Abstract :
Currently, the most widely used tool for non-invasive diagnosis of ischemic heart disease (IHD) is exercise electrocardiography. The sensitivity of this methodology is known to be limited, generally considered to be between 50% and 70%, and in some studies has been reported to be even lower. In standard ECG analysis, performed in the 0.05-100Hz frequency range, detection of ischemia from the ECG is based on identifying changes in the repolarization phase of the cardiac cycle, manifested in changes of the ST segment. However, ischemia can also induce changes to the depolarization phase, which can be detected by examining the high-frequency content of the mid-QRS complex. A significant body of evidence accumulated in recent years indicates that higher frequency ECG components contain valuable information for the detection of IHD. BSP has developed the HyperQtrade technology, which allows the extraction and analysis of the high-frequency components of the ECG. The physical acquisition of the HyperQtrade signal does not require any deviation from the standard ECG recording process. The ECG is amplified and digitized at a sampling rate of 1000 samples/sec. Since the signal-to-noise ratio of the high frequency ECG components is markedly inferior to that of standard ECG, a multifaceted process for extracting the HyperQtrade signal is was developed, including identification of the QRS complexes, rejection of corrupted signals, several alignment procedures, and optimization of the balance between the noise reduction procedure and the integrity of the HyperQtrade signal. HyperQtrade-based diagnostics involve the identification and isolation of phenomena directly related to the ischemic condition of the heart. The signal´s features indicating ischemic condition include the energy content of the signal, its amplitude, and the change in its morphology. Recent clinical studies with the HyperQtrade System that compared its performance with standard ECG interpretation in stress te- - sting indicate that the HyperQtrade methodology provides marked improvement in accuracy of IHD diagnosis over conventional ECG.
Keywords :
diseases; electrocardiography; medical signal detection; patient diagnosis; signal sampling; ECG analysis; ECG recording process; HyperQ signal extraction; depolarization phase; exercise electrocardiography; frequency 0.05 Hz to 100 Hz; multifaceted process; myocardial ischemia heart disease detection; noninvasive diagnosis; sampling rate; signal-to-noise ratio; Cardiac disease; Data mining; Electrocardiography; Ischemic pain; Myocardium; Performance analysis; Phase detection; Phase frequency detector; Signal processing; Signal sampling; Ischemia; signal averaged ECG; stress testing;