James M. Lindauer

Improvements in atrial fibrillation detection for real-time monitoring

Electrocardiographic (ECG) monitoring plays an important role in the management of patients with atrial fibrillation (AF). Automated real-time AF detection algorithm is an integral part of ECG monitoring during AF therapy. Before and after antiarrhythmic drug therapy and surgical procedures require ECG monitoring to ensure the success of AF therapy. This article reports our experience in developing a real-time AF monitoring algorithm and techniques to eliminate false-positive AF alarms. We start by designing an algorithm based on R-R intervals. This algorithm uses a Markov modeling approach to calculate an R-R Markov score. This score reflects the relative likelihood of observing a sequence of R-R intervals in AF episodes versus making the same observation outside AF episodes. Enhancement of the AF algorithm is achieved by adding atrial activity analysis. P-R interval variability and a P wave morphology similarity measure are used in addition to R-R Markov score in classification. A hysteresis counter is applied to eliminate short AF segments to reduce false AF alarms for better suitability in a monitoring environment. A large ambulatory Holter database (n = 633) was used for algorithm development and the publicly available MIT-BIH AF database (n = 23) was used for algorithm validation. This validation database allowed us to compare our algorithm performance with previously published algorithms. Although R-R irregularity is the main characteristic and strongest discriminator of AF rhythm, by adding atrial activity analysis and techniques to eliminate very short AF episodes, we have achieved 92% sensitivity and 97% positive predictive value in detecting AF episodes, and 93% sensitivity and 98% positive predictive value in quantifying AF segment duration.

Philips QT Interval Measurement Algorithms for Diagnostic, Ambulatory, and Patient Monitoring ECG Applications

Background: Commonly used techniques for QT measurement that identify T wave end using amplitude thresholds or the tangent method are sensitive to baseline drift and to variations of terminal T wave shape. Such QT measurement techniques commonly underestimate or overestimate the “true” QT interval.

What is inside the electrocardiograph

The details of digital recording and computer processing of a 12-lead electrocardiogram (ECG) remain a source of confusion for many health care professionals. A better understanding of the design and performance tradeoffs inherent in the electrocardiograph design might lead to better quality in ECG recording and better interpretation in ECG reading. This paper serves as a tutorial from an engineering point of view to those who are new to the field of ECG and to those clinicians who want to gain a better understanding of the engineering tradeoffs involved. The problem arises when the benefit of various electrocardiograph features is widely understood while the cost or the tradeoffs are not equally well understood. An electrocardiograph is divided into 2 main components, the patient module for ECG signal acquisition and the remainder for ECG processing which holds the main processor, fast printer, and display. The low-level ECG signal from the body is amplified and converted to a digital signal for further computer processing. The Electrocardiogram is processed for display by user selectable filters to reduce various artifacts. A high-pass filter is used to attenuate the very low frequency baseline sway or wander. A low-pass filter attenuates the high-frequency muscle artifact and a notch filter attenuates interference from alternating current power. Although the target artifact is reduced in each case, the ECG signal is also distorted slightly by the applied filter. The low-pass filter attenuates high-frequency components of the ECG such as sharp R waves and a high-pass filter can cause ST segment distortion for instance. Good skin preparation and electrode placement reduce artifacts to eliminate the need for common usage of these filters.

Where do derived precordial leads fail

A 12-lead electrocardiogram (ECG) reconstructed from a reduced subset of leads is desired in continued arrhythmia and ST monitoring for less tangled wires and increased patient comfort. However, the impact of reconstructed 12-lead lead ECG on clinical ECG diagnosis has not been studied thoroughly. This study compares the differences between recorded and reconstructed 12-lead diagnostic ECG interpretation with 2 commonly used configurations: reconstruct precordial leads V(2), V(3), V(5), and V(6) from V(1),V(4), or reconstruct V(1), V(3), V(4), and V(6) from V(2),V(5). Limb leads are recorded in both configurations. A total of 1785 ECGs were randomly selected from a large database of 50,000 ECGs consecutively collected from 2 teaching hospitals. ECGs with extreme artifact and paced rhythm were excluded. Manual ECG annotations by 2 cardiologists were categorized and used in testing. The Philips resting 12-lead ECG algorithm was used to generate computer measurements and interpretations for comparison. Results were compared for both arrhythmia and morphology categories with high prevalence interpretations including atrial fibrillation, anterior myocardial infarct, right bundle-branch block, left bundle-branch block, left atrial enlargement, and left ventricular hypertrophy. Sensitivity and specificity were calculated for each reconstruction configuration in these arrhythmia and morphology categories. Compared to recorded 12-leads, the V(2),V(5) lead configuration shows weakness in interpretations where V(1) is important such as atrial arrhythmia, atrial enlargement, and bundle-branch blocks. The V(1),V(4) lead configuration shows a decreased sensitivity in detection of anterior myocardial infarct, left bundle-branch block (LBBB), and left ventricular hypertrophy (LVH). In conclusion, reconstructed precordial leads are not equivalent to recorded leads for clinical ECG diagnoses especially in ECGs presenting rhythm and morphology abnormalities. In addition, significant accuracy reduction in ECG interpretation is not strongly correlated with waveform differences between reconstructed and recorded 12-lead ECGs.

