Real-time, low-complexity, low-memory solution to ECG-based heart rate detection.
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.
Ravindran
Sourabh
S
Speech and Audio Lab, Signal Processing Systems R&D Center, Texas Instruments, Dallas, TX, USA. sourabh@ti.com
Dunbar
Steven
S
Nisarga
Bhargavi
B
D000465:Algorithms; D001698:Biomedical Engineering; D004562:Electrocardiography / Q000295:instrumentation / Q000706:statistics & numerical data*; D006339:Heart Rate; D006347:Heart Sounds; D006801:Humans; D010701:Phonocardiography / Q000295:instrumentation / Q000706:statistics & numerical data; D012815:Signal Processing, Computer-Assisted