Sanjeev D. Nandedkar

Motor unit number index (MUNIX)

The surface-recorded compound muscle action potential (CMAP) and electromyographic (EMG) interference pattern is used to compute the motor unit number index (MUNIX). The MUNIX demonstrated all known changes in the number of motor units in normal subjects, and in patients with amyotrophic lateral sclerosis (ALS). In normal subjects MUNIX decreased slightly with age and showed excellent reproducibility. In many ALS patients MUNIX was reduced even when the CMAP was normal. Lower MUNIX values were seen in weaker muscles. This is a noninvasive method that requires minimal electrical stimulation. It is performed in less than 5 min. This makes it suitable for serial EMG investigations.

Quantitative electrophysiologic studies in sporadic inclusion body myositis.

Sporadic inclusion body myositis (S‐IBM) is a progressive, acquired disease of unknown etiology. Prior studies have suggested neurogenic involvement based on electrophysiologic data, although the biopsy is compatible with a myopathic process. Quantitative electrophysiologic studies were performed in the biceps brachii of 17 subjects with biopsy‐proven S‐IBM. Quantitative motor unit action potential (MUAP) analysis was compatible with myopathy in 16 subjects, with the remaining subject being within normal limits. Quantitative interference pattern was myopathic in all 13 subjects studied. Macro‐EMG MUAP amplitude was reduced in 3 of 17 studies; the remainder were within normal range, and none was increased as would be expected in neurogenic disease. Fiber density was normal to borderline increased in all subjects. Possible reasons for encountering neurogenic‐appearing MUAPs may include choice of muscle studies, because some patients have co‐existing polyneuropathy and large‐amplitude MUAPs from hypertrophied muscle fibers. The data from this study indicate that S‐IBM is a myopathic process.

Models and simulations in electromyography

In electromyography, one assesses the pathophysiology on the basis of the waveform characteristics of the recorded signal. This requires detailed knowledge of the relationship between the waveform generators and the waveform measurements. Models and computer simulations can be used to explore this relationship in an efficient manner. Combining models with experimental methods will allow us to define new measurements and new rules of interpretation. This is discussed with some of the models developed for electromyography signal analysis.

Some observations on fibrillations and positive sharp waves

Electromyographic recordings of fibrillation potentials (FPs) and positive sharp waves (PSWs) demonstrate transformation of FP to PSW and vice versa, atypical firing patterns, changes in waveform shape and amplitude, and time‐locked potentials. The etiology of the waveform characteristics of FP and PSW is discussed based on abnormal propagation in a small section of muscle fiber that is “damaged” by the needle. The results of simple computer simulations are described.

Quantitative EMG Analysis

In the past five decades, a variety of quantitative analysis techniques have been developed. Some require special electrodes as in single-fiber or macro EMG techniques. In this chapter, we will limit our discussion to EMG quantification by the concentric and monopolar needle electrodes used for the routine EMG examination. We will also review some techniques of motor unit number estimation that complement the routine needle electrode analysis.

Digital reproduction of biopotential waveforms for neurophysiological studies

A simple biological signal generator capable of reproducing complex biopotential waveforms is described. It is constructed by a combination of digital and analog circuit components and can be used under different experimental conditions, such as in calibration of biomedical instrumentation systems, or simply as a function generator providing voltage outputs of various waveforms. The biopotential waveform to be generated is sampled at a high frequency and the samples are stored sequentially in a programmable read only memory (PROM). The samples are then fed in the same sequence to a digital-to-analog (D/A) converter and the resulting output is amplified and a DC offset is added. External controls are provided to adjust the DC offset, amplitude and repetition rate of the signal generated. The reproduced voltage signals are stable and superior in quality to those produced by conventional biological signal generators.

MICROPROCESSOR-BASED JITTER ANALYSIS IN SINGLE FIBER ELECTROMYOGRAPHY

In single fiber electromyographic recordings of action potentials from two muscle fibers belonging to the same motor unit, a variability in the interval between action potentials in successive discharges is observed. This is largely due to variations in transmission time from nerve to muscle. This variability, called “jitter,” is typically expressed as the mean consecutive difference (MCD). Increased jitter has been clinically used to diagnose the defect of neuromuscular transmission that characterizes myasthenia gravis. We have developed a microprocessor-based system that automatically measures the jitter in single fiber EMG. A pulse lasting for the duration of the interpotential interval (IPI) is generated using analog and digital hardware. A microprocessor system based on INTEL 8080 is employed to measure IPI in groups of 20 and up to 10 groups in a single run. Elementary statistical analysis is performed and the results are displayed on a CRT and a monitor scope. The hardware preprocessing of the signal makes it feasible to measure jitter with precision up to one microsecond. Complete control of data acquisition and processing is available through software commands.