Segmented beat modulation method for electrocardiogram estimation from noisy recordings.

Clinical utility of an electrocardiogram (ECG) affected by too high levels of noise such as baseline wanders, electrode motion artifacts, muscular artifacts and power-line interference may be jeopardized if not opportunely processed. Template-based techniques have been proposed for ECG estimation from noisy recordings, but usually they do not reproduce physiological ECG variability, which, however, provides clinically useful information on the patient's health. Thus, this study proposes the Segmented-Beat Modulation Method (SBMM) as a new template-based filtering procedure able to reproduce ECG variability, and assesses SBMM robustness to the aforementioned noises in comparison to a standard template method (STM). SBMM performs a unique ECG segmentation into QRS segment and TUP segment, and successively modulates/demodulates (by stretching or compressing) the former segments in order to adaptively adjust each estimated beat to its original morphology and duration. Consequently, SBMM estimates ECG with significantly lower estimation errors than STM when applied to recordings affected by various levels of the considered noises (SBMM: 176-232µV and 79-499µV; STM: 215-496µV and 93-1056µV, for QRS and TUP segments, respectively). Thus, SBMM is able to reproduce ECG variability and is more robust to noise than STM.

Predictive Power of f99 Repolarization Index for the Occurrence of Ventricular Arrhythmias.

BACKGROUND: Defects of cardiac repolarization, noninvasively identifiable by analyzing the electrocardiographic (ECG) ST segment and T wave, are among the major causes of sudden cardiac death. Still, no repolarization-based index has so far shown sufficient sensitivity and specificity to justify preventive treatments. Thus, the aim of this work was to evaluate the predictive power of our recently proposed f99 index for the occurrence of ventricular arrhythmias. METHODS: Our study populations included 170 patients with implanted cardiac defibrillator (ICD), 44 of which developed ventricular tachycardia and/or fibrillation during the 4-year follow-up (ICD_Cases) and 126 did not (ICD_Controls). The f99 index, defined as the frequency at which the repolarization normalized cumulative energy reaches 99%, was computed in each of the 15 (I to III, aVl, aVr, aVf, V1 -V6 , X, Y, Z) available ECG leads independently, and then maximized over the 6 precordial leads (f99_MaxV1 -V6 ), 12 standard leads (f99_Max12STD) and three orthogonal leads (f99_MaxXYZ) to avoid dispersion-related issues. Each index predictive power was quantified as the area under the receiving operating characteristic curve (AUC). RESULTS: Median f99_MaxV1 -V6 , f99_Max12STD and f99_MaxXYZ values were significantly higher in the ICD_Cases than in the ICD_Controls (48 Hz vs. 35 Hz, P<0.05; 51 Hz vs. 43 Hz, P<0.05; 45 Hz vs. 31 Hz, P<10(-3) ; respectively), indicating a more fragmented repolarization in the former group. The AUC values were 0.62, 0.63 and 0.68, respectively. CONCLUSIONS: The f99 represents a promising risk index for the occurrence of ventricular arrhythmias, especially when maximized over the three orthogonal leads.

Noninvasive fetal electrocardiography: an overview of the signal electrophysiological meaning, recording procedures, and processing techniques.

BACKGROUND: Noninvasive fetal electrocardiography (fECG), obtained positioning electrodes on the maternal abdomen, is important in safeguarding the life and the health of the unborn child. This study aims to provide a review of the state of the art of fECG, and includes a description of the parameters useful for fetus clinical evaluation; of the fECG recording procedures; and of the techniques to extract the fECG signal from the abdominal recordings. METHODS: The fetus clinical status is inferred by analyzing growth parameters, supraventricular arrhythmias, ST-segment variability, and fetal-movement parameters from the fECG signal. This can be extracted from an abdominal recording obtained using one of the following two electrode-types configurations: pure-abdominal and mixed. Differently from the former, the latter also provides pure maternal ECG tracings. From a mathematical point of view, the abdominal recording is a summation of three signal components: the fECG signal (i.e., the signal of interest to be extracted), the abdominal maternal ECG (amECG), and the noise. Automatic extraction of fECG includes noise removal by abdominal signal prefiltration (0.5-45 Hz bandpass filter) and amECG cancellation. CONCLUSIONS: Differences among methods rely on different techniques used to extract fECG. If pure abdominal electrode configurations are used, fECG is extracted directly from the abdominal recording using independent component analysis or template subtraction. Eventually, if mixed electrode configurations are used, the fECG can be extracted using the adaptive filtering fed with the maternal ECG recorded by the electrodes located in the woman thorax or shoulder.

Abnormal repolarization in the acute myocardial infarction patients: a frequency-based characterization.

Despite ST elevation having poor sensitivity for acute myocardial infarction (AMI), it remains the main electrocardiographic (ECG) repolarization index for AMI diagnosis. Aim of the present study was to propose a new f99 index, defined as the frequency at which the repolarization normalized cumulative energy reaches 99%, for ECG AMI discrimination from health with good sensitivity and good specificity. Evaluation of such f99 index was performed on 12-standard-lead (I, II, III, aV1, aVr, aVf, V1 to V6) ECG recordings of 47 healthy controls and 108 acute myocardial infarction (AMI) patients. Repolarization dispersion caused f99 distributions to be significantly lead dependent. In most leads (leads I, II, aVl, aVr, V2-V6), f99 median value was lower in the healthy controls (10-17 Hz) than in the AMI patients (12-38 Hz) indicating higher frequency components (i.e. a more fragmented repolarization) in the latter population. AMI patients from healthy controls discrimination by f99, evaluated in terms of sensitivity (Se) and specificity (Sp), was also lead dependent. Single-lead analysis indicated leads I (Se=80%, Sp=77%) and aVl (Se=84%, Sp=74%) as optimal. Instead, lead-system analysis, performed to overcome dispersion issues, provided the best results when averaging over the 6 precordial leads (Se= 81% and Sp=74%). In conclusion, our new f99 index appears as a promising tool for non-invasively and reliably discriminate AMI patients from healthy subjects.

Use of the dominant T wave to enhance reliability of T-wave offset identification.

T-wave offset (Toff) identification may be jeopardized by the presence of a significant inter-method (IMV) and inter-lead (ILV) Toff variability. Thus, the aim of the present study was to investigate if the dominant T wave (DTW) may be used to enhance Toff-identification reliability. DTWs and 15-lead ECG T waves of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were analyzed for Toff identification using Zhang et al.'s (M1) and Daskalov and Christov's (M2) methods. Results indicate that IMV is significantly reduced when identifying Toff from the DTW rather than from single ECG leads in both populations (CHS: 5ms vs. 5-15ms; AMIP: 10ms vs. 10-20ms). Moreover, when analyzing ILV, Toff was found to be equivalent (correlation=0.71-0.98; P<10(-14)) to the median Toff among leads, but required only one identification instead of 15. Thus, the DTW can be used to enhance Toff-identification reliability.