TY - JOUR
AU - Steinhaus, David
AB - INTRODUCTIONCardiovascular Disease (CVD), an umbrella term encompassing an array of disorders affecting the heart and blood vessels, is the leading cause of death worldwide and a significant burden on global health care.(World Health Organisation (WHO), 2021) Early detection and monitoring of CVDs is crucial as it allows the identified conditions to be treated and appropriate medical precautions to be established. Due to the wealth of physiological information derived from the heart's electrical signal, electrocardiography is among the most effective diagnostic tools available to aid clinicians in the fight against CVD. Although once restricted to clinical settings, integrating ECG functionality into portable devices allows healthcare professionals to continuously monitor cardiac function remotely over extended periods. The ambulatory approach is compelling and is becoming increasingly valuable in diagnosing and managing cardiac arrhythmias, including atrial fibrillation (AF), which manifest infrequently and inconsistently. (Sana et al., 2020) Being able to accurately extract the relevant physiological information from patients amidst the background noise of a non‐clinical, unstable environment is vital to ensure no further increases in burden to the clinical pathway.Electrocardiogram (ECG) signals are characterized by five key features (P, Q, R, S and T waves) pertaining to the direction of electrical signal propagation through the 
TI - A universal, high‐performance ECG signal processing engine to reduce clinical burden
JF - Annals of Noninvasive Electrocardiology
DO - 10.1111/anec.12993
DA - 2022-09-01
UR - https://www.deepdyve.com/lp/wiley/a-universal-high-performance-ecg-signal-processing-engine-to-reduce-oj8cHntUCI
VL - 27
IS - 5
DP - DeepDyve
ER -