Comparison of computer ST criteria for diagnosis of severe coronary artery disease.

To determine which computer ST criteria are superior for predicting patterns and severity of coronary artery disease during exercise testing, 230 male veterans were studied who had both coronary angiography and a treadmill exercise test. Significant (p < or = 0.05) differences in computer-scored ST criteria were observed among patients with progressively increasing disease severity. Three-vessel/left main disease produced responses significantly different from 1- and 2-vessel disease or those with < 70% occlusion. Discriminant function analysis revealed that horizontal or downsloping ST depression measured at the J junction during exercise or recovery, or both, was the most powerful predictor of severe disease. With use of a cut point of 0.075 mV ST depression, horizontal or downsloping ST depression alone yielded a sensitivity of 50% (95% confidence interval = 35 to 65%) and specificity of 71% for prediction of severe disease; the only additional variable that added significantly to the prediction was exercise capacity, which improved sensitivity to 57% (95% confidence interval = 41 to 72%) with no change in specificity. Measurements of ST amplitude at the J junction and at 60 ms after the J point without slope considered and other scores, including the Treadmill Exercise Score, ST Integral, and ST/heart rate index, had a lower but comparable predictive accuracy when compared with horizontal or downsloping ST depression. Prediction of coronary artery disease severity can be achieved using computerized electrocardiographic measurements obtained during exercise testing. The most powerful marker for severe coronary artery disease is the amount of horizontal or downsloping ST-segment depression during exercise or recovery, or both, a measurement that stimulates the traditional visual approach.

A real-time data-logger system using an optical disk WORM for archiving continuous 12-lead ECG data during exercise testing.

An exercise ECG analysis program was developed over 15 years on a number of mainframes, minicomputers and, most recently, microcomputer-based systems. It has been rehosted into both Motorola MC68000 and Intel 80286 microprocessor-based development systems and is currently used with a removable 200 Mbyte optical disk (Write-Once-Read-Many, WORM) based data-logger system that can record and store all 12 leads simultaneously and continuously for an entire exercise test (up to 38 minutes). Data is acquired with 12-bit A/D resolution at 500 samples/sec. All ECG data and patient information are archived on the optical disk for later off-line recall and analysis on a PC or real-time replay through a D/A converter. Recorded ECG signals are at patient levels so they can be replayed through the patient cable box on any commercial system. Current development includes both simultaneous on-line processing and storage of 12-lead ECG data and off-line processing and development performed on the long-term, continuous ECG data being archived on optical disk. Patient medical histories and clinical information are separately entered into an applications database, where ECG measures and test results are later included. This new optical disk based exercise ECG database contains more than 600 complete exercise tests and is projected to increase to nearly 3,000 within 2 years.

Problems and limitations of ECG baseline estimation and removal using a cubic spline technique during exercise ECG testing: recommendations for proper implementation.

One common variety of exercise-induced artifact is baseline wander resulting from movement, respiration, and poor electrode contact. Although filters can be designed to remove much of this baseline variation, they will distort the low-frequency components of the ECG complex, such as the TP-segment, the PR-segment, and, most problematically, the ST-segment. The ST-segment is the most diagnostically relevant measure of the ECG taken during exercise. While linear baseline interpolation and removal may be adequate at lower heart rates, they also will introduce significant distortions. This is particularly evident when excessive nonlinear wander is present, as seen at higher heart rates and respiration rates. A nonlinear, third-order, polynomial estimator of baseline wander, known as the cubic spline, has been used for nearly 15 years. It is a very robust technique applied to exercise ECG recordings. Since the cubic spline is not a filter and use an a priori knowledge of the shape of the ECG signal, it estimates the true baseline and avoids distortion better. The more common implementations of this technique use relatively short ECG recordings. With the advent of increasing power in computerized ECG systems, the implementation of the cubic spline algorithm for removing baseline wander in continuous, longer-duration ECG records and in real-time processing is being attempted. However, the correct application of the cubic spline to continuous recordings is not straightforward and involves a number of previously unforeseen difficulties. The accuracy and resolution of both floating point and integer operations is critical during long-term application of the cubic spline function.(ABSTRACT TRUNCATED AT 250 WORDS)

Detection and measurement of the P-wave and T-wave during exercise testing using combined heuristic and statistical methods.

Accurate detection and measurement of the P-wave and T-wave components of the ECG complex have been difficult and often avoided in computerized ECG analysis. This is particularly so during exercise testing where T-P fusion occurs during higher heart-rates. By combining advanced pattern-recognition techniques, statistical measurements and empirically based heuristic decision-making logic, our ECG Analysis program has been able to reliably detect, measure and track these components during exercise testing to a degree surpassing visual detection by highly experienced readers. Complete analysis of each consecutive record gathered during the exercise test is performed and a data-base of measurements and parameters is created for reference comparison of previous results at each analysis step to current measurements. Thus, evaluation of each current record for appropriate and accurate analysis is based on an expert system approach which is constantly updated and can adjust itself to individual ECG morphology as the test progresses. Preliminary attempts are also being made to separate, extract and normalize the P-wave and T-wave during fusion for better understanding and comparison of changes which occur at high heart-rates. Theoretical and clinical reasons related to the detection and measurements of the P-wave and T-wave during exercise testing are also discussed.

Sensory interaction, brain activity, and reading ability in young adults.

Forty-one Navy recruits were divided into two groups (HIGH versus LOW) based on reading ability. Eight channels of visual (VERP), auditory (AERP), and bimodal (BERP) event related brain potential data were analyzed in order to assess the relationship between sensory interaction and reading ability. The HIGH group showed greater VERP amplitude than did the LOW group, while the lOW group showed greater AERP and BERP amplitude than did the HIGH group. Discriminant analysis provided separation of the two groups when VERP and AERP variables were used but not BERP variables. Sensory modality interaction was assessed through the derived expression. Greatest group differences were found late in the waveform (between 300 and 400 msec) suggesting that sensory interaction also affects higher-order cognitive functioning. Distractability may partially account for the ERP differences found for the two reading groups.