Detecting Dementia Using EEG Signal Processing and Machine Learning

Mahbuba Ferdowsi, Choon-Hian Goh, Gary Tse, Haipeng Liu

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)
1 Downloads (Pure)

Abstract

Dementia is a syndrome associated with an ongoing decline in brain functioning, with impaired ability to remember, think, or make decisions. It is an increasing global public health problem, with nearly 10 million new cases each year. The total number of people with dementia is projected to reach 82 million in 2030 and 152 million in 2050. Dementia imposes a huge economic burden, with the costs are associated with the severity. The early detection of dementia plays a key role in improving the intervention and management and reducing the costs.
Original languageEnglish
Title of host publicationArtificial Intelligence Enabled Signal Processing based Models for Neural Information Processing
EditorsRajesh Kumar Tripathy, Ram Bilas Pachori
Place of PublicationBoca Raton
PublisherCRC Press, Taylor & Francis Group
Chapter10
Pages150-167
Number of pages18
Edition1
ISBN (Electronic)9781003479970
ISBN (Print)9781032529301
DOIs
Publication statusPublished - 6 Jun 2024

Bibliographical note

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

Keywords

  • Dementia
  • EEG
  • Neurology

Fingerprint

Dive into the research topics of 'Detecting Dementia Using EEG Signal Processing and Machine Learning'. Together they form a unique fingerprint.

Cite this