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SummaryBackground and hypothesis: Genetic influence on development of athlete's heart is uncertain. This study investigated whether angiotensin-converting enzyme (ACE) gene polymorphism influenced development of athlete's heart.Methods: Forty-three participants in a 100-km ultramarathon were classified on the basis of ACE gene polymorphism into a deletion group (n = 26) and an insertion group (n = 17). Echocardiograms were recorded to determine left ventricular end-diastolic and end-systolic diameters, interventricular septal thickness, left ventricular posterior wall thickness, left ventricular mass, and ejection fraction.Results: Left ventricular end-diastolic diameter (65.5 k 4.0 mm) and left ventricular mass (369.5 k 73.9 g) were significantly larger in the subjects with deletion than in those with insertion (57.4 f 4.2 mm, 306.5 k 93.7 g). However, no significant differences in the other parameters were noted.Conclusions: In long-distance runners, ACE gene polymorphism of the D/D and DA genotypes has a stronger influence

continuation point was corrected using Hanning window. It was necessary to force the signal to zero at the beginning and end of the time series to reduce the effect of leakage. Hanning window is a smoothing window, which has excellent frequency and amplitude resolution. The data processed in this manner underwent frequency analysis with the FFT computation routine. Overlap processing can be used to provide high resolution in both the frequency and time axes. We processed the data of 2 ms of the preceding segment simultaneously. These segments were calculated continuously with the FFT calculation for 5 ms at 512 points (Fig 2). The processing result was displayed in 3 dimensions: the time axis (ms), frequency axis (Hz) and strength axis ( V). Subjects and MeasurementTen healthy male volunteers (mean age, 27±1.2 years), having no abnormality in their ECG, were chosen. We used f the techniques for measuring the minute electric potential of an electrocardiogram (ECG), the time domain method is usually used because it can get a high signal to noise ratio (S/N ratio) by signal averaging. [1][2][3] However, it is difficult to evaluate the highfrequency electrical potential within the QRS complex by this method, although it is excellent for detecting the late electric potential that occurs at the end of the QRS complex. Moreover, a disadvantage of this method is that the high-frequency component decreases remarkably when the number of averagings increases due to the unstable trigger position. Although the frequency domain method was considered useful for the analysis of the structure inside the QRS complex it could not detect the change in minute electric potential because it analyzes the whole QRS complex at one time. 4-9 Therefore, short-time First Fourier Transforms (SFFT), which improves the frequency resolution by high-frequency sampling, was used to analyze the ECG of healthy individuals and we then evaluated its usefulness in detecting the change in minute electric potential. Methods PrincipleThe low-frequency-component-containing ECG was removed with a high-pass filter (Fig 1). Of the data in a segment of 160 ms, including the QRS complex, the dis- To detect the minute electric potential inside the QRS complex, a new frequency domain method was designed using short-time First Fourier Transforms (SFFT) and high-frequency sampling (oversampling). SFFT improved the frequency resolution by oversampling that was applied to this analysis. The electric potential data of 15,000 points received weighted, running average processing and was subtracted from the original waveform to reduce the low-frequency component. The data in a segment of 160 ms, including QRS, was processed by frequency analysis with the SFFT computation routine. The ECG of healthy individuals was analyzed by this method and its usefulness evaluated. The processing waves of the X-axis, Y-axis, and Z-axis of a representative normal subject were formed into 3 groups of peak electric potential. SFFT enabled the detection of the structure inside the QRS com...

Holter monitoring is widely used for the detection of arrhythmia and ischemic episodes. Traditionally, analog amplitude-modulated Holter devices have been used for detecting arrhythmia, but they produce signal distortion due to contour effects and phase distortion caused by the tape recorders. A digital Holter device without these disadvantages has been developed and can reproduce clinically accurate electrocardiographic waveforms useful for assessment of arrhythmia and ST segments. However, their reliability is questionable when detecting pacing pulses in pacemaker patients. Because electrocardiographic signals are digitized based on sampling rate, pacing pulses are occasionally missed. Therefore, the FM-300 was developed, a new device for detecting pacing pulses on digital recordings that has both digital and analog circuits in one system and indicates pacing pulse timing with arrows. This device can automatically detect and recognize pacing pulses from various artifacts and pacing modalities, making it easy to identify pacing pulses on digitally recorded electrocardiograms. The FM-300 is useful in the diagnosis and assessment of pacemaker function and has improved the reliability of pulse detection in digital Holter monitoring.

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