This book describes the analysis and design of event-driven processing circuits in the mixed-signal domain, which aim to directly reduce the amount of system data when sampling the data. By investigating event-driven sensing techniques, that adaptively adjust the sampling rate based on the signal activity of time-sparse signals such as the ECG or action potentials, the circuit techniques described in the book aim to minimize the power consumption of the sensing device as well as the transmission power. This optimization is explored in the book by investigating event-driven level-crossing ADCs (LCADCs). Readers will gain a system-level understanding of chip design for biomedical wearables, learn which parts of the system are the most important and how the different building blocks of a system interact.

• Provides a system-level perspective on wearable devices for healthcare;
• Reviews existing level-crossing ADC literature and provides a detailed analysis of this event-driven type of circuit;
• Shows readers how level-crossing ADCs work and what are the tradeoffs, compared to other circuit architectures.

This book describes the analysis and design of event-driven processing circuits in the mixed-signal domain, which aim to directly reduce the amount of system data when sampling the data. By investigating event-driven sensing techniques, that adaptively adjust the sampling rate based on the signal activity of time-sparse signals such as the ECG or action potentials, the circuit techniques described in the book aim to minimize the power consumption of the sensing device as well as the transmission power. This optimization is explored in the book by investigating event-driven level-crossing ADCs (LCADCs). Readers will gain a system-level understanding of chip design for biomedical wearables, learn which parts of the system are the most important and how the different building blocks of a system interact.