A HardWare Implementation of the PWM inspired encoding/decoding algorithm (IHA-PWM). A new supervised training approach of SNN for regression based on both backpropagation and PWM inspired encoding/decoding algorithm. Define the specification for a neuromorphic HardWare implementation of both IHA-PWM and the new supervised training algorithm.

The main challenge of this approach is to characterize the state of the patient in a given time, so that the Virtual Sensor is able to detect slight variations in this state. The final goal is to provide therapists with information that allows them to adapt easily the rehabilitation therapies, so that their efficiency is maximized, which will impact on the quality of life of patients.    

This project focuses on the development of an intelligent tip for the monitoring and diagnosis of Multiple Sclerosis (MS) patients. The data adquired by this device is intended to be used for diagnosis purposes, offering objective data that can be used to optimize and adapt the rehabilitation therapy to the particular state of each patient, which will lead to the improvement of his/her life quality. MS is one of the neurological diseases with more impact in society (40000 patients in Spain), due to: 1) the average...