Chris Van Hoof – författare

The increasing performance of smart microsystems merging sensors, signal processing and wireless communication promises to have a pervasive impact during the coming decade. These autonomous microsystems nd applications in sport evaluation, health care, environmental monitoring and automotive s- tems. They gather data from the physical world, convert them to electrical form, compensate for interfering variables or non-linearities, and either act - rectly on them or transfer it to other systems. Most often, these sensor systems are developed for a speci c application. This approach leads to a high rec- rent design cost. A generic front-end architecture, where only the sensors and the microcontroller software are customized to the selected application, would reduce the costs signi cantly. This work presents a new generic architecture for autonomous sensor nodes. The modular design methodology provides a exible way to build a complete sensor interface out of con gurable blocks. The settings of these blocks can be optimized according to the varying needs of the application. Furthermore, the system can easily be expanded with new building blocks. The modular system is illustrated in a Generic Sensor Interface Chip (GSIC) for capa- tive sensors. Many con guration settings adapt the interface to a broad range of applications. The GSIC is optimized for ultra low power consumption. It achieves an ON-state current consumption of 40?A.

Biopotential Readout Circuits for Portable Acquisition Systems describes one of the main building blocks of such miniaturized biomedical signal acquisition systems. The focus of this book is on the implementation of low-power and high-performance integrated circuit building blocks that can be used to extract biopotential signals from conventional biopotential electrodes. New instrumentation amplifier architectures are introduced and their design is described in detail. These amplifiers are used to implement complete acquisition demonstrator systems that are a stepping stone towards practical miniaturized and low-power systems.

This book is based on a graduate course entitled, Ubiquitous Healthcare Circuits and Systems, that was given by one of the editors at his university.  It includes an introduction and overview to the field of biomedical ICs and provides information on the current trends in research.  The material focuses on the design of biomedical ICs rather than focusing on how to use prepared ICs.

This book is based on a graduate course entitled, Ubiquitous Healthcare Circuits and Systems, that was given by one of the editors at his university.  It includes an introduction and overview to the field of biomedical ICs and provides information on the current trends in research.  The material focuses on the design of biomedical ICs rather than focusing on how to use prepared ICs.

This book discusses the design and implementation aspects of ultra-low power biosignal acquisition platforms that exploit analog-assisted and algorithmic approaches for power savings.The authors describe an approach referred to as “analog-and-algorithm-assisted” signal processing.This enables significant power consumption reductions by implementing low power biosignal acquisition systems, leveraging analog preprocessing and algorithmic approaches to reduce the data rate very early in the signal processing chain.They demonstrate savings for wearable sensor networks (WSN) and body area networks (BAN), in the sensors’ stimulation power consumption, as well in the power consumption of the digital signal processing and the radio link. Two specific implementations, an adaptive sampling electrocardiogram (ECG) acquisition and a compressive sampling (CS) photoplethysmogram (PPG) acquisition system, are demonstrated.First book to present the so called, “analog-and-algorithm-assisted” approaches for ultra-low power biosignal acquisition and processing platforms;Covers the recent trend of “beyond Nyquist rate” signal acquisition and processing in detail, including adaptive sampling and compressive sampling paradigms;Includes chapters on compressed domain feature extraction, as well as acquisition of photoplethysmogram, an emerging optical sensing modality, including compressive sampling based PPG readout with embedded feature extraction;Discusses emerging trends in sensor fusion for improving the signal integrity, as well as lowering the power consumption of biosignal acquisition systems.

This book presents fundamental requirements, electrical specification, and parameter tradeoffs of wearable EEG acquisition circuits, especially those compatible with dry electrodes for user-friendly recordings.

This book presents fundamental requirements, electrical specification, and parameter tradeoffs of wearable EEG acquisition circuits, especially those compatible with dry electrodes for user-friendly recordings.

The increasing performance of smart microsystems merging sensors, signal processing and wireless communication promises to have a pervasive impact during the coming decade. These autonomous microsystems nd applications in sport evaluation, health care, environmental monitoring and automotive s- tems. They gather data from the physical world, convert them to electrical form, compensate for interfering variables or non-linearities, and either act - rectly on them or transfer it to other systems. Most often, these sensor systems are developed for a speci c application. This approach leads to a high rec- rent design cost. A generic front-end architecture, where only the sensors and the microcontroller software are customized to the selected application, would reduce the costs signi cantly. This work presents a new generic architecture for autonomous sensor nodes. The modular design methodology provides a exible way to build a complete sensor interface out of con gurable blocks. The settings of these blocks can be optimized according to the varying needs of the application. Furthermore, the system can easily be expanded with new building blocks. The modular system is illustrated in a Generic Sensor Interface Chip (GSIC) for capa- tive sensors. Many con guration settings adapt the interface to a broad range of applications. The GSIC is optimized for ultra low power consumption. It achieves an ON-state current consumption of 40?A.