Best matches procedure in transition phase identification for hand grip test analysis in normal and pathological subjects

In this work the analysis of biomedical data characterizing motor activities of the limbs is carried out with the aim to extract useful information for evaluate the state of subjects affected by Parkinson's disease. Previously, a simple and inexpensive system that measures the force of palmar grip has been presented, then a suitable software protocol able to record, to manage and to enterprise the acquired data, has been realized. Afterwards, a first analysis in time domain has led to identify some biomedical parameters characterizing motor activities of limbs; the study of these parameters and the analysis of the correlations between the acquired data, has permitted to develop suitable models describing the time behavior of the palmar grip. In this paper the authors propose a more detailed study that evaluates the filtering, phase noise effects and the performances of different methods used to estimate the characteristic parameters of the palmar grip.