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M I Harba

Publications and source records attributed to M I Harba.

4 recordsLinked to original sources
PubMed1988

On-line measurement of muscle fibre conduction velocity: analysis and optimization of performance.

Measurement of the average muscle fibre conduction velocity from surface electromyographic signals has important applications in the study of muscle fatigue and in ergonomics. In this paper, a two-channel hardware polarity correlator (which estimates 256 correlation coefficients per channel at a sampling rate of 18.58 kHz) and a specially designed surface electrode unit, are used to investigate various factors affecting the measurement reliability: electrode dimensions; EMG preprocessing to make the estimated correlation function more suitable for time delay measurement; and the manner in which velocity estimates, measured simultaneously from two different sections of the same muscle, are related. All the tests were performed on the biceps brachii when under medium tension; some tests involved tensions which led to muscle fatigue. Results showed that smaller electrode dimensions (i.e. smaller electrode units) and EMG preprocessing to increase its effective bandwidth, give more reliable measurements. Further, it was found that the estimated mean velocity is dependent on the location of the electrode unit on the muscle, and that at certain locations no reliable estimates can be obtained. The preliminary results obtained with muscle fatigue indicate that the estimated conduction velocity decreases, but not uniformly, across the muscle.

Electrodes↗
PubMed1988

Fast on-line polarity correlation algorithms for muscle fibre conduction velocity measurement.

Polarity cross-correlation is a useful technique for the measurement of muscle fibre conduction velocity using surface electromyography. Owing to the nature and volume of computation involved in the correlation function, standard techniques for its estimation by a microprocessor are too slow for an on-line application. In this paper two algorithms suitable for on-line estimation of polarity function are presented. Some useful features of the correlation function, as well as careful programming and careful choice of instructions, made it possible to use a standard microprocessor to achieve higher sampling rates than those reported recently.

Action Potentials↗
PubMed1986

EMG processor based on the amplitude probability distribution.

The EMG signal is being used increasingly for the control of prostheses and for investigating and retraining human movements. The raw (unprocessed) EMG is normally unsuitable for such applications and some processing is necessary. Due to the statistical characteristics of the EMG, it is usually difficult to achieve a processing delay of less than 100 ms. We introduce here a new EMG signal processing technique, implemented on an 8-bit microprocessor. It uses changes in the amplitude probability distribution of the EMG signal to discriminate between a number of tension levels in an individual muscle. The program employs procedures often used in pattern and speech recognition, in that it is trained to identify several tension levels. With a processing delay of 100 ms, on-line tests show that the new processor achieves a recognition rate of 84.8% when discriminating between five tension levels (including relaxation) in the biceps brachii. When the number of tension levels is reduced to four, the recognition rate becomes 96.7%, which compares well with other similar systems, some of which were tested in parallel with the new technique.

Adult↗