News

Intelligent sleep monitoring tool will help to perform early diagnosis of Parkinson’s disease

Intelligent sleep monitoring tool will help to perform early diagnosis of Parkinson’s disease
Digital Health Solutions
Member News

In cooperation with neuroscientists, the Brain Diseases Analysis Laboratory (BDALab) develops a new wearable-based system that will support the early diagnosis of Parkinson’s disease (PD). In a pilot study, it has been observed that the system could differentiate healthy controls and people with a high risk of developing PD with 89% sensitivity and 87% specificity.

The Brain Diseases Analysis Laboratory (BDALab) in cooperation with the Applied Neuroscience research group of the Central European Institute of Technology (CEITEC) and with the St. Anne’s University Hospital in Brno (FNUSA) is currently developing a system that will support neurologists in the diagnosis of Parkinson’s disease (PD) in its prodromal stage, i.e. in a period of the underlying neurodegenerative process with subtle or nonspecific symptoms. Such identification of the early stage of PD is crucial for the development of disease-modifying treatment since the neurodegeneration may be possibly stopped or treated before the pathological cascades start.

Utilising wearables (actigraphs) and machine-learning-driven post-processing, the system identifies a sleep disorder that is typically an early marker of PD. Participants wear the actigraph for 7 nights and then transfer data to a web-based system, which automatically analyse it and generate sleep measures and sleep quality reports that support the diagnosis.

The system has already passed a pilot testing, where it processed 100 recordings (nights) of people diagnosed with a high risk of developing PD (based on the MDS criteria, https://doi.org/10.1002/mds.27802), and 292 recordings of healthy controls. It was able to differentiate the group with 89% sensitivity and 87% specificity.

The development of the system was supported by European Regional Development Fund no. CE1581 (Interreg niCE-life – Development of an integrated concept for the deployment of innovative technologies and services allowing independent living of frail elderly) of the European Union (https://www.interreg-central.eu/Content.Node/niCE-life.html). Some other research topics of BDALab could be found at https://bdalab.utko.fekt.vut.cz/ 

Discover more about the Brain Diseases Analysis Laboratory:

The Brain Diseases Analysis Laboratory (BDALab) is an international multidisciplinary research group focusing on the objective and quantitative analysis of brain diseases.

NEWS​

Related News

Finland – Kuopio Health Ecosystem is ECHAlliance Ecosystem of the Month – July

15 Jul 2024
This month we are featuring our Finland - Kuopio Health Ecosystem as our Ecosystem of the Month.

EU JAMRAI- 2: Building a One Health World

15 Jul 2024
The mission at EU-JAMRAI 2 is to lead the fight against antimicrobial resistance (AMR) through joint and coordinated action across Europe.

Team MediBoost Wins AI4Health.Cro Innovation Competition

15 Jul 2024
Team MediBoost clinched the top prize at this year’s AI4Health.Cro innovation competition, winning €5,000 for their groundbreaking application designe...

Tackling obesity

8 Jul 2024
Apply for funding to develop effective strategies to tackle overweight and obesity. ‘Tackling obesity’ is open to applications submitted to the Popula...

Cancer research transatlantic development and skills enhancement award 2024

4 Jul 2024
Following the UK-US Cancer Summit, MRC and NIHR, in partnership with NCI, are launching a second competition for the cancer research transatlantic dev...

24/52 Liver Disease (EME Programme)

4 Jul 2024
The Efficacy and Mechanism Evaluation (EME) Programme is accepting Stage 1 applications to this funding opportunity.

Become a member

Join ECHAlliance to amplify your organisation’s message, grow your networks, connect with innovators and collaborate globally.
 
First name *
Last Name *
Email Address *
Country *
Position *
First name *
Last Name *
Email Address *
Country *
Position *