Machine learning approach for sudden cardiac arrest prediction based on optimal heart rate variability features
Link to publisher's homepage at www.aspbs.com/
Saved in:
Main Authors: | Murukesan, L., Murugappan, Muthusamy, Dr., Muhammad Nadeem, Iqbal, Krishinan, Saravanan, Dr. |
---|---|
Other Authors: | murukesan.loganathan23@gmail.com |
Format: | Article |
Language: | English |
Published: |
American Scientific Publishers
2015
|
Subjects: | |
Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/39430 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sudden cardiac death prediction using ECG signal derivative (heart rate variability): a review
by: Murukesan, Loganathan, et al.
Published: (2014) -
Sudden cardiac arrest (SCA) prediction system using Heart rate variability (HRV) features and machine learning algorithms
by: Murugappan, Muthusamy, Dr., et al.
Published: (2014) -
Electrocardiogram signal based sudden cardiac arrest prediction using machine learning approaches
by: L Murukesan, Loganathan
Published: (2019) -
Pre-participation Evaluation of Malaysian University Athletes – The Mmportance of Cardiovascular Screening
by: Zhuang Li Lim, et al.
Published: (2018) -
Frequency band analysis of electrocardiogram (ECG) signals for human emotional state classification using discrete wavelet transform (DWT)
by: Murugappan, Muthusamy, Dr., et al.
Published: (2014)