Parkinson's Disease Motor Symptoms in Machine Learning: A Review

Autor:	Ahlrichs, Claas, Lawo, Michael
Rok vydání:	2013
Předmět:	Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	This paper reviews related work and state-of-the-art publications for recognizing motor symptoms of Parkinson's Disease (PD). It presents research efforts that were undertaken to inform on how well traditional machine learning algorithms can handle this task. In particular, four PD related motor symptoms are highlighted (i.e. tremor, bradykinesia, freezing of gait and dyskinesia) and their details summarized. Thus the primary objective of this research is to provide a literary foundation for development and improvement of algorithms for detecting PD related motor symptoms. Comment: Health Informatics: An International Journal (HIIJ), November 2013, Volume 2, Number 4
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1312.3825 Zobrazit plný text záznamu View this record from Arxiv