000			03865nam a22004215i 4500
710	2		_aSpringerLink (Online service) _9106996
999			_c110332 _d110332
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005			20230102113415.0
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008			190102s2019 gw a o |||| 0|eng d
020			_a9783030058708
024	7		_a10.1007/978-3-030-05870-8 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aTK5102.9 _b2019 EB
100	1		_aPamula, Venkata Rajesh _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9670402
245	1	0	_aAnalog-and-Algorithm-Assisted Ultra-low Power Biosignal Acquisition Systems _cby Venkata Rajesh Pamula, Chris Van Hoof, Marian Verhelst.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019.
300			_a1 recurso en línea (XXIII, 114 páginas) _b82 ilustraciones, 60 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aAnalog Circuits and Signal Processing _x1872-082X
490	0		_aEngineering (Springer-11647)
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	3		_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		7	_2embne _aProceso de señales _9150608
700	1		_aVan Hoof, Chris. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aVerhelst, Marian. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783030058692
776	0	8	_iPrinted edition: _z9783030058715
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-05870-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aPrimersemestre_2019_Engineering
998			_aSI _cm _dz _feng _ggw _h0 _b09/2019 _ejf _zSI