Objective monitoring of axial symptoms in Parkinson's disease

Duration: October 2023 – September 2025

Scientific Coordinator: Marco Ghislieri

Project Type: Funded project through competitive call

PoliTO Role: Scientific Partner

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder characterized by numerous motor and non-motor symptoms that differentially impact patients’ daily activities, independence, and quality of life. Besides cardinal motor symptoms such as bradykinesia, rigidity, and tremor, which predominantly affect the limbs, another set of motor symptoms, termed axial motor symptoms, manifest during disease progression. These axial symptoms have been identified as primary determinants of reduced independence and quality of life and can also contribute to mortality by causing falls and aspiration pneumonia. Moreover, axial symptoms respond poorly or not at all to common therapeutic strategies and are often recognized only when their consequences become apparent. 

Recent scientific efforts have focused on developing e-Health tools for more granular and accurate detection and quantification of motor symptoms and their fluctuations, not only in clinical settings but also during patients’ everyday lives. However, accurate and reliable monitoring of axial symptoms has received limited attention and remains a research priority. 

In this context, this project aims to develop a system for detecting and monitoring freezing of gait, postural abnormalities and instability, speech problems, and dysphagia using wearable technologies including cameras, surface EMG probes, and motion sensors. Based on the team’s expertise and preliminary data, we intend to establish an adequate system for quantifying these four principal axial symptoms, test it on patients in clinical settings, and deploy it in home environments. The ultimate goal is to propose a technological tool for long-term, ecological, and quantitative assessment of axial symptoms in Parkinson’s Disease. 

The multidisciplinary research team has the necessary knowledge and experience to set the research context, test suitable technologies, and analyze data with algorithms based on previous research. The system will be validated in both research and home environments to enable accurate detection and quantification of axial symptoms in Parkinson’s Disease. 

Involved Structure

• DET, Department of Electronics and Telecommunications (project lead) 
• DAUIN, Department of Control and Computer Engineering 

Partners

• University of Turin 
• Politecnico di Milano 
• IEIIT CNR 
• University of Rome "La Sapienza" 

Location

• University of Turin 
• Politecnico di Milano 
• IEIIT CNR 
• University of Rome "La Sapienza" 

Project Team

• Dr. Marco Ghislieri (DET), Politecnico di Torino 
• Dr. Carlo Alberto Artusi, University of Turin 
• Dr. Claudia Ferraris, National Research Council 
• Prof. Veronica Cimolin, Politecnico di Milano 
• Dr. Antonio Suppa, University of Rome "La Sapienza" 

Sustainable Development Goals (SDGs)

3. Good health and well-being