9612191 Erim The objective of this study is to investigate the usefulness of two state-of-the-art methods in the analysis of electrical signals recorded from human muscles. These techniques are wavelet and time-frequency transforms, which have yielded favorable results in data compression, nonstationary signal analysis and noise removal; and fuzzy logic which has been successfully employed in decision- making and control fields. These methods will be applied to two main problems encountered in the analysis of signals recorded from muscles: a) the identification of the activities of individual muscle units represented in signals recorded via needle electrodes, and b) the analysis of the time-varying nature of signals recorded during dynamic contractions via surface electrodes attached to the skin over the muscle. The availability of powerful analysis tools will enhance the research in these fields geared toward gaining a better understanding of the control of muscles by the central nervous system, as well as the development of reliable diagnostic procedures to be used in the clinical environment. The initial year will be devoted to the implementation of the techniques proposed to be employed in the study, and to the application of these to specific signals recorded from muscles. It is hoped that this year will serve to provide the principal investigator with expertise in these new fields and help to establish her as an independent researcher. It is further hoped that the work carried out during this year will produce the preliminary results necessary to demonstrate the applicability of the mentioned techniques to the investigation of muscle signals, and that it will lead to the proposal of at least one full-blown study structured according to the findings and conclusions of the present study. ***
