Classification of Alzheimer’s Patients through Ubiquitous Computing

Sensors

卷:17

Carmen Lage¹  Alicia Nieto-Reyes²  Rafael Duque²  José Luis Montaña² 

[1] Cognitive Disorders Unit, Department of Neurology, Marqués de Valdecilla University Hospital (HUMV) Valdecilla Biomedical Research Institute (IDIVAL), 39008 Santander, Spain;

[2] Department of Mathematics, Statistics and Computer Science, Universidad de Cantabria, 39005 Santander, Spain;

关键词: Alzheimer;    functional data analysis;    healthcare;    hypothesis testing;    pattern recognition;    supervised classification;    ubiquitous computing;   

DOI  :  10.3390/s17071679

来源: DOAJ

【 摘 要 】

Functional data analysis and artificial neural networks are the building blocks of the proposed methodology that distinguishes the movement patterns among c’s patients on different stages of the disease and classifies new patients to their appropriate stage of the disease. The movement patterns are obtained by the accelerometer device of android smartphones that the patients carry while moving freely. The proposed methodology is relevant in that it is flexible on the type of data to which it is applied. To exemplify that, it is analyzed a novel real three-dimensional functional dataset where each datum is observed in a different time domain. Not only is it observed on a difference frequency but also the domain of each datum has different length. The obtained classification success rate of 83 % indicates the potential of the proposed methodology.

【 授权许可】

Unknown