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Titolo:
Estimation of respiratory parameters via fuzzy clustering
Autore:
Babuska, R; Alic, L; Lourens, MS; Verbraak, AFM; Bogaard, J;
Indirizzi:
Delft Univ Technol, Dept Informat Technol & Syst, Control Engn Lab, NL-2600 GA Delft, Netherlands Delft Univ Technol Delft Netherlands NL-2600 GA 00 GA Delft, Netherlands Erasmus Med Ctr, Dept Pulm & Intens Care Med, NL-3015 GD Rotterdam, Netherlands Erasmus Med Ctr Rotterdam Netherlands NL-3015 GD Rotterdam, Netherlands
Titolo Testata:
ARTIFICIAL INTELLIGENCE IN MEDICINE
fascicolo: 1-3, volume: 21, anno: 2001,
pagine: 91 - 105
SICI:
0933-3657(200101/03)21:1-3<91:EORPVF>2.0.ZU;2-2
Fonte:
ISI
Lingua:
ENG
Soggetto:
OBSTRUCTIVE PULMONARY-DISEASE; AIR-FLOW OBSTRUCTION; VENTILATED PATIENTS; VOLUME CURVES; MECHANICS; IMAGES; PATTERNS; MODEL;
Keywords:
respiratory mechanics; mechanical ventilation; parameter estimation; respiratory resistance and compliance; expiratory time constant; fuzzy clustering; least-squares estimation;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Citazioni:
24
Recensione:
Indirizzi per estratti:
Indirizzo: Babuska, R Delft Univ Technol, Dept Informat Technol & Syst, Control Engn Lab, POB 5031, NL-2600 GA Delft, Netherlands Delft Univ Technol POB 5031 Delft Netherlands NL-2600 GA lands
Citazione:
R. Babuska et al., "Estimation of respiratory parameters via fuzzy clustering", ARTIF INT M, 21(1-3), 2001, pp. 91-105

Abstract

The results of monitoring respiratory parameters estimated from flow-pressure-volume measurements can be used to assess patients' pulmonary condition, to detect poor patient-ventilator interaction and consequently to optimize the ventilator settings. A new method is proposed to obtain detailed information about respiratory parameters without interfering with the expiration. By means of fuzzy clustering, the available data set is partitioned intofuzzy subsets that can be well approximated by linear regression models locally. Parameters of these models are then estimated by least-squares techniques. By analyzing the dependence of these local parameters on the location of the model in the how-volume-pressure space. information on patients' pulmonary condition can be gained. The effectiveness of the proposed approaches is demonstrated by analyzing the dependence of the expiratory time constant on the volume in patients with chronic obstructive pulmonary disease (COPD) and patients without (COPE). (C) 2001 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 05/04/20 alle ore 19:36:12