Nur Sabrina Risman
National University of Malaysia
6 Papers
19 Citations
Nur Sabrina Risman is an academic researcher from National University of Malaysia. The author has contributed to research in topics: Intensive care & Photoplethysmogram. The author has an hindex of 4, co-authored 6 publications.
Chat about Author
Papers
Development of Respiratory Rate Estimation Technique Using Electrocardiogram and Photoplethysmogram for Continuous Health Monitoring
TL;DR: This study aims to estimate the RR from electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which consist of passive and non-invasive acquisition modules, and reveals that the filtering method efficiently extracted respiratory information from the ECG and PPG signals.
17
FPGA design and implementation of Electrocardiogram biomedical embedded system
Nur Sabrina Risman,Siti Norhayati Md Yassin,Chen Wei Sia,Yuan Wen Hau,Nazrul Anuar Nayan +4 more
- 01 Dec 2014
TL;DR: A FPGA design and implementation of Electrocardiogram biomedical embedded system (ECG-SoC) which performs ECG pre-processing and heart rate variability (HRV) feature extraction which suitable for remote homecare monitoring and rural health care application is presented.
12
A portable respiratory rate estimation system with a passive single-lead electrocardiogram acquisition module
TL;DR: Results indicate that the proposed hardware and algorithm could replace the manual counting method, uncomfortable nasal airflow sensor, chest band, and impedance pneumotachography often used in hospitals.
11
•Journal Article
Breathing rate estimation from a single-lead electrocardiogram acquisition system
TL;DR: Results indicate that the proposed hardware and algorithm could replace the manually counted, uncomfortable nasal air flow sensor or chest band often used in hospitals.
7
•Journal Article
Implementation of heart rate variability analysis algorithm on FPGA platform
TL;DR: The developed ECG-SoC system is capable of compiling a raw ECG dataset, detecting QRS, computing R-R intervals, and displaying the FFT output and power spectrum analysis and has the potential to be used in the future as a portable stand alone medical device for heart disease detection and monitoring.
5