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.
