The present invention provides a way to prognosticate some abnormality of the heart condition through analyzing the electrocardiogram of a patient. In R-R interval detection section 3, R-R intervals are detected from the electrocardiogram data collected in the electrocardiogram data collection section 1 to generate a time-series data. In the characteristic quantity calculation section 5, a series of partial sets B(j)'s is generated, where the partial set B(j) consists of n successive elements starting from the j-th element of the time-series data and n is a constant integer smaller than the total number of elements in the time-series data, and a set of the characteristic quantities (y j , x j ) for each partial set B(j) is calculated, where y j is the mean value of all elements in the set B (j) and x j is the mean value of each difference of the first element from each element in the partial set B(j). Then in the diagnostic parameter calculation section 7, three parameters u, v, w are calculated after splitting the (y, x) -plane into lattices, where the isolation number v is the number of said characteristic quantity sets each of which is included in a lattice on (y, x) -plane that does not include any other characteristic quantity set, the overlap number u is the difference subtracted said isolation number v from the total number of said characteristic quantity sets, and the maximum overlap degree w is the maximum number of characteristic quantity sets included in a lattice on said (y, x) -plane. These three parameters are used as the larger of the overlap number u in comparison with the isolation number v and the larger value of the maximum overlap degree w derived from the electrocardiogram of a person are showing less healthy heart condition of the patient.
