An example of computer aided decision-making system for recognition of respiration pathology

• Autorzy: Jóźwik A. , Sokołowska B. , Budzińska K.
• Języki publikacji: EN

Abstrakty

EN

A main objective of the work was presentation of a new statistic approach to an analysis of respiration data. The breathing with intact and denervated diaphragm was compared. The respiration process was desciribed by three parameters: breathing frequency, tidal volume, and minute ventilation. Experimental data concerned a group of twelve anaesthetised cats. These data were analysed by a modification of the well-known k nearest neighbour rule (k-NN). It has been adopted from the statistical pattern recognition theory. The three ventilatory parameters were used to recognise whether we deal with the normal or the pathological case. Certain percentage of misclassifications must be taken into account. This misclassification rate is a measure how strong is the dependence between the ventilation parameters and preservation of the diaphragm innervation. The proposed method promises good differentiation of the two compared ways of respiration. It offers nearly five times smaller misclassification rate as compared with the standard k-NN rule.

Słowa kluczowe

EN

pattern recognition; supervised classification; k-NN rules; feature selection; respiration; ventilation; diaphragm

PL

rozpoznawanie obrazów; klasyfikacja nadzorowana; wybór funkcji; oddychanie; wentylacja; przepona

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2001
• Tom: Vol. 2, Part. 1
• Strony: MI41--MI48
• Opis fizyczny: Bibliogr. 7 poz., rys., tab.

Twórcy

autor

Jóźwik A.

• Institute of Biocybernetics & Biomedical Engineering, Polish Academy of Sciences, Trojdena 4, 02-109 Warsaw, Poland
• Technical University of Łódź, Computer Engineering Department, Al. Politechniki 11, 90-924 Łódź

autor

Sokołowska B.

• Medical Research Centre, Department of Neurophysiology, Polish Academy of Sciences, Pawińskiego 5, 02-106 Warszawa

autor

Budzińska K.

• Medical Research Centre, Department of Neurophysiology, Polish Academy of Sciences, Pawińskiego 5, 02-106 Warszawa

Bibliografia

• [1] DEVIJVER, P.A., KITTLER, J., 1982. Pattern Recognition: A Statistical Approach, Prentice Hall Internationa London.
• [2] JÓŹWIK, A., CHMIELEWSKI, L., CUDNY, W., SKŁODOWSKI, M., 1996. A 1-NN Preclassifier for Fuzzy k-NN Rule, Proceedings of 13th International Conference on Pattern Recognition, v. IV, track D., August, pp. 234-238, Vienna.
• [3] MASKREY, M., EVANS, S.E., MESCH, U., ANDERSEN, N.A., SHERREY, J.H., 1992. Phrenicotomy in the rat: acute changes in blood gases, pH and body temperature. Respir. Physiol. 90, 47-54.
• [4] NACHAZEL, J., PALECEK, F., 1992. Hypoventilation after acute phrenicotomy of the urethane anaesthetized rats. Physiol. Res. 41, 375-380.
• [5] ROCCO, P.R.M., FAFFE, D.S., FEIJOO, M., MENEZES, S.L., VASCONCELLOS, F.P., ZIN, W.A., 1997. Effects of uni- and bilateral phrenicotomy on active and passive respiratory mechanics in rats. Respir. Physiol. 110, 9-18.
• [6] SOKOŁOWSKA, B., BUDZIŃSKA, K., JÓŹWIK, A., 1998. The k-NN rule application for the evaluation of the influence of chemical stimuli on the ventilatory parameters before and after interruption of conduction in the phrenic nerves, Proceedings of the IV National Conference, Applications of Mathematics in Biology and Medicine, Zwierzyniec , 129-132.
• [7] SOKOŁOWSKA, B., BUDZIŃSKA, K., POKORSKI M., 1997. Diaphragmatic electromyograms and respiratory pattern after unilateral and bilateral partial denervation of the cat diaphragm, Pneumonologia i Alergologia Polska, 65(7-8), 500-507.