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.
Ph.D Candidate: Tania Mondéjar Palomares M.Sc
Advisor: Ramón Hervás Lucas Ph.D & José Miguel Latorre Postigo Ph.D
Nowadays, we are living a different use and understanding of videogames. Particularly, Serious Games aim to develop specific objectives beyond entertainment, mainly, educational and training objectives. There is a novel perspective that uses Serious Games as an innovative tool in the field of health (health games).
This thesis belongs to that perspective due to its multidisciplinary approach focused on neurosciences and computation. The main goal is to determine the neuropsychological brain functions while using videogames to help the design of serious games with health purposes, particularly, to support the diagnosis and treatment of cognitive-related pathologies.
Ph.D Candidate: Elitania Jiménez García
Advisor: José Bravo Rodríguez Ph.D
Co-Advisor: Jesus Fontecha Diezma Ph.D
This thesis aims to develop a method for asynchronous analysis of the glycemic trend. It will be used as a prevention tool for patients with diabetes mellitus. The glycemic trend is calculated using data mining techniques and/or artificial intellegence applied to data obtained by sensors,smartphones and smart devices. These data will be collected through continuous monitoring of patients with diabetes, considering aspects such as physical activity, blood sugar levels, diet, self-education of diabetes and endocrine profile. Also they are considered complementary aspects such as sleep, heart rate and/or emotional state.
Ph.D Candidate: Esperanza Johnson Ruiz
Advisor: José Bravo Rodríguez & Ramón Hervás Lucas Ph.D
With a certain percentage of the population having been diagnosed with different forms of Social Communications Disorders (SCD), current assistive technologies can improve their quality of life. In this thesis we explore the way in to approach an assistive system for improving SCD, based on human-avatar interaction.
This thesis will contribute with a general methodology that develops different kinds of interaction between humans and avatars, including the relationship among them and their communication skills. These skills are typically training to treat SCD.
Ph.D Candiddate: Carlos Gutierrez López de la Franca.
Advisor: José Bravo Rodríguez Ph.D & Ramon Hervás Lucas Ph.D
Activity Recognition in a scientific setting is a field that is extremely popular, in which numerous and diverse proposals exist and tackle the creation of systems capable of recognising activities through different types of sensors.
Therefore, with this proposal we intend to analyse the Behaviourof people, with a focus not only based on Activity Recognition but also with a strong component centred on smart environments with context awareness and supported by the foundations of the Psychology of Behaviour.