FOG-IT - An Integrated software platform for Tagging Freezing of Gait in Parkinson’s Disease
From 01-01-2021 to 31-12-2023
Description
Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting around 2% of older people (>60 years). Alarmingly, PD is one of the fastest growing neurological disorders with a prevalence that doubles every 20-30 years. Due to ageing and environmental factors, 4.3 million people will be living with PD by 2040 in the EU alone.1 The disease hallmark is an alpha-synucleinopathy-driven loss of mainly nigrostriatal dopaminergic neurons, causing a widespread brain circuitry dysfunction and a multitude of motor and non-motor symptoms.2 Freezing of Gait (FOG), whereby patients suddenly lose the ability to walk, is quite possibly the most debilitating symptom, as it is episodic and most of all unpredictable. Most patients will develop FOG in the course of the disease (70% after 5-10 years), a turning point called ‘FOG-conversion’. Once this milestone is reached, patients experience more anxiety, have a lower quality of life and are at a much higher risk of falls.3 Sixty-one percent of falls in PD are directly due to FOG often forcing institutionalization into nursing homes.4 Current treatments are unable to slow down PD and offer only partial relief for FOG. Despite prolific research efforts,5 the underlying biology of FOG is ill-understood, precluding therapeutic development. The most important limitation to advance novel treatments is the difficulty to measure FOG. Health professionals rely on unreliable clinical methods to rate FOG. Research and industry depend on motion capturing (MoCap) systems, which work well for normal motion but fail to pick up disrupted movement without costly visual annotation. With this project, we want to address this bottleneck by pioneering and testing a technology-driven FOG-measurement software platform. We propose a 4-phased release of this platform, evolving from (1) basic automatic, (2) multiple source, (3) personalized to (4) online assessment. With each upgrade, we will target the interest from the scientific and medical instruments communities, and will license our software to parties who have the capacity to perform the upscaling.
Team
- Bart Vanrumste, Co-promoter
- Alice Nieuwboer, Coordinator (External)
Financing
Funding: KU Leuven - Internal Funding KU Leuven
Program/Grant Type: C3 - KU Leuven Category 3 Funding
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.