Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT00661934 |
| Other study ID # |
HSR-R-01 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
N/A
|
| First received |
April 17, 2008 |
| Last updated |
July 30, 2008 |
| Start date |
May 2008 |
| Est. completion date |
May 2009 |
Study information
| Verified date |
July 2008 |
| Source |
Hillel Yaffe Medical Center |
| Contact |
Simcha Meisel, MD |
| Phone |
0523260931 |
| Email |
meisel[@]hy.health.gov.il |
| Is FDA regulated |
No |
| Health authority |
Israel: Ethics Commission |
| Study type |
Observational
|
Clinical Trial Summary
The study goal is to investigate the effect of dialysis/medicinal treatment on cardiac
function and heart sounds by recording heart signals from the chest wall.
Description:
The mechanical functionality of the cardiovascular system is governed by a complex interplay
between pressure gradients, determined by the contraction force of the myocardial cells, the
dynamics of blood flow and the compliance of cardiac chambers and blood vessels. These
mechanical processes produce vibrations and acoustic signals that can be recorded over the
chest wall. Vibro-acoustic heart signals, including heart sounds (phonocardiogram), apical
pulse (apexcardiogram) and arterial pulse (e.g. carotid pulse) carry valuable clinical
information, but their use has been mostly limited to qualitative assessment by manual
methods [1] (Figure 1).
The primary research hypothesis of this work is that clinical information regarding the
mechanical functionality of the cardiovascular system can be automatically extracted from
the vibro-acoustic heart signals by combining medical algorithms with digital signal
processing techniques and computational learning algorithms.
The utilization of vibro-acoustic signals in clinical diagnosis and monitoring, by means of
computerized devices, has been overlooked for many years due to the introduction of more
sophisticated imaging techniques such as echocardiography, cardiac CT and cardiac MRI.
However, these valuable techniques require complex and expensive equipment, as well as
expert operators and interpreters. In particular, these imaging techniques can not be used
continuously or outside of the hospital environment. Recent advancements in sensor
technology, wireless communication and miniaturization of high-performance computing devices
enable to re-approach the analysis of mechanical heart signals using a broad
interdisciplinary view.
The research methodology for achieving the goal of the trial will be as follows:
1. Vibro-acoustic heart signals including phonocardiogram, apexcardiogram and carotid
pulse will be recorded from subjects undergoing dialysis/medicinal Treatment.
2. The correlation between the progress of the dialysis/medicinal treatment process and
the changes in the temporal and morphological characteristics of the vibro-acoustic
signals will be investigated.
3. Signal processing algorithms will be used to automatically analyze the vibro-acoustic
signals.
The recorded signals will be saved digitally to the hard-disk of the recording system, along
with the measured reference parameters. Signal processing methods [2][3] will be used to
segment the signals into distinct components and extract temporal and morphological
features. Statistical linear regression will be used to identify significant correlations
between features of the vibro-acoustic signals and the reference parameters. Computational
learning algorithms will be used to explore non-linear relations and to evaluate the
potential of estimating hemodynamic indexes from the vibro-acoustic signals.
This study is intended to evaluate novel methods for non-invasive estimation of cardiac
indexes that reflect the mechanical functionality of the heart. Modern digital signal
processing techniques and efficient computational learning algorithms can be combined to
attain automatic real-time processing of vibro-acoustic signals for continuous monitoring of
cardiac functionality and early detection of cardiac pathologies.
