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.본 발명은 환자의 심전도 데이터로부터 심장의 여러가지 환경에 대한 대응력 부족이나 그 결과 일어날 수 있는 돌발적 이상사태를 예견하는 방법을 제공하는 것이다. 이를 위하여 본 발명에서는 심전도 데이터 수집부(1)에서 장시간에 걸쳐 수집한 심전도 데이터로부터 각 심박에 나타나는 피크점의 간격(R-R간격)의 시계열 데이터(r0, r1 …)를 그 검출부(3)에서 검출한다
