Marcelino Martinez_Sober⁽¹⁾, Juan Guerrero⁽²⁾, Gustavo Camps i Valls⁽³⁾, Antonio J. Serrano López⁽⁴⁾, José David Martín Guerrero^(5)
(1)Universidad de Valencia - Burjassot. Spain
⁽²⁾Departamento de Electrónica. Universidad de Valencia - Burjassot. Spain
⁽³⁾Universitat de València - Burjassot, Valencia. Spain
⁽⁴⁾Dpto. Electrónica. Universidad de Valencia - Burjasot. Spain
⁽⁵⁾G.P.D.S. Departament d´Enginyeria Electrònica. Universitat de València - Burjassot. Spain

	[Cardiolovascular Diseases]	[Health Informatics]

DIGITALISATION AND TIME SERIES OBTENTION

The digitalisation of Holter tapes is carried out by means of a continuous system of acquisition constituted by a system of reading the tapes (Pathfinder), a visualisation application and a data acquisition card PCL711B (fig. 1). By means of our visualisation program the relative acquisition parameters are controlled (gain, channel, sampling rate etc.).

The acquisition time of each tape is 23 minutes (corresponding to 23 hours, because recording speed is 50 times slower than acquisition Holter speed) so the size of each one of them is around 40 MB. The storage of the files in digital support is carried out on CD-ROM units because they are really extensive files.

As regard the series, two periods have been analysed:

-Diurnal period: with a duration of 6 hours starting from 9:00am o´clock

-Nocturnal period: with a duration of 4 hours starting from 1:00am o´clock

FIDUCIAL POINT MARKING PROGRAM

For the marked of pulses and visualisation of the digitised signs was carried out an application in visual environment taking advantage of the versatility of the programming GUI of Matlab 5.0 ⁽²⁾.

I. Process of Marking Pulses.

As we say former, in the studies of time series of 24 hours, 2 periods are distinguished one day and another nocturne that they will be analysed for separate. In the process of having marked a set of waves, an ECG is shown so that the cardiologist locates a tract of the sign of good quality or that in which the patient´s pathology is observed with more clarity. Once selected the period, the program visualises in separated mode each of the pulses and invites the cardiologist to mark the points of interest just as it is shown in fig. 2

The marking process is repeated until marking the desired number of points. When concluding this process of marked for the day period and nocturne is generated a file of marks that will be used later on.

Once located the areas of those that we want to obtain the series RR, we proceed to use a detection program of this series implemented in C language. For the QRS complex localisation we have used the detector included in the MIT-BIH arrhythmia database, developed by W.A.H Engelse and C. Zeelemberg ⁽¹⁾. The algorithm uses a band-pass filter to attenuate the frequencies outside of the band of the QRS complex. To be able to locate the areas of ECG that are possible candidates to QRS, thresholds they are used. These are calculated starting from the file of having obtained in the previous stage and parameters of the acquisition like the resolution of the converter, gain etc.

After the visualisation of some of the obtained series, it has been checked that some recorded files can contain errors due to losses of contact of the electrodes or a bad quality of the signal. In such cases detector produces a high number of false detections.

Under these conditions, whenever the quality of the signal in adjacent tracts allows them, it is preferable to redefine the day and nocturne so-called periods with the purpose of having more appropriate temporary series. Really this doesn´t affect since to the later studies with these periods we are distinguishing among activity/quietness for what the time limit considered is not decisive.

To be able to carry out that indicated previously it is much more convenient not to consider any period type (day/night) and to obtain the temporary series from the registration to the complete, such and like it is shown in fig. 3.

If in the RR time-series picks outside of what we can consider as the mean value of the whole RR series is observed, it indicates us that the detector of QRS is not working properly. This can be due to that the signal is of very bad quality, or simply to that the detector has its limitations. In these cases the signal visualisation with the marks facilitates us the determination of what it is happening. As the visual inspection of all the periods is very tedious, exists a program that analyses the series and determines if the number of false detections is acceptable or not.

The time series are stored in order to be analysed and to obtain parameters of interest in the frequency and time domain that will serve as indicators in the determination of heart pathologies.

Discussion Board

Any Comment to this presentation?

[ABSTRACT] [INTRODUCTION] [DIGITALISATION AND TIME SERIES OBTENTION] [TIME SERIES PROCESSING] [IMAGES] [CONCLUSIONS] [ACKNOWLEDGEMENTS] [BIBLIOGRAPHY] [Discussion Board]

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	[Cardiolovascular Diseases]	[Health Informatics]

Marcelino Martinez_Sober, Juan Guerrero, Gustavo Camps i Valls, Antonio J. Serrano López, José David Martín Guerrero
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Last update: 14/01/00