A 9-lead Holter monitor using the lead-switching technique (9-lead DCG) and conventional 12-lead electrocardiograph (12-lead ECG) were simultaneously used for recording during treadmill exercise testing (Td-test) in 140 patients with coronary artery disease. Coronary arteriography was performed in 118 of the 140 patients, and the correlation between coronary stenosis and anterior or inferior projection of ST depressions occurring during the Td-test was investigated. Additionally, 10 patients with acute myocardial infarction (AMI) were studied to test ST elevation detection by the 9-lead DCG. The CM5 lead demonstrated ST depressions in 92 of the 109 patients showing ST depressions in one or more leads. High lateral (HL) and/or low lateral leads detected all ST depressions occurring in the I and aVL leads of the 12-lead ECG. Leads CM1, CM2 and CM3 exhibited low sensitivity (0-32%) and high specificity (56-100%), while leads CM4, CM5, and CM6 provided greater sensitivity (66-95%), but less specificity (3-32%) in detecting diseases of the left anterior descending artery, left circumflex artery and/or right coronary artery (RCA). In contrast, the low back (LB) lead demonstrated high sensitivity (88%) and high specificity (86%) in detecting RCA disease. Lead CM3 detected ST elevations in all 6 patients with anterior AMI, while the LB lead did so in all 4 patients with inferior AMI. With a Holter monitor, 4 leads are needed: CM5 like, CM3 like, lateral (such as HL) and inferior (such as LB). The LB lead is useful in detecting inferior ischemia.
Pitch detection is an important and essential technique in speech analysis, synthesis, and so on. There are many methods to extract voice pitch, but it is difficult to perform pitch extraction in real time. This paper describes a simple real-time pitch detection algorithm which directly estimates the interval between peaks of the waveform. This algorithm consists of the following two parts: one is the peak emphasis of voiced signals and the other is the pitch detection. The peak emphasis is obtained by running a DFS (discrete Fourier series) and a window operation. It is important to determine the peaks for the pitch measurement because the pitch period is obtained by estimating the interval between successive peaks representing the pitch period of the voiced signal. The peaks related to pitch are determined using a few simple rules. Since the voiced signal waveform includes several extra complicated peaks, these rules are constructed taking into account the characteristics of the voiced signal. Other peaks, which do not correspond to the pitch period, are rejected by a simple logical judgment. A real-time pitch detection algorithm has been realized using a conventional DSP.
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