Projet SOSSOLARY_C is a software package, developped in the synchronous, data flow, parallel language SIGNAL, primary dedicated to the Autonomic Nervous System (ANS), through the analysis of physiological signals and their correlations: Heart Rate (HR), Arterial Blood Pressure (ABP), breathing, motility and electro-encephalographic activity (EEG). Our aim is to illustrate the new approach given by LARY_C for the processing of polygraphic recordings, through a clinical application, the nocturnal Periodic Leg Movements (PLM). Polygraphic recordings analysis, usually visually done, can't provide all the needed information, in particular the relations between rhythms are difficult to extract. The LARY_C library of medical signal processing provides a condense representation of the physiological rhythms; the SIGNAL synchronous environment provides the necessary tools to assess the relationships between these rhythms, in order to automatically produce a set of (cardiovascular) parameters related to an event (a PLM). We analysed the magnitude of the changes on HR and systolic ABP, the ANS behaviour through their activity in high and middle frequencies, the delays between the beginning of cardiovascular perturbations and the movement, and the relations with cortical activation reflected by an augmentation of α activity on the EEG. On one hundred PLM in a typical patient, cardiovascular changes related to movements are significant; the more often, they precede the movement and they are even more important in presence of high α-activity. These preliminary results show PLM not only like a central nervous system dysfunction addressed to the motor system but rather like a dysfunction of reticular excitability responsible for motor, ANS and cortical activation. They ask the question of long term consequences of these cardiovascular swings and therefore of their specific treatement in addition to sleep and motor desorders one. Such an automatic approach seems appropriate for a better understanding of the physiopathology and to help the diagnostic in a large variety of clinical applications involving non-stationary, long duration polygraphic signals
