Cardiovascular diseases are the leading cause of death globally, represent-ing 31.4% of all deaths in the world in 2022. With more than half of all cardiovascu-lar disease-related deaths happening in settings outside of the hospital, there is a needfor constant at-home monitoring to prevent them. Such long-term monitoring solutionsnecessitate auton...
Cardiovascular diseases can be detected early by analyzing the electrocardiogram of a patient using wearable systems. In the context of smart sensors, detecting arrhythmias with good accuracy and ultra-low power consumption is required for long-term monitoring. This paper presents a novel cardiac arrhythmia classification method based on antidictio...
Cardiovascular diseases can be detected early by analyzing the electrocardiogram of a patient using wearable systems. In the context of smart sensors, detecting arrhythmias with good accuracy and ultra-low power consumption is required for long-term monitoring. This paper presents a novel cardiac arrhythmia classification method based on antidictio...
Published in Theoretical Computer Science
