Title :
Real-time, low-complexity, low-memory solution to ECG-based heart rate detection
Author :
Ravindran, Sourabh ; Dunbar, Steven ; Nisarga, Bhargavi
Author_Institution :
Speech & Audio Lab., Texas Instrum., Dallas, TX, USA
Abstract :
This paper addresses the issue of heart rate detection from noisy ECG data, and presents a method with low complexity and low memory requirements that can detect QRS complex in the presence of noise and muscle artifacts. On the MIT-BIH arrhythmia database we were able to detect 99.3% of QRS complexes with 0.47% false detection. This method can also be applied to heart rate detection using phonocardio signals.
Keywords :
diseases; electrocardiography; medical signal detection; muscle; real-time systems; ECG-based heart rate detection; MIT-BIH arrhythmia database; QRS complex detection; false detection; muscle artifacts; noisy ECG data; phonocardio signal; Algorithms; Biomedical Engineering; Electrocardiography; Heart Rate; Heart Sounds; Humans; Phonocardiography; Signal Processing, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5334447
