Ph.D Candidate: Iván González Díaz

Advisor: José Bravo Rodríguez Ph.D

The purpose of this thesis is to provide a low cost, minimally invasive, and easy deployment solution to diagnose early states of Frailty and Dementia in elderly people using Quantitative Gait Analysis. To accomplish this task, the inherent gait variability over time will be captured through long-term gait monitoring processes from different sensor sources, such as inertial measurement units (IMUs), force sensitive resistors (FSRs) arrays, smartphone built-in sensors and vision-based systems. The proposed solution will combine local data processing in the elder’s environment using the smartphone and data provided by wearable devices (i.e. wireless sensorized insoles) to estimate gait parameters based on the involved forces and a passive vision-based system that externally estimates the measurements through a structured light sensor and 3-D point-cloud processing. The temporal evolution of the estimated gait parameters will be assessed by means of inference mechanisms customizable to each subject.