Simulation linking EMG power spectra to recruitment and rate coding

Surface electromyogram signal modelling

The paper reviews the fundamental components of stochastic and motor-unit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.

Physiology and interpretation of the electromyogram

The purpose of this review is to consider some issues in the interpretation of the electromyogram (EMG) and to discuss current areas of controversy regarding use of the EMG. We consider the underlying physiology and origin of the EMG signal and offer an abbreviated discussion of measurement issues and selected factors that affect the characteristics of the EMG signal. We discuss many of the problems affecting interpretation, including normalization, crosstalk, and issues specific to contraction. In the final section, we consider topics of current interest in electromyography, such as muscle fatigue, task specificity, multichannel representations, and muscle fiber conduction velocity. We present, in addition, alternative analysis techniques. This review should interest researchers and clinicians who seek to obtain the valuable information inherent in the EMG while respecting the potential sources of variance and misinterpretation.

Differences between surface EMG in male and female subjects evidenced by automatic analysis

40 healthy volunteers (20 males and 20 females) have been studied by an automatic analysis of their surface EMG. The power density spectrum (PDS) of the electromyographic signal, derived from the tibialis anterior muscle, was used to evaluate the RMS values of the EMG developed during maximal voluntary (Vc) and evoked (Vm) contractions. The ratios between Vc, calculated over each of 5 frequency bands (5-15, 20-40, 45-70, 75-110, 115-160 Hz), and the total Vc have also been calculated. No significant differences emerge in the Vm values for males and females, whereas the Vc values for female subjects are found to be significantly reduced (P less than 0.001) with respect to the corresponding values for males. Significant differences have also been found concerning the percentage distribution of power in the above mentioned frequency bands for men and women (P less than 0.001). It can thus, be hypothesized that there are two different modalities of motor unit recruitment and that different sociological and cultural traditions may be more important in producing these differences than sexually determined physiological differences.

Neural control of head rotation: electromyographic evidence

Electromyograms, representing samples of neurological control signals, can be used to predict head rotation that can be either time optimal or non-time optimal, depending upon a given subject's intent. Kinematic factors such as operating levels in terms of horizontal and vertical position of the head from which horizontal rotations are made, importantly influence the tonic and phasic aspects of the EMG signal. Pairs of head-rotating muscles, splenius and sternocleidomastoideus muscles, demonstrate reciprocal innervation, particularly for time optimal head rotations. Head rotations of the same amplitude but different velocities correlate with pulse height and pulse width of envelopes of the rectified EMG. Rise of the agonistic EMG correlates in detail with rise of the acceleration transient for a given fast or slow head rotation. Our data demonstrate both the optimal control of details of head movements and the influence of the stretch reflex that strongly relates to initial head position and the velocity of the movements around the primary position. The results support the idea of higher level programmed control of head rotation in human subjects.