Abstract
Cerebral small vessel disease (CSVD) involves pathophysiological changes in the function and anatomy of the brain that affect its activity. Electroencephalogram (EEG) signals reflect the electrophysical activities of the brain and can be non-invasively measured with wearable devices. EEG has been used in the detection of CSVD-related cognitive impairment. Recently, development of artificial intelligence (AI) technologies provides new potential for EEG-enhanced diagnosis of CSVD. In this chapter, we review the state of the art and summarize the recent advancements as well as limitations to provide future directions for the EEG-based detection of CSVD. This chapter provides a reference for clinicians, physiologists, and biomedical engineers.
| Original language | English |
|---|---|
| Title of host publication | Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases |
| Subtitle of host publication | Towards Data-Driven Smart Healthcare |
| Editors | Haipeng Liu, Gary Tse |
| Publisher | CRC Press, Taylor & Francis Group |
| Chapter | 4 |
| Pages | 64-75 |
| Number of pages | 12 |
| Edition | 1 |
| ISBN (Electronic) | 9781003481621 |
| ISBN (Print) | 9781032771694 |
| DOIs | |
| Publication status | Published - 23 Jun 2025 |
Bibliographical note
Publisher Copyright:© 2025 selection and editorial matter, Haipeng Liu and Gary Tse; individual chapters, the contributors.