Thesis Project Form
Title (tentative): Neurodiseases Motor Fluctuation Study| Thesis advisor(s): Chiappalone Michela, Vittorio Sanguineti (DIBRIS), Paolo Bonato (Harvard Medical School) | E-mail: |
| Address: Via Opera Pia 13, 16145 Genova | Phone: |
Description
Motivation and application domain
X-linked Dystonia-Parkinsonism is a disease that occurs only among Illongo people of Philippines. It is a neurodegenerative disease that evolves over the course of many years, resulting in significant disability and a shortened life span. The aim of this thesis is to use advanced machine-learning techniques to analyze data collected with wearable sensors and to assess the clinical score of the pathology in a completely automatic way.
General objectives and main activities
The thesis research will be aimed at the investigation of novel biomarkers using data analysis techniques in order to identify pathological patterns in X-linked Dystonia-Parkinsonism. Accordingly, the main tasks will be the following ones:
• Acquiring data using wearable devices, from both healthy subjects and patients.
• Developing software algorithms based on Machine Learning techniques
• Analyzing the collected data to predict clinical scores
• Acquiring data using wearable devices, from both healthy subjects and patients.
• Developing software algorithms based on Machine Learning techniques
• Analyzing the collected data to predict clinical scores
Training Objectives (technical/analytical tools, experimental methodologies)
The thesis will allow training in neuroengineering, rehabilitation, neurophysiology, data analysis, machine learning, code writing.
Place(s) where the thesis work will be carried out: Spaulding Rehabilitation Hospital, Boston, MA, USA
Additional information
Pre-requisite abilities/skills: Coding expertise is mandatory for the data analysis part.
Maximum number of students: 1
Financial support/scholarship: YES