Authors:
Angela Pimentel
1
;
Hugo Gamboa
2
;
Sérgio Reis Cunha
3
and
Ana Dulce Correia
4
Affiliations:
1
FCT-UNL, Portugal
;
2
FCT-UNL and PLUX - Wireless Biosignals, Portugal
;
3
Porto University, Portugal
;
4
University of Lisbon, Portugal
Keyword(s):
Parkinson’s Disease (PD), Zebrafish, Behaviour, Biosensor MOBS, Machine Learning.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Detection and Identification
;
Devices
;
Health Information Systems
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Physiological Computing Systems
;
Wearable Sensors and Systems
Abstract:
Parkinson’s disease (PD) is one of the neurodegenerative diseases with an increased prevalence widely studied by the scientific community. Understanding the behaviour related to the disease is an added value for diagnosis and treatment. Thus the use of an animal model for PD that develops similar symptoms to the human being allows to the clinic a larger vision over the health of a patient. Zebrafish can be used to study some human diseases including PD. This work describes the development of an algorithm for the characterization of behaviour in this specie. The biosensor called Marine On-line Biomonitor System (MOBS) is connected electrically to chambers where the specimen of zebrafish moves freely providing a signal that is related with the fish activity. Using the developed algorithm based on signal processing, statistic analysis and machine learning techniques we present classification of a fish as normal or ill and characterize its behaviour.