A method for quantifying electromyograms.

When the motor end plate of a motor neuron transmits a signal to its muscle fibers, it induces local voltage changes that reflect the functional utilization of the muscle. Electromyography (EMG) is a technique for recording these localized voltage changes either from the surface of the entire muscle or within the muscle by the insertion of needles or pairs of fine wires (Guha and Amend. i979). The voltage changes at the electrode tips are amplified, displayed on a chart recorder or oscilloscope screen. and also stored on magnetic tape for subsequent analysis. EMG is now used extensively in a variety of biological and biomedical applications. It is also being used in zoological studies to report on muscular activity during feeding, locomotion. breathing and display behavior in fishes, amphibians, reptiles, birds and mammals. With relatively few exceptions. the descriptions for the records obtained are qualitative. Start and stop ofactivity may be ietermined from chart records or films taken from an oscilroscope screen. However, the magnitude of these signals and the changes with time (coincident with physical events) are often sorted only into general categories of ‘high’, ‘medium’ and ‘low’ firing intensity. Such descriptors permit only limited correlation with the physical effects induced by muscular activity. The literature contains numerous proposals for computergenerated spectra) analysis of EMG signals (Basmajian er al.. 1975; Desmedt. 1973: Eberstein and Goodgold, 1978). However. these approaches have not found their way into most studies on functional morphology, either because of the cost and complexity of the equipment concerned or because correlation with mechanical events has not been obvious. The present paper describes a simple system that simultaneously analyzes up to seven channels of electromyograms. (1) It can utilize data stored on any analog or commercial FM tape system. so that the results of several experimental laboratories may be analyzed in a single central facility. (2) It provides a data matrix directly from the analog signal without intervening manual steps. Each channel of the EMG record is subdivided automatically into sampling intervals (bins). For each of these, the resulting data matrix lists the number of spikes and their mean height. The matrix is machine readable and may be transformed into bar graphs and otherwise analyzed by an intelligent graphics system. (3) It permits compensation for variable levels of basehne noise during analysis. (4) It incorporates the capacity for analysis of other physrcal factors. such as displacement or pressure. (5) It