Technical challenges and future directions in lead reconstruction for reduced-lead systems

Reduced-lead electrocardiographic systems are currently a widely accepted medical technology used in a number of applications. They provide increased patient comfort and superior performance in arrhythmia and ST monitoring. These systems have unique and compelling advantages over the traditional multichannel monitoring lead systems. However, the design and development of reduced-lead systems create numerous technical challenges. This article summarizes the major technical challenges commonly encountered in lead reconstruction for reduced-lead systems. We discuss the effects of basis lead and target lead selections, the differences between interpolated vs extrapolated leads, the database dependency of the coefficients, and the approaches in quantitative performance evaluation, and provide a comparison of different lead systems. In conclusion, existing reduced-lead systems differ significantly in regard to trade-offs from the technical, practical, and clinical points of view. Understanding the technical limitations, the strengths, and the trade-offs of these reduced-lead systems will hopefully guide future research.

Limitations on the Re-use of patient specific coefficients for 12-lead ECG reconstruction

Patient specific coefficients for reconstructing missing precordial leads (patient-specific single-use or PSS) show good performance but require a 12-lead ECG to start monitoring. A more convenient approach is either the use of population based coefficients (POP) or patient specific coefficients from an old 12-lead ECG (patient-specific multi-use or PSM). We used a data set of 1493 resting 12-lead ECGs from 224 patients. Waveform comparisons were made between recorded 12-lead and reconstructed cases using RMS difference. Three cases were compared, PSS, PSM and POP. Median RMS reconstruction error in the ST-T region was 16, 46 and 40 muV for lead configuration V1/V4 in the PSS, PSM and POP cases respectively. For the V2/V5 configuration, median ST-T RMS error was 8, 40 and 41 muV. The RMS error for the PSS case was lower and significantly better by paired T-test. The difference between the two more convenient use-models, PSM and POP, was not significant. Population based coefficients are preferred over patient-specific coefficients if the single-use use-model cannot be followed.

A novel heart rate variability index for evaluation of left ventricular function using five-minute electrocardiogram

In this paper, we introduce a new index based on the frequency-domain analysis of heart rate variability, or more precisely, the power spectrum of the instant heart rate signal. This index, called VHFI, is defined as the very high frequency component of the power spectrum normalized to represent its relative value in proportion to the total power minus the very low frequency component. We tested VHFI on patients with known reduced left ventricular function and found that this index has the potential to be a useful tool for quick evaluation of left ventricular function.

Comparison of two automated methods for QT interval measurement

In this paper we compared two methods of automated QT interval measurement on standard ECG databases: the Root-Mean-Square (RMS) lead combining method aimed at QT monitoring and the method of median of lead-by-lead QT interval measurements. We used the PhysioNet PTB (N=548) and CSE measurement (N=125) standard databases. Both have reference QT interval measurements from a group of annotators. The last 10 seconds of each PTB record was downsampled from 1000 sample per second (sps) and an amplitude resolution of 1 muV to 500 sps and 5 muV in order to match the CSE set. PTB records #205 and #557 were excluded due to ventricular paced rhythm and artifact, respectively. Twenty five cases were excluded from the CSE set to match the selection of cases for IEC algorithm testing (IEC 60601-2-51). We processed all records using the Philips resting 12- lead ECG algorithm to generate representative beats for QT interval measurement. The RMS method measures QRS onset and end of Ton an RMS waveform constructed from 9 leads I, II, III and V1-V6. The lead-by-lead method takes the median QT interval across leads. The automated QT intervals by the RMS and lead-by-lead methods were compared to the reference manual QT measurements. The mean difference between the lead-by-lead QT and the reference QT was 1.7plusmn9.7 ms and 12.4plusmn23.0 ms (mean plusmnstandard deviation (SD)) for the CSE and PTB sets respectively. For the RMS method, the mean difference was -2.8plusmn11.1 ms and 10.3plusmn20.9 ms. F-tests indicate that the standard deviation between methods is not significantly different for the CSE set (P=0.18) or the PTB set (P=0.77). The lead-by-lead and RMS methods perform similarly, leading to the conclusion that the choice between them should be based on considerations such as the number of leads available or computational efficiency.

Normal ECG limits for Asian infants and children

Normal ECG limits are age-dependent, particularly in infants and children, and diagnostic ECG criteria are dependent on the availability of normal limits. As part of an ongoing study, we have evaluated selected ECG amplitudes and time intervals in a cohort of 1,166 healthy Chinese infants and children from Shanghai, China. We observe notable increases of QRS and QT intervals with age, a notable trend toward decreased R and increased S amplitudes in V2, and that T wave transition occurs at age 12 and that it occurs slightly earlier for males. We observe no notable gender differences in ECG parameters at age less than 12 years old, but that evolution differences begin to be manifested after age 8 years. The normal ECG limits in Asian infants and children are also compared with available data from North American infants and children

Right precordial leads V4R and V5R in ECG detection of acute ST elevation mi associated with proximal right coronary artery occlusion

ST elevation myocardial infarction (STEMI) in the right ventricle (RV) associated with right coronary artery (RCA) occlusion is known to have high hospital mortality. The hypothesis tested in this study is: right precordial leads V4R and V5R help detect STEMI in the right ventricle. ECGs from 1,970 subjects were collected in Ruijin Hospital (n=1,342), Shanghai, China and Lund University Hospital, Lund (n=565), Sweden. All ECGs were recorded with additional leads on the right precordial location in V4R and V5R. Our results show that the subjects with middle to upper RCA occlusion often show ST elevation in leads V4R and V5R and ST depression in lateral leads I, aVL, V5-V6, and are often undetected as STEMI or AMI in the standard 12-lead ECG. We conclude that adding V4R and V5R to standard ECG recording in assessing patients presenting with acute coronary syndrome is an easy and convenient way to increases the sensitivity of STEMI detection