The biomechanical signals acquisition through wireless sensor networks and the information processing for healthcare in patients with Parkinson's disease (PD) have an important challenge. As well as other biomechanical signs, patients with PD usually present slow movements, difficult to initiate, vary or interrupt which reflect in gait alterations. The patient should walk at least 10 meters, then turn around and return to the starting point. These movement requirements can affect the wireless communication quality. Currently there are many scales for the assessment of patients with PD, but in recent research, the scale 'Movement Disorder Society-Unified Parkinson's Disease-Rating Rating Scale' (MDS-UPDRS) has gained great notoriety. However, evaluation is in a subjective way and depends a lot on the patient's momentary status and the results shown are qualitative only, and the subtle differences not detected. This paper presents results with wireless sensors networks Bluetooth and XBee, respectively, as well as the first stage of a diffuse model to analyse, evaluate and classify the gait according to the parameters established by the MDS-UPDRS, with multi-axial signals from inertial measurement units. The model presented good results for evaluation and classification, always backed-up by the help of medical experts.