An overview of ML methods to model symptoms in movement disorders (the case of Parkinson’s disease): from classical ML to DL

This conference is part of the AI4Health Lecture Series organised by the Department of Computer Science and the Department of Life Sciences and Medicine of the University of Luxembourg. 

Abstract

There exist different movement disorders with different origin. Parkinson’s disease (PD) is one of those disorders and appears due to the progressive death of dopaminergic neurons in the substantia nigra of the mid-brain. Diagnosis and monitoring of PD patients is still highly subjective, time consuming and expensive. Existing medical scales used to evaluate the neurological state of PD patients cover many different aspects, including activities of daily living, motor aspects, speech and depression. This makes the task of automatically reproducing experts’ evaluation very difficult because several bio-signals and modeling methods are required to produce clinically acceptable/practical results.

This talk tries to show part of the way that has been traveled since about ten years considering different bio-signals (e.g., speech, gait, and handwriting) and methods of Machine Learning and the relatively new topics of Deep Learning (DL) with the aim to find suitable models for PD diagnosis and monitoring. Results with classical feature extraction and classification methods will be presented and also experiments with CNN and LSTM architectures will be discussed.

Speaker

Juan Rafael Orozco-Arroyave was born in Medellín, Colombia in 1981. He is an Electronics Engineer from the University of Antioquia (2004). From 2004 to 2009 he was working for a telco company in Medellín, Colombia. In 2011 he finished the MSc. degree in Telecommunications from the Universidad de Antioquia. In 2015 he finished the PhD in Computer Science in a double degree program between the University of Erlangen (Germany) and the University of Antioquia (Colombia). Currently Juan Rafael Orozco-Arroyave is associate Professor at the University of Antioquia and adjunct researcher at the Pattern Recognition Lab at the University of Erlangen.

Participation via this link: 

https://unilu.webex.com/unilu/j.php?MTID=m321de1741e5670737950863dd1982d5a