The continuous monitoring of vital body signs such as the electrocardiogram (ECG) signal is crucial for the early detection of health issues and requires long-term monitoring with a wireless connected device that must operate for extended periods of time on a small, portable battery. This requires an ultra-low energy consumption. This doctoral research addresses the need for energy-efficient sensing devices by focusing on event-driven processing in the mixed-signal domain. By investigating event-driven level-crossing ADCs (LCADCs) that adaptively adjust the sampling rate based on the signal activity of time-sparse signals such as the ECG the research aims to minimize the power consumption of the sensing device as well as transmission power.
26/9/2024 17:00 - 19:00
ESAT Aula L
