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Dynamic time warping and machine learning for signal quality assessment of pulsatile signals.

Abstract:

In this work, we describe a beat-by-beat method for assessing the clinical utility of pulsatile waveforms, primarily recorded from cardiovascular blood volume or pressure changes, concentrating on the photoplethysmogram (PPG). Physiological blood flow is nonstationary, with pulses changing in height, width and morphology due to changes in heart rate, cardiac output, sensor type and hardware or software pre-processing requirements. Moreover, considerable inter-individual and sensor-location va...

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Publication status:
Published

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Publisher copy:
10.1088/0967-3334/33/9/1491

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Institution:
University of Oxford
Department:
Oxford, MPLS, Engineering Science
Role:
Author
Journal:
Physiological measurement
Volume:
33
Issue:
9
Pages:
1491-1501
Publication date:
2012-09-05
DOI:
EISSN:
1361-6579
ISSN:
0967-3334
URN:
uuid:b80268dd-694e-481e-84d5-39e3da625ee9
Source identifiers:
349815
Local pid:
pubs:349815

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