Adv. Cardiol., vol. 19, pp. 171-172 (Karger, Basel 1977)

A Method for Running a Computer-Based BCG Data Bank Z. JANUSKEVH':IUS, A. VALUZIS, G. VITENSTEINAS and S. KORSAKASC

Practical use of automated ECG analysis raises the problem and provides the availability of computer-based ECG data storage. Such files would enable one to design more reliable diagnostic algorithms and to tackle, by comparison of old and new ECG, the problem of elucidation of early changes of ECG and early signs of cardiovascular diseases. The key requirements of medical and technical character for an automated ECG file are as follows: compact ECG representation and highaccuracy reconstruction of it; flexibility of the structure, to provide for data actualization; minimal time of search; and convenient representation of the output information. Considering these requirements, we propose an ECG file arranged after the functional diagram in figure 1. To save computer memory, the ECG data should be compressed. A method of adaptive discretization and two-dimensional packing [VALUZHIS et ai., 1972] is used and thereby the overall compression equal to 10.4 is achieved. The probability of a reconstruction error exceding 0.05 mV is 0.00035 (p = 0.99). The record of one 12-lead ECG, 4 sec each lead, takes up, on the average, four kilobytes. Merely the ECG records are commonly stored in computerized files. We reckoned it necessary to enter also the additional description (index records) of the ECG. For this, a special descriptor language was proposed enabling one to have key clinical diagnoses, ECG inferences and patients' identification data in an index record. Studies carried out showed that descriptor distribution follows the Ziepf's hyperbolic law. The expediency of multilist address arrangement of the index record file is demonstrated. The search is based on inquiries that are presented in the language close to the natural one. Index records and ECGs are available at output.

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Institute for Cardiovascular Research, Kaunas

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Fig. 1. A functional diagram of computer-based BCG data storage.

Prof. Z. JANUSKEVICIUS, MD, Institute for Cardiovascular Research, Street, 233007 Kaunas, Lithuanian SSR (USSR)

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