LEADER 04514nam 22006015 450 001 9910337630503321 005 20200705142415.0 010 $a3-030-05870-0 024 7 $a10.1007/978-3-030-05870-8 035 $a(CKB)4100000007389454 035 $a(DE-He213)978-3-030-05870-8 035 $a(MiAaPQ)EBC5628150 035 $a(PPN)233798919 035 $a(EXLCZ)994100000007389454 100 $a20190102d2019 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAnalog-and-Algorithm-Assisted Ultra-low Power Biosignal Acquisition Systems$b[electronic resource] /$fby Venkata Rajesh Pamula, Chris Van Hoof, Marian Verhelst 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XXIII, 114 p. 82 illus., 60 illus. in color.) 225 1 $aAnalog Circuits and Signal Processing,$x1872-082X 311 $a3-030-05869-7 327 $aChapter1: Challenges and Opportunities in Wearable Biomedical Interfaces -- Chapter2: Adaptive Sampling for Ultra-low Power Electrocardiogram (ECG) Readouts -- Chapter3: Introduction to Compressive Sampling (CS) -- Chapter4: Compressed Domain Feature Extraction -- Chapter5: A Low Power Compressive Sampling (CS) Photoplethysmogram (PPG) Read-out With Embedded Feature Extraction -- Chapter6: Conclusions and Future Work. 330 $aThis book discusses the design and implementation aspects of ultra-low power biosignal acquisition platforms that exploit analog-assisted and algorithmic approaches for power savings.The authors describe an approach referred to as ?analog-and-algorithm-assisted? signal processing.This enables significant power consumption reductions by implementing low power biosignal acquisition systems, leveraging analog preprocessing and algorithmic approaches to reduce the data rate very early in the signal processing chain.They demonstrate savings for wearable sensor networks (WSN) and body area networks (BAN), in the sensors? stimulation power consumption, as well in the power consumption of the digital signal processing and the radio link. Two specific implementations, an adaptive sampling electrocardiogram (ECG) acquisition and a compressive sampling (CS) photoplethysmogram (PPG) acquisition system, are demonstrated. First book to present the so called, ?analog-and-algorithm-assisted? approaches for ultra-low power biosignal acquisition and processing platforms; Covers the recent trend of ?beyond Nyquist rate? signal acquisition and processing in detail, including adaptive sampling and compressive sampling paradigms; Includes chapters on compressed domain feature extraction, as well as acquisition of photoplethysmogram, an emerging optical sensing modality, including compressive sampling based PPG readout with embedded feature extraction; Discusses emerging trends in sensor fusion for improving the signal integrity, as well as lowering the power consumption of biosignal acquisition systems. 410 0$aAnalog Circuits and Signal Processing,$x1872-082X 606 $aElectronic circuits 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aBiomedical engineering 606 $aCircuits and Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/T24068 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 615 0$aElectronic circuits. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aBiomedical engineering. 615 14$aCircuits and Systems. 615 24$aSignal, Image and Speech Processing. 615 24$aBiomedical Engineering and Bioengineering. 676 $a621.3815 700 $aPamula$b Venkata Rajesh$4aut$4http://id.loc.gov/vocabulary/relators/aut$01000339 702 $aVan Hoof$b Chris$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aVerhelst$b Marian$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910337630503321 996 $aAnalog-and-Algorithm-Assisted Ultra-low Power Biosignal Acquisition Systems$92296047 997 $aUNINA