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001 978-3-030-05870-8
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005 20220801215447.0
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008 190102s2019 sz | s |||| 0|eng d
020 _a9783030058708
_9978-3-030-05870-8
024 7 _a10.1007/978-3-030-05870-8
_2doi
050 4 _aTK7867-7867.5
072 7 _aTJFC
_2bicssc
072 7 _aTEC008010
_2bisacsh
072 7 _aTJFC
_2thema
082 0 4 _a621.3815
_223
100 1 _aPamula, Venkata Rajesh.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_944504
245 1 0 _aAnalog-and-Algorithm-Assisted Ultra-low Power Biosignal Acquisition Systems
_h[electronic resource] /
_cby Venkata Rajesh Pamula, Chris Van Hoof, Marian Verhelst.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXXIII, 114 p. 82 illus., 60 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAnalog Circuits and Signal Processing,
_x2197-1854
505 0 _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.
520 _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.
650 0 _aElectronic circuits.
_919581
650 0 _aSignal processing.
_94052
650 0 _aBiomedical engineering.
_93292
650 1 4 _aElectronic Circuits and Systems.
_944505
650 2 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aBiomedical Engineering and Bioengineering.
_931842
700 1 _aVan Hoof, Chris.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_944506
700 1 _aVerhelst, Marian.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_944507
710 2 _aSpringerLink (Online service)
_944508
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030058692
776 0 8 _iPrinted edition:
_z9783030058715
830 0 _aAnalog Circuits and Signal Processing,
_x2197-1854
_944509
856 4 0 _uhttps://doi.org/10.1007/978-3-030-05870-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c77512
_d77512