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Title of Journal: Med Biol Eng Comput

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Abbravation: Medical & Biological Engineering & Computing

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Springer Berlin Heidelberg

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DOI

10.1016/0375-9601(78)90440-1

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ISSN

1741-0444

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Detection of cardiovascular risk from a photopleth

Authors: Dirk Sommermeyer Ding Zou Joachim H Ficker Winfried Randerath Christoph Fischer Thomas Penzel Bernd Sanner Jan Hedner Ludger Grote
Publish Date: 2015/11/04
Volume: 54, Issue: 7, Pages: 1111-1121
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Abstract

Cardiovascular disease is the main cause of death in Europe and early detection of increased cardiovascular risk CR is of clinical importance Pulse wave analysis based on pulse oximetry has proven useful for the recognition of increased CR The current study provides a detailed description of the pulse wave analysis technology and its clinical application A novel matching pursuitbased feature extraction algorithm was applied for signal decomposition of the overnight photoplethysmographic pulse wave signals obtained by a singlepulse oximeter sensor The algorithm computes nine parameters pulse index SpO2 index pulse wave amplitude index respiratoryrelated pulse oscillations pulse propagation time periodic and symmetric desaturations time under 90  SpO2 difference between pulse and SpO2 index and arrhythmia The technology was applied in 631 patients referred for a sleep study with suspected sleep apnea The technical failure rate was 14  Anthropometric data like age and BMI correlated significantly with measures of vascular stiffness and pulse rate variability PPT and age r = −054 p  0001 PR and age r = −036 p  001 The composite biosignal risk score showed a dose–response relationship with the number of CR factors p  0001 and was further elevated in patients with sleep apnea AHI ≥ 15n/h p  0001 The developed algorithm extracts meaningful parameters indicative of cardiorespiratory and autonomic nervous system function and dysfunction in patients suspected of SDB

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