Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Syncope also known as transient loss of consciousness which caused problem to human daily life. Since machine learning is much more advanced, classification of syncope can be done with machine learning. Head-up tilt table test (HUTT) having a lengthy procedure and might causing patient to feel disco...
Saved in:
Main Author: | Gan, Ming Hong |
---|---|
Format: | Final Year Project / Dissertation / Thesis |
Published: |
2023
|
Subjects: | |
Online Access: | http://eprints.utar.edu.my/5809/1/BI_1801320_Final_GAN_MING_HONG.pdf http://eprints.utar.edu.my/5809/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Classification of vasovagal syncope from physiological signals on tilt table testing
by: Ferdowsi, Mahbuba, et al.
Published: (2024) -
Assessing the efficacy of machine learning algorithms for syncope classification: A systematic review
by: Goh, Choon-Hian, et al.
Published: (2024) -
Experience of a rapid access falls and syncope service at a teaching hospital in Kuala Lumpur
by: Gan, S.Y., et al.
Published: (2017) -
Ethnic differences in lifetime cumulative incidence of syncope: the Malaysian elders longitudinal research (MELoR) study
by: Tan, Maw Pin, et al.
Published: (2020) -
Development of tilt table with visual feedback function for hemiplegia patients
by: Cho, J., et al.
Published: (2007)