title: Towards real-time QRS feature extraction for wearable monitors.
abstract: The ability to generate computationally compact ECG analysis algorithms is of interest in the field of wearable physiologic monitors. Such remote monitors necessarily have limited on-board energy storage and therefore lack the computational power and physical memory often required for academic study of physiologic waveforms. Herein we evaluate a set of algorithms with markedly different computation and memory footprints useful in extracting QRS complexes from synthetically generated noisy and measured ECG signals. A small memory and computational footprint Short Time Fourier Transform ECG analysis algorithm is demonstrated to have similar sensitivity and specificity to a more complex but highly accurate Stockwell Transform.
authors.forename: Lukas
authors.initials: L
authors.lastname: Smital
authors.forename: Clifton
authors.initials: C
authors.lastname: Haider
authors.forename: Pavel
authors.initials: P
authors.lastname: Leinveber
authors.forename: Pavel
authors.initials: P
authors.lastname: Jurak
authors.forename: Barry
authors.initials: B
authors.lastname: Gilbert
authors.forename: David
authors.initials: D
authors.lastname: Holmes
mesh_terms: D000465:Algorithms; D004562:Electrocardiography / Q000295:instrumentation / Q000379:methods*; D005583:Fourier Analysis; D006801:Humans; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio