Abstract: The clinical usefulness of heart rate variability is
limited to the range of Holter monitoring software available. These
software algorithms require a normal sinus rhythm to accurately
acquire heart rate variability (HRV) measures in the frequency
domain. Premature ventricular contractions (PVC) or more
commonly referred to as ectopic beats, frequent in heart failure,
hinder this analysis and introduce ambiguity. This investigation
demonstrates an algorithm to automatically detect ectopic beats by
analyzing discrete wavelet transform coefficients. Two techniques
for filtering and replacing the ectopic beats from the RR signal are
compared. One technique applies wavelet hard thresholding
techniques and another applies linear interpolation to replace ectopic
cycles. The results demonstrate through simulation, and signals
acquired from a 24hr ambulatory recorder, that these techniques can
accurately detect PVC-s and remove the noise and leakage effects
produced by ectopic cycles retaining smooth spectra with the
minimum of error.
Abstract: Waste lubricating oil re-refining adsorption process by
different adsorbent materials was investigated. Adsorbent materials
such as oil adsorbent, egg shale powder, date palm kernel powder,
and acid activated date palm kernel powder were used. The
adsorption process over fixed amount of adsorbent at ambient
conditions was investigated. The adsorption/extraction process was
able to deposit the asphaltenic and metallic contaminants from the
waste oil to lower values. It was found that the date palm kernel
powder with contact time of 4 h was able to give the best conditions
for treating the waste oil. The recovered solvent could be also reused.
It was also found that the activated bentonite gave the best
physical properties followed by the date palm kernel powder.
Abstract: This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.
Abstract: Heart-s electric field can be measured anywhere on
the surface of the body (ECG). When individuals touch, one person-s
ECG signal can be registered in other person-s EEG and elsewhere
on his body. Now, the aim of this study was to test the hypothesis
that physical contact (hand-holding) of two persons changes their
heart rate variability. Subjects were sixteen healthy female (age: 20-
26) which divided into eight sets. In each sets, we had two friends
that they passed intimacy test of J.sternberg. ECG of two subjects
(each set) acquired for 5 minutes before hand-holding (as control
group) and 5 minutes during they held their hands (as experimental
group). Then heart rate variability signals were extracted from
subjects' ECG and analyzed in linear feature space (time and
frequency domain) and nonlinear feature space. Considering the
results, we conclude that physical contact (hand-holding of two
friends) increases parasympathetic activity, as indicate by increase
SD1, SD1/SD2, HF and MF power (p
Abstract: The RR interval series is non-stationary and unevenly
spaced in time. For estimating its power spectral density (PSD) using
traditional techniques like FFT, require resampling at uniform
intervals. The researchers have used different interpolation
techniques as resampling methods. All these resampling methods
introduce the low pass filtering effect in the power spectrum. The
lomb transform is a means of obtaining PSD estimates directly from
irregularly sampled RR interval series, thus avoiding resampling. In
this work, the superiority of Lomb transform method has been
established over FFT based approach, after applying linear and
cubicspline interpolation as resampling methods, in terms of
reproduction of exact frequency locations as well as the relative
magnitudes of each spectral component.
Abstract: Diabetes mellitus (DM) is frequently characterized by
autonomic nervous dysfunction. Analysis of heart rate variability
(HRV) has become a popular noninvasive tool for assessing the
activities of autonomic nervous system (ANS). In this paper, changes
in ANS activity are quantified by means of frequency and time
domain analysis of R-R interval variability. Electrocardiograms
(ECG) of 16 patients suffering from DM and of 16 healthy volunteers
were recorded. Frequency domain analysis of extracted normal to
normal interval (NN interval) data indicates significant difference in
very low frequency (VLF) power, low frequency (LF) power and
high frequency (HF) power, between the DM patients and control
group. Time domain measures, standard deviation of NN interval
(SDNN), root mean square of successive NN interval differences
(RMSSD), successive NN intervals differing more than 50 ms (NN50
Count), percentage value of NN50 count (pNN50), HRV triangular
index and triangular interpolation of NN intervals (TINN) also show
significant difference between the DM patients and control group.
Abstract: The linear methods of heart rate variability analysis
such as non-parametric (e.g. fast Fourier transform analysis) and
parametric methods (e.g. autoregressive modeling) has become an
established non-invasive tool for marking the cardiac health, but their
sensitivity and specificity were found to be lower than expected with
positive predictive value
Abstract: Many recent electrophysiological studies have
revealed the importance of investigating meditation state in order to
achieve an increased understanding of autonomous control of
cardiovascular functions. In this paper, we characterize heart rate
variability (HRV) time series acquired during meditation using
nonlinear dynamical parameters. We have computed minimum
embedding dimension (MED), correlation dimension (CD), largest
Lyapunov exponent (LLE), and nonlinearity scores (NLS) from HRV
time series of eight Chi and four Kundalini meditation practitioners.
The pre-meditation state has been used as a baseline (control) state to
compare the estimated parameters. The chaotic nature of HRV during
both pre-meditation and meditation is confirmed by MED. The
meditation state showed a significant decrease in the value of CD and
increase in the value of LLE of HRV, in comparison with premeditation
state, indicating a less complex and less predictable nature
of HRV. In addition, it was shown that the HRV of meditation state
is having highest NLS than pre-meditation state. The study indicated
highly nonlinear dynamic nature of cardiac states as revealed by
HRV during meditation state, rather considering it as a quiescent
state.
Abstract: A five-class density histogram with an index named cumulative density was proposed to analyze the short-term HRV. 150 subjects participated in the test, falling into three groups with equal numbers -- the healthy young group (Young), the healthy old group (Old), and the group of patients with congestive heart failure (CHF). Results of multiple comparisons showed a significant differences of the cumulative density in the three groups, with values 0.0238 for Young, 0.0406 for Old and 0.0732 for CHF (p