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

Have your say: Online Public Consultation for the development of a future Skills Strategy for the healthcare sector

4 Dec 2024

Finland – South Ostrobothnia Wellbeing Technology Ecosystem is ECHAlliance Ecosystem of the Month – December

4 Dec 2024
This month we are featuring our Finland - South Ostrobothnia Wellbeing Technology Ecosystem as our Ecosystem of the Month.

£4.3 Million LaunchPad Competition Now Open

4 Dec 2024
Round two of the multi-million Health and Life Sciences Launchpad funding for Northern Ireland is now open and UK registered businesses can apply for ...

Joint Cluster Initiatives (EUROCLUSTERS) for Europe’s recovery

3 Dec 2024
The Staff Exchanges action offers a unique opportunity to promote the transfer of knowledge and innovation through international research collaboratio...

MSCA Staff Exchanges call

3 Dec 2024
The Staff Exchanges action offers a unique opportunity to promote the transfer of knowledge and innovation through international research collaboratio...

Grace Kelly Childhood Cancer Trust

3 Dec 2024
The Grace Kelly Childhood Cancer Trust (GKCCT) is a research charity that raises awareness of childhood cancers and provides funding to support resear...

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 *