Linear ECG-lead transformations estimate or derive unrecorded target leads by applying a number of recorded basis leads to a so-called linear ECG-lead transformation matrix. The inverse transform of such a linear ECG-lead transformation performs a transformation in the opposite direction (from the target leads to the basis leads). The pseudo-inverse of a given transformation matrix can be used to perform such an inverse transformation. Linear regression based inverse transformation matrices are, provided that sufficient
training data for their development is available, an alternative to pseudo-inverse matrices. The aim of this research was to compare the estimation performance of pseudo-inverse and linear regression based inverse transformations. This comparison was performed for two example inverse transformations. The performance of the different transformations was assessed using root-meansquared-error (RMSE) values between the QRS-T complexes of recorded and derived leads. Typical mean RMSE values associated with the regression based
approach were found to be approximately two thirds to half of the mean RMSE values achieved by the approach based upon the pseudo-inverse. Provided that sufficient data are available, linear regression should be used for the development of inverse ECG-lead transformation matrices.
Background: Body surface potential mapping (BSPM) provides additional electrophysiological information that can be useful for the detection of cardiac diseases. Moreover, BSPMs are currently utilized in electrocardiographic imaging (ECGI) systems within clinical practice. Missing information due to noisy recordings, poor electrode contact is inevitable. In this study, we present an interpolation method that combines Laplacian minimization and principal component analysis (PCA) techniques for interpolating this missing information. Method: The dataset used consisted of 117 lead BSPMs recorded from 744 subjects (a training set of 384 subjects, and a test set of 360). This dataset is a mixture of normal, old myocardial infarction, and left ventricular hypertrophy subjects. The missing data was simulated by ignoring data recorded from 7 regions: the first region represents three rows of five electrodes on the anterior torso surface (high potential gradient region), and the other six regions were realistic patterns that have been drawn from clinical data and represent the most likely regions of broken electrodes. Three interpolation methods including PCA based interpolation, Laplacian interpolation, and hybrid Laplacian-PCA interpolation methods were used to interpolate the missing data from the remaining electrodes. In the simulated region of missing data, the calculated potentials from each interpolation method were compared with the measured potentials using relative error (RE) and correlation coefficient (CC) over time. In the hybrid Laplacian-PCA interpolation method, the missing data are firstly interpolated using Laplacian interpolation, then the resulting BSPM of 117 potentials was multiplied by the (117 × 117) coefficient matrix calculated using the training set to get the principal components. Out of 117 principal components (PCs), the first 15 PCs were utilized for the second stage of interpolation. The best performance of interpolation was the reason for choosing the first 15 PCs. Results: The differences in the median of relative error (RE) between Laplacian and Hybrid method ranged from 0.01 to 0.35 (p b 0.001), while the differences in the median of correlation between them ranged from 0.0006 to 0.034 (p b 0.001). PCA-interpolation method performed badly especially in some scenarios where the number of missing electrodes was up to 12 or higher causing a high region of missing data. The figures of median of RE for PCAmethod were between 0.05 and 0.6 lower than that for Hybrid method (p b 0.001). However, the median of correlation was between 0.0002 and 0.26 lower than the figure for the Hybrid method (p b 0.001). Conclusion: Comparison between the three methods of interpolation (Laplacian, PCA, Hybrid) in reconstructing missing data in BSPM showed that the Hybrid method was always better than the other methods in all scenarios; whether the number of missed electrodes is high or low, and irrespective of the location of these missed electrodes.
This article investigates the selection of optimal ECG leads for the detection of ST changes more likely to appear in patch systems with closely spaced leads. Method: We analysed body surface potential maps (BSPMs) from 44 subjects undergoing PTCA. BSPMs were recorded at 120 sites and these were expanded to 352 nodes (Dalhousie torso) using Laplacian interpolation. A total of 88 BSPMs were investigated. This included the 44 subjects at baseline and the 44 subjects at peak balloon inflation (PBI). At PBI the subjects had various coronary arteries occluded (14 LAD, 15 LCX, 15 RCA). All possible bipolar leads were calculated for each subject. Leads were ranked based on the maximum ST-segment change between baseline and PBI for each subject. Leads with electrode spacing of more than 100 mm were excluded. The highest ranked lead was chosen as the short spaced lead (SSL) on the anterior torso. Result: The median ST-segment change for the chosen SSL for each vessel was LAD = 134 µV, LCX = 65 µV, RCA = 166 µV. The maximum ST segment change observed for the same lead was LAD = 277 µV, LCX = 166 µV, RCA = 257 µV . For comparison, the highest median observed on the 12-lead ECG for each vessel was LAD = 137 µV (V3), LCX = 130 µV (III), RCA = 196 µV (III).
