Andreas Brink-Kjær

PhD project by Andreas Brink-Kjær

Name: Andreas Brink-Kjær
Project Title: Design of Interpretable end-to-end Deep Learning Models for Diagnosis of Sleep Disorders and Sleep Quality Evaluation
Group: Biomedical Signal Processing & AI research group
Supervisor(s): Helge B.D. Sørensen, Poul Jennum, and Emmanuel Mignot

Project Description: 

The main objective of the PhD project is to invent a deep learning system for automatic diagnosis of REM sleep behaviour disorder (RBD) from recorded PSG signals. Idiopathic RBD is regarded as a prodromal stage of neurodegeneration, and a precursor of Parkinson’s Disease. An important aim for the project is that the system is interpretable, as the system is intended to be used as an assisting tool in clinical settings. The system should, therefore, be able to highlight the signal regions that attribute to the diagnostic decision.

Perspective:
Such a system could facilitate efficient diagnosis of RBD and profiling of the neurodegenerative phenotype. Once reliable neuroprotective agents are available, early diagnosis of RBD and an accurate description of the phenotype that develops overt neurodegenerative disease would enable prevention or slow down the progression of neurodegeneration.
 

Kontakt

Andreas Brink-Kjær
Postdoc
DTU Sundhedsteknologi

Kontakt

Helge Bjarup Dissing Sørensen
Gruppeleder, Lektor MSK, Ph.D.
DTU Sundhedsteknologi
45 25 52 44