Detection of cardiovascular risk from a photoplethysmographic signal using a matching pursuit algorithm.

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 th...

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Publicado en:Medical & Biological Engineering & Computing Vol. 54; no. 7; pp. 1111 - 1122
Autores principales: Sommermeyer, Dirk, Zou, Ding, Ficker, Joachim, Randerath, Winfried, Fischer, Christoph, Penzel, Thomas, Sanner, Bernd, Hedner, Jan, Grote, Ludger, Ficker, Joachim H
Formato: research Journal Article
Publicado: Springer Nature Jul2016
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Detection of cardiovascular risk from a photoplethysmographic signal using a matching pursuit algorithm.
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          Sommermeyer, Dirk
          Zou, Ding
          Ficker, Joachim
          Randerath, Winfried
          Fischer, Christoph
          Penzel, Thomas
          Sanner, Bernd
          Hedner, Jan
          Grote, Ludger
          Ficker, Joachim H
        affil: Department of Internal Medicine and Clinical Nutrition, Center for Sleep and Vigilance Disorders, Sahlgrenska Academy, University of Gothenburg, Gothenburg Sweden
      sug:
        subj:
          Plethysmography Methods
          Signal Processing, Computer Assisted
          Sleep Apnea Syndromes Physiopathology
          Algorithms
          Cardiovascular Diseases Diagnosis
          Human
          Adult
          Cardiovascular Diseases Physiopathology
          Heart Rate
          Atherosclerosis Physiopathology
          Female
          Male
          Aged
          Risk Factors
          Cardiovascular System Physiology
          Middle Age
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Adult: 19-44 years
          Aged: 65+ years
          Middle Aged: 45-64 years
          Female
          Male
      ab: 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 pursuit-based feature extraction algorithm was applied for signal decomposition of the overnight photoplethysmographic pulse wave signals obtained by a single-pulse oximeter sensor. The algorithm computes nine parameters (pulse index, SpO2 index, pulse wave amplitude index, respiratory-related 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 1.4 %. Anthropometric data like age and BMI correlated significantly with measures of vascular stiffness and pulse rate variability (PPT and age r = -0.54, p < 0.001, PR and age r = -0.36, p < 0.01). The composite biosignal risk score showed a dose-response relationship with the number of CR factors (p < 0.001) and was further elevated in patients with sleep apnea (AHI ≥ 15n/h; p < 0.001). The developed algorithm extracts meaningful parameters indicative of cardiorespiratory and autonomic nervous system function and dysfunction in patients suspected of SDB.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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