Hypertension is a silent killer and one-third of its sufferers are unaware of its presence. Tonometric devices, like SphygmoCor, Compilor etc., represent the gold standard in pulse wave velocity (PWV) and augmentation index (AIx) measurements which are limited by their high cost and operational accuracy. Here, we present an alternative technology that is low cost and may be suitable for the ‘wearable’ setting. We undertook the comparisons of arterial waveforms obtained by photoplethysmogram (PPG) and finger ballistocardiogram (BPP) sensors which were then validated against a SphygmoCor tonometric device. Specifically, the agreement analysis of the augmentation, stiffness, reflection, elasticity, ejection elasticity and dicrotic reflection indexes showed that arterial distension waveform sensing using BPP sensor, has precision and accuracy similar to that of a SphygmoCor tonometric device whilst outperforming the volumetric arterial flow sensing using a PPG sensor, in every index. BPP indexes showed the r2 fit of up to 0.95 and Spearman’s rank correlation up to 0.91 when validated against the SphygmoCor tonometer. The estimated individual transfer functions for the BPP sensor, with reference to SphygmoCor, have accuracies of above 85% and 98% for 2 and 4-element windkessel (WK) models, respectively. The findings reported in this work may also be useful for the development of systems that are beneficial in the early and/or routine detection of hypertension.
The magnitude of the spatial ventricular gradient (MSVG) is an attractive parameter in electrocardiogram (ECG)monitoring applications. The MSVG is most commonlyobtained from150 Hz low-pass filtered resting ECGs. However, monitoring applications typically utilize 40 Hz low-pass filtered ECG data. The extend to which the value of the MSVG is affected by the utilization of 40 Hz low-pass monitoring ECG filters over the commonly used 150 Hz low-pass resting ECG filters has not previously been reported. The aim of this research was to quantify the differences between MSVG values computed using 40 Hz low-pass filtered ECG data (MSVG40) and 150 Hz low-pass filtered ECG data (MSVG150). The differences between the MSVG40 and the MSVG150 were quantified as systematic error (mean difference) and random error (span of Bland-Altman 95% limits of agreement) using a study population of 726 subjects. The systematic error was found to be 0.013 mV ms [95% confidence interval: 0.008 mV ms to 0.018 mV ms]. The random error was quantified as 0.282 mV ms [95% confidence interval: 0.266 mV ms to 0.298 mV ms]. Our findings suggest that it is possible to record accurate MSVG values using 40 Hz low-pass filtered ECG data.
We perform a novel comparative analysis between optically and mechanically derived pulse transit time (PTT) that is universally employed technique for cuffless blood pressure (BP) estimation. For data collection two inline photoplethysmogram (PPG) sensors were mounted at the distal and proximal phalanxes of the index finger of each subject and top each PPG sensor fixture a finger ballistocardiogram (BPP) sensors were clamped. The clamped stacking of the BPP sensors over the PPG sensors provided vertical aligned acquisition of the blood flow waveform through the radial artery for both sensors. The analysis of variance (ANOVA) between PTT derived from the BPP and PPG sensors resulted in a statistically significant difference at p<0.05. The PTT derived from the BPP sensors showed higher values, 17.8 milliseconds on average, than the PTT derived from the PPG sensors. Higher accuracy PTT values will improve the estimation of cuffless BP and thus has the potential to revolutionize the technology.
Background: We have previously reported on the potential of patch-based ECG leads to observe changes typical during ischaemia. In this study we aim to assess the utility of patch-based leads in the detection of these changes.
Method: Body surface potential maps (BSPM) from subjects (n=45) undergoing elective percutaneous coronary angioplasty (PTCA) were used. The short spaced lead (SSL), that was previously identified as having the greatest ST-segment change between baseline and peak balloon inflation (PBI), was selected as the basis for a patch based lead system. A feature set of J-point amplitudes for all bipolar leads available within the same 100 mm region were included (n=6). Current 12-lead ECG criteria were applied to 12-lead ECGs for the same subjects to benchmark performance.
Results: The previously identified single SSL achieved sensitivity and specificity of 87% and 71% respectively using a Naive Bayes classifier. Adding other combinations of leads to this did not improve performance significantly. The 12-lead ECG performance was 62/93% (sensitivity/specificity).
Conclusion: This study suggests that short spaced leads can be sensitive to ischaemic ECG changes. However, due to the short distance between leads, they lack the specificity of the 12-lead ECG.