Pervasive Sensing and Machine Learning for Mental Health

Degree Course: 
Biomedical/Electronic/Computer science engineer (Information-engineering track)
Department of Information Engineering - UNIVPM

Mental health is one of the major global health issues affecting substantially more people than other non-communicable diseases. Recent advances in imaging and sensing have facilitated the acquisition of detailed neurological signals and imaging techniques for better understanding of the disorder. These technologies have led to new insights into mental illnesses providing the needed data to improve the diagnosis, identify triggers of episodes, and enable preventative interventions with diverse machine learning approaches. The candidate will be required to study, investigate and apply machine learning approaches for episode detection and early intervention for patients with health diseases.

Aim: Applying machine learning and deep learning for episode detection and early diagnosis of mental-health disease

Supervisors : Sara Moccia, Luca Romeo

Start: Sept, 2018

Expected graduation: Feb/July, 2019

Skills that will be acquired: Programming (Python, MATLAB)

Contacts: {e.frontoni, l.romeo, s.moccia}

Academic Tutor: 
Emanuele Frontoni