| Description |
1 online resource |
| Series |
Analog circuits and signal processing series |
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Analog circuits and signal processing series.
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| Contents |
Intro; Preface; Abstract; Acknowledgments; Contents; Abbreviations and Acronyms; List of Figures; List of Tables; 1 Challenges and Opportunities in Wearable Biomedical Interfaces; 1.1 Introduction; 1.2 Low-Power Biomedical Interfaces; 1.3 Introduction and Overview of ECG and PPG; 1.3.1 Introduction to ECG SignalProcessing; 1.3.2 Introduction to PPG Signal Processing; 1.4 Architectural and Algorithmic Approaches: Assisted Processing Architectures; 1.5 Overview and Organization of the Book; 2 Adaptive Sampling for Ultra-Low-Power ECG Readouts; 2.1 Overview of Adaptive Sampling |
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2.2 Adaptive Sampling for ECG2.2.1 Performance Evaluation of Adaptive Sampling on Real Datasets; 2.2.2 Energetics and Power Budget of the Analog Adaptive Sampling Controller (ASC); 2.3 Architecture of the Adaptive Sampling Controller (ASC); 2.3.1 Activity Detector; 2.3.2 Delay Element; 2.3.2.1 The Filter Transfer Function; 2.3.2.2 Passive Bessel Filter Topology; 2.3.2.3 gm-C Filter Topology; 2.3.2.4 Noise Analysis; 2.3.2.5 Effect of Non-idealities of the OTA on Filter Response; 2.4 Measured Performance of the Adaptive Sampling Controller(ASC); 2.5 Conclusions |
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3 Introduction to Compressive Sampling (CS)3.1 Beyond Nyquist Signal Processing; 3.2 Compressive Sampling Signal Acquisition; 3.3 Compressive Sampling Signal Reconstruction; 3.4 Reconstruction Algorithm with Reduced Edge Artifacts; 3.4.1 Algorithm Proposal; 3.4.2 Computational Complexity of Overlapped Window Reconstruction; 3.4.3 Simulation Results; 3.5 State-of-the-Art Compressive Sampling HardwareImplementations; 3.6 Conclusions; 4 Compressed Domain Feature Extraction; 4.1 Introduction; 4.2 Overview of the State of the Art; 4.3 Feature Extraction from Compressively Sampled PPG Signals |
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4.4 Conclusions5 A Low-Power Compressive Sampling (CS) PPG Readout with Embedded Feature Extraction; 5.1 Introduction; 5.2 PPG SoC Architecture and Building Blocks; 5.2.1 Duty Cycle Reduction in Compressive Sampling (CS) PPG Readout; 5.2.2 Compressive Sampling (CS) PPG SoC Architecture; 5.2.3 Architecture of the Analog Front End (AFE); 5.2.3.1 The Transimpedance Amplifier (TIA); 5.2.3.2 The Switched Integrator (SI); 5.2.3.3 The Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC); 5.2.4 Architecture of the Digital Back End (DBE) |
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5.3 Measured Performance of the PPG Application Specific Integrated Circuit (ASIC)5.4 Conclusions; 6 Conclusions and Future Work; 6.1 Summary and Contributions of the Book; 6.2 Future Work; 6.2.1 Motion Artifact Reduction in PPG Acquisition Systems; 6.2.2 Event-Driven ECG Assisted PPG Acquisition; 6.3 Conclusions; References; Index |
| Summary |
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 |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Online resource; title from PDF file page (EBSCO, viewed January 10, 2019) |
| Subject |
Signal processing -- Digital techniques -- Equipment and supplies.
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TECHNOLOGY & ENGINEERING -- Mechanical.
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Signal processing -- Digital techniques -- Equipment and supplies
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| Form |
Electronic book
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| Author |
Hoof, Chris van, author.
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Verhelst, Marian, author.
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| ISBN |
9783030058708 |
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3030058700 |
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