Dick F. Stegeman

Motor unit size estimation of enlarged motor units with surface electromyography.

Surface EMG is hardly used to estimate motor unit (MU) characteristics, while its non‐invasiveness is less stressful for patients and allows multi‐electrode recordings to investigate different sites of the muscle and MU. The present study compares motor unit potentials (MUPs) obtained with surface EMG and macro EMG during voluntary contraction of the biceps brachii muscle of patients with enlarged MUs caused by prior poliomyelitis. Averaged surface MUPs were obtained by means of needle EMG (SMUP1) and surface EMG (SMUP2) triggering. The MUPs area and peak amplitudes correlated well when comparing the macro MUP and SMUP1 of the same MUs. When MU populations of different patients were compared, the SMUP1s and SMUP2s were equally sensitive to pathology as macro MUPs. In this, the late non‐propagating positive wave (only present in unipolar recordings) is more robust than the triphasic propagating wave. Therefore, surface EMG can be used for detecting enlarged MUs.

Independent Component Analysis of High-Density Electromyography in Muscle Force Estimation

Accurate force prediction from surface electromyography (EMG) forms an important methodological challenge in biomechanics and kinesiology. In a previous study (Staudenmann , 2006), we illustrated force estimates based on analyses lent from multivariate statistics. In particular, we showed the advantages of principal component analysis (PCA) on monopolar high-density EMG (HD-EMG) over conventional electrode configurations. In the present study, we further improve force estimates by exploiting the correlation structure of the HD-EMG via independent component analysis (ICA). HD-EMG from the triceps brachii muscle and the extension force of the elbow were measured in 11 subjects. The root mean square difference (RMSD) and correlation coefficients between predicted and measured force were determined. Relative to using the monopolar EMG data, PCA yielded a 40% reduction in RMSD. ICA yielded a significant further reduction of up to 13% RMSD. Since ICA improved the PCA-based estimates, the independent structure of EMG signals appears to contain relevant additional information for the prediction of muscle force from surface HD-EMG

Multi-channel EMG of the M. triceps brachii in rats during treadmill locomotion

OBJECTIVES The study aims at a precise characterisation of intramuscularly varying recruitment patterns within the triceps brachii muscle (long and lateral head; proximal, medial, distal regions) in the time course of averaged step cycles during locomotion. METHODS The triceps brachii muscle of 15 Hannover rats was investigated with a supramuscular 16-electrodes grid during treadmill locomotion. Multi-channel electromyogram (EMG) was recorded simultaneously with high-speed videography. The rectified and smoothed EMG was time-normalised. EMG profiles and dynamic EMG-map series were calculated. Differences between EMG distribution patterns were tested by multivariate analysis of variance. RESULTS In the pre-stance phase EMG activity increased especially in the proximal long head. It most likely propagated from lower muscle layers of the long head. During stance phase the EMG activity of the lateral head rose steeply and exceeded those of the long head in short time. The fastest steps show the highest EMG amplitudes. CONCLUSIONS EMG registrations with grid electrodes help in the identification of intramuscular co-ordination processes during locomotion. While the EMG profiles characterise the time course, the topographical distribution is better represented in dynamic EMG interference maps. The dynamic changing activation patterns of triceps brachii depend on the phase of the step cycle. This clearly indicates the different functions of the muscle heads.

Selective spatial information from surface EMG after temporal filtering: the application to interference EMG using cross-covariance analysis

OBJECTIVE An increased spatial resolution in multichannel surface EMG recordings would provide new possibilities for the investigation of intermuscular and intramuscular coordination. A known analytical solution for volume conduction allows the conclusion that a high pass filtered surface electromyography (SEMG) signal contains information from a smaller environment near the recording electrode and therefore provides a higher spatial resolution. METHODS The present paper concerns experiments on 9 subjects to measure, from the human biceps brachii muscle during static isometric contraction, using multichannel surface EMG. Cross-correlation functions between bipolar SEMG channels were calculated and high pass filtered. RESULTS The correlation peaks showed the signs of propagating action potentials. The spatial width in the direction perpendicular to the muscle fibres decreased with increasing cut-off frequency. There exists an optimal cut-off frequency, which provides the best spatial resolution. It correlates with the thickness of the subcutaneous fat layer which causes a minimum depth of the active muscle fibres measured. CONCLUSIONS High pass filtered cross-covariance functions of bipolar SEMG channels have an increased spatial resolution perpendicular to the muscle fibre direction and the frequency content of the signals can potentially give an indication of the depth of the active muscle fibres.

Online Simultaneous Myoelectric Finger Control

State-of-the-art prosthetic hands allow separate control of all digits. Restoring natural hand use with these systems requires simultaneous and proportional control of all fingers. Regression algorithms might be able to predict any combination of degrees of freedom after training them separately. However, to the best of our knowledge, this has yet to be shown online. Twelve able-bodied participants were instructed to reach predefined target forces representing either single or combined finger presses, following a system training session consisting of only individual finger presses. Myoelectric control was implemented using linear ridge regression. The results demonstrated that myoelectric control allowed participants to reach both single finger, and combination targets, with hit rates of 88% and 54% respectively. These findings suggest that simultaneous control of multiple fingers is possible, even when these movements are not included in the training set.