No abstract

Objective: Atrial dominant frequency (DF) maps undergoing atrial fibrillation (AF) presented good spatial correlation with those obtained with the non-invasive body surface potential mapping (BSPM). In this study, a robust BSPM-DF calculation method based on wavelet analysis is proposed.Approach: Continuous wavelet transform along 40 scales in the pseudo-frequency range of 3-30 Hz is performed in each BSPM signal using a Gaussian mother wavelet. DFs are estimated from the intervals between the peaks, representing the activation times, in the maximum energy scale. The results are compared with the traditionally widely applied Welch periodogram and the robustness was tested on different protocols: increasing levels of white Gaussian noise, artificial DF harmonics presence and reduction of number of leads. 11 AF simulations and 12 AF patients are considered in the analysis. For each patient, intracardiac electrograms were acquired in 15 locations from both atria. The accuracy of both methods was assessed by calculating the absolute errors of the HDF B SP M with respect to the atrial HDF, either simulated or intracardially measured, and assumed correct if ≤ 1 Hz. The spatial distribution of the errors between torso DFs and atrial HDFs were compared with atria driving mechanisms location. Torso HDF regions, defined as portions of the maps with |DF −HDF B SP M | ≤ 0.5 Hz were identified and the percentage of the torso occupied these regions was compared between methods. Main results:The proposed method allowed a significant improvement on non-invasive estimation of the atria HDF (median relative error of 7.14% vs. 60.00%, p = 0.06), outperforming the Welch approach in correct estimations of atrial HDFs non-invasively for both cases: models (81.82% vs 45.45%) and patients (75.00% vs 66.67%). A low positive BSPM-DF maps correlation was seen between techniques (0.47 for models and 0.63 for patients), highlighting overall differences in DF distributions. The method was more robust to white Gaussian noise and harmonics and presented more consistent results in lead layouts with low spatial resolution (p = 0.99 vs. p = 0.94).Significance: Estimation of atrial HDFs using BSPM is improved by the proposed waveletbased algorithm, helping increase the non-invasive diagnostic ability in AF.

Non-invasive acquisition of the electrical heart activity through high density mapping might allow early diagnosis of heart diseases overcoming the limitations of the traditional ECG method. This study presents a BSPM system (hardware and platform) to allow users to analyze the characteristics of morphology in up to 64 simultaneous body surface potentials (BSPs) including the 12-lead ECG and vectocardiogram (VCG). The signals undergo a preprocessing step followed by the R peak detection using previously validated techniques for heart rate variability studies. In addition, embedded 3D isopotential, 3D isochrone maps and VCG planes allow researchers to investigate the heart's the electrical activity and its patterns under different heart rhythm disorders in clinical practice.

Body surface potential mapping (BSPM) systems allow non-invasive investigation of the spatial-temporal behaviour of cardiac electrical activity. This study aims to present the validation (application) of 62-channel BSPM equipment. 12-lead ECG plus two leads on the back were recorded (21 healthy volunteers) and further segmented for 4 consecutive beats allowing to obtain P, QRS and T peaks and heart activity R-R, PR, QRS, ST and QT segments. The vectorcardiograms (VCG) are extracted from the electrodes placed on the torso (direct measurement -DM) or indirectly by the Inverse Dower, Uijen and Willems methods. 17 instants of time during one heart beat (P-QRS-T) (Figure 2) are used to generate sequential isopotential maps for each healthy volunteer to investigate propagation of highest and lowest potentials presented on each map. The results obtained in healthy volunteers are comparable with results in the literature, suggesting the system can help identifying heart rhythm disorders, in patients.