Theoretical basis and software implementation of contour analysis of cardiosignals in real time

Abstract

Presentation of a biomedical signal (in particular, cardiological signal) in tabulated form in PC memory is the first and often most important stage of its automatic analysis. The simplest form of such presentation is sampiing of a signal at a constant step. There are also more sophisticated methods of sampling. The goal of such sampling is to compress the data so that all important information is retained in a minimum volume of information.Methods of transformation of ECG developed in 1959 independently by Pipberger and Kaseres have received wide acceptance. These methods are based on automatic determination of coordinates of separate ECG waves and measurement of their amplitude and time parameters. This approach, which has now become classical, has gained such wide acceptance because it imitates the methods used by skilled physicians. During the evolution of this approach, the method of transformation of an ECG into a cardiointervalogram was developed. A eardiointervalogram is a time series made up of durations of successive cardiocyctes. Studies of cardiac rhythm later became an independent branch of medical science.The two fundamental approaches on which the first stage of automatic analysis of cardiological information is based were developed and tested for the purpose of ECG processing. This was mainly due to specific properties of ECG signal which make it the most feasible of all physiological signals for automatic analysis. Also, ECG provides very valuable diagnostic information.The goal of this work was to describe an algorithm of partial or complete morphological analysis of car- 27 formation (LST) to be performed. It allows diagnostically valuable elements of cardiosignaI within a narrow frequency band to be selected and noise to be eliminated. The problem of morphological analysis can be reduced to determination of coordinates of local extremums of the transformed curve. The algorithm should determine the coordinates over the entire frequency range.Consider differences of order i of the following type:where {X,} is the series of discrete values of the signal; {Y,} is the series of values of differences of order i; V is the differential operator with a shift back; K, is the shift (decimation) coefficient; i is the order of the difference. Equation (2) is expanded as follows:-i

Synchronous automated analysis of spirogram and cardiointervalogram

“…The LST procedure provides morphological analysis of cardiosignals in realtime mode [1]. The following parameters should be specified: series of discrete values of the initial signal {X,}; sampling interval Tq; the order of difference i; displacement coefficient K~; linear filtering coefficient l.…”