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 variability exists. Simple template matching methods are therefore inappropriate, and a patient-specific adaptive initialization is therefore required. We introduce dynamic time warping to stretch each beat to match a running template and combine it with several other features related to signal quality, including correlation and the percentage of the beat that appeared to be clipped. The features were then presented to a multi-layer perceptron neural network to learn the relationships between the parameters in the presence of good- and bad-quality pulses. An expert-labeled database of 1055 segments of PPG, each 6 s long, recorded from 104 separate critical care admissions during both normal and verified arrhythmic events, was used to train and test our algorithms. An accuracy of 97.5% on the training set and 95.2% on test set was found. The algorithm could be deployed as a stand-alone signal quality assessment algorithm for vetting the clinical utility of PPG traces or any similar quasi-periodic signal.
journal_name
Physiol Measjournal_title
Physiological measurementauthors
Li Q,Clifford GDdoi
10.1088/0967-3334/33/9/1491subject
Has Abstractpub_date
2012-09-01 00:00:00pages
1491-501issue
9eissn
0967-3334issn
1361-6579journal_volume
33pub_type
杂志文章abstract:OBJECTIVE:Eye-tracking devices have become widely used as clinical assessment tools in a variety of applied-scientific fields to measure saccadic eye movements. With the emergence of multiple static and dynamic devices, the concurrent need for algorithm development and validation is paramount. APPROACH:This review ass...
journal_title:Physiological measurement
pub_type: 杂志文章,评审
doi:10.1088/1361-6579/ab02ab
更新日期:2019-02-26 00:00:00
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journal_title:Physiological measurement
pub_type: 杂志文章
doi:10.1088/0967-3334/35/11/2307
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journal_title:Physiological measurement
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doi:10.1088/0967-3334/30/7/002
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journal_title:Physiological measurement
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journal_title:Physiological measurement
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journal_title:Physiological measurement
pub_type: 临床试验,杂志文章
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更新日期:1994-05-01 00:00:00
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journal_title:Physiological measurement
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更新日期:2014-11-01 00:00:00
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journal_title:Physiological measurement
pub_type: 杂志文章
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更新日期:2017-07-24 00:00:00
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journal_title:Physiological measurement
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journal_title:Physiological measurement
pub_type: 临床试验,杂志文章
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更新日期:2006-03-01 00:00:00
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更新日期:2007-06-01 00:00:00
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journal_title:Physiological measurement
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更新日期:1993-08-01 00:00:00
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journal_title:Physiological measurement
pub_type: 杂志文章
doi:10.1088/0967-3334/37/4/544
更新日期:2016-04-01 00:00:00
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journal_title:Physiological measurement
pub_type: 杂志文章
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更新日期:2014-08-01 00:00:00
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journal_title:Physiological measurement
pub_type: 杂志文章
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pub_type: 历史文章,杂志文章,评审
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journal_title:Physiological measurement
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更新日期:2015-04-01 00:00:00
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更新日期:2005-06-01 00:00:00
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journal_title:Physiological measurement
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journal_title:Physiological measurement
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更新日期:2011-11-01 00:00:00
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journal_title:Physiological measurement
pub_type: 杂志文章
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