Alzheimer's disease detection using orthogonal matching pursuit and k-nearest neighbors classifier on EEG signals

Authors

  • Al Christian N. Mabute ⋅ PH Department of Physical Sciences and Mathematics, University of the Philippines Manila
  • Herbert B. Domingo ⋅ PH Department of Physical Sciences and Mathematics, University of the Philippines Manila

Abstract

The possible use of electroencephalography (EEG) signal as biomarker for detecting Alzheimer's disease (AD) and determining its severity is already known. EEG signals from a Florida State University study dataset were decomposed using orthogonal matching pursuit algorithm and subsequently applied k-nearest neighbors classifier. Obtained mean accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve indicate that EEG signal processing can be used for screening and detecting AD in humans.

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Issue

Article ID

SPP-2024-PF-04

Section

Poster Session F (Physics Education and Interdisciplinary Topics)

Published

2024-06-25

How to Cite

[1]
ACN Mabute and HB Domingo, Alzheimer’s disease detection using orthogonal matching pursuit and k-nearest neighbors classifier on EEG signals, Proceedings of the Samahang Pisika ng Pilipinas 42, SPP-2024-PF-04 (2024). URL: https://proceedings.spp-online.org/article/view/SPP-2024-PF-04.