A Hardware-Software System for Accurate Segmentation of Phonocardiogram Signal

Background

Phonocardiogram (PCG) signal provides valuable information for diagnosing heart diseases. However, its applications in quantitative analyses of heart function are limited because the interpretation of this signal is difficult. A key step in quantitative PCG is the identification of the first and second sounds (S1 and S2) in this signal.

Objective

This study aims to develop a hardware-software system for synchronized acquisition of two signals electrocardiogram (ECG) and PCG and to segment the recorded PCG signal via the information provided in the acquired ECG signal.

Material and Methods

In this analytical study, we developed a hardware-software system for real-time identification of the first and second heart sounds in the PCG signal. A portable device to capture synchronized ECG and PCG signals was developed. Wavelet de-noising technique was used to remove noise from the signal. Finally, by fusing the information provided by the ECG signal (R-peaks and T-end) into a hidden Markov model (HMM), the first and second heart sounds were identified in the PCG signal.

Results

ECG and PCG signals from 15 healthy adults were acquired and analyzed using the developed system. The average accuracy of the system in correctly detecting the heart sounds was 95.6% for S1 and 93.4% for S2.

Conclusion

The presented system is cost-effective, user-friendly, and accurate in identifying S1 and S2 in PCG signals. Therefore, it might be effective in quantitative PCG and diagnosing heart diseases.

DETERMINING THE RISK OF CARDIOVASCULAR DISEASE IN PATIENTS DIAGNOSED WITH SCHIZOPHRENIA AND BIPOLAR AFFECTIVE DISORDER

<AbstractText Label="BACKGROUND">In Schizophrenia (SCZ) and Bipolar Affective Disorder (BAD) patients using the Framingham Heart Risk Scoring (FHRS), we aimed to investigate the possible cardiac arrhythmia risk by calculating electrocardiogram (ECG) parameters (QT, QTc, Tpe, and TPE/QTc ratios), which are ventricular repolarization markers.</AbstractText><AbstractText Label="SUBJECTS AND METHODS">Subjects and methods: A total of 140 BAD and 253 SCZ patients were included in the study. Age, blood test results (fasting blood glucose, LDL-HDL-TC levels, hemogram values), blood pressure and heart rate, smoking status, antihypertensive drug use, and FHRS were calculated from the patient files, and sociodemographic information was recorded. In addition, ECG calculations were performed, and QT, QTc, TPe, TPe/QTc ratios and heart rate were measured.</AbstractText><AbstractText Label="RESULTS">When we evaluated the cardiac risk indexes of SCZ and BAD patients, we detected that FHRS was higher in smokers, female patients, and those with other medical diseases such as diabetes mellitus (DM) (p<0.05). In addition, we found that QTc rates, markers of ventricular repolarization, were associated with FHRS, the number of antipsychotics used, patient age, disease duration, and the number of hospitalizations. TPe and QT rates were found to increase in parallel with FHRS. In addition, a positive correlation was found between QTc rates in females, patients with DM, and those using additional medical drugs. (p<0.05)</AbstractText><AbstractText Label="CONCLUSIONS">In BAD and SCZ patients, diabetes diagnosis, other medical drug use, a high Framingham heart score, the number of antipsychotics, the disease duration, the patient&apos;s age, and an increased number of hospitalizations may increase the risk of cardiac arrhythmia. Therefore, possible cardiac risk should be considered in patients with chronic drug use, such as BAD and SCZ. Regulating the treatment and follow-up of this group of patients against possible cardiac risks will reduce cardiac mortality and morbidity</AbstractText>.

Non-invasive body surface electrocardiographic imaging for diagnosis of atrial cardiomyopathy

AIMS

Atrial cardiomyopathy (ACM) is associated with new-onset atrial fibrillation, arrhythmia recurrence after pulmonary vein isolation (PVI) and increased risk for stroke. At present, diagnosis of ACM is feasible by endocardial contact mapping of left atrial (LA) low-voltage substrate (LVS) or late gadolinium-enhanced magnetic resonance imaging, but their complexity limits a widespread use. The aim of this study was to assess non-invasive body surface electrocardiographic imaging (ECGI) as a novel clinical tool for diagnosis of ACM compared with endocardial mapping.

METHODS AND RESULTS

Thirty-nine consecutive patients (66 ± 9 years, 85% male) presenting for their first PVI for persistent atrial fibrillation underwent ECGI in sinus rhythm using a 252-electrode-array mapping system. Subsequently, high-density LA voltage and biatrial activation maps (mean 2090 ± 488 sites) were acquired in sinus rhythm prior to PVI. Freedom from arrhythmia recurrence was assessed within 12 months follow-up. Increased duration of total atrial conduction time (TACT) in ECGI was associated with both increased atrial activation time and extent of LA-LVS in endocardial contact mapping (r = 0.77 and r = 0.66, P < 0.0001 respectively). Atrial cardiomyopathy was found in 23 (59%) patients. A TACT value of 148 ms identified ACM with 91.3% sensitivity and 93.7% specificity. Arrhythmia recurrence occurred in 15 (38%) patients during a follow-up of 389 ± 55 days. Freedom from arrhythmia was significantly higher in patients with a TACT <148 ms compared with patients with a TACT ≥148 ms (82.4% vs. 45.5%, P = 0.019).

CONCLUSION

Analysis of TACT in non-invasive ECGI allows diagnosis of patients with ACM, which is associated with a significantly increased risk for arrhythmia recurrence following PVI.