected muscles. Specifically, our goal was to characterize whether surface EMG amplitude, a gauge of neural input, was systematically larger as a function of force, in paretic muscles when compared to the contralateral muscles in the same subject, and to neurologically intact subjects. We tested the first dorsal interosseous (FDI) in five hemiparetic and six neurologically intact subjects. In four of the stroke subjects the EMG-force slope was significantly greater on the affected side as compared to the contralateral side as well as compared to neurologically intact subjects. We discuss possible experimental as well as physiological factors that may contribute to an increased slope, concluding that a combination of abnormal firing rate patterns and changes in MU control are the most likely reasons for the observed changes.