Abstract: Noise level has critical effects on the diagnostic
performance of signal-averaged electrocardiogram (SAECG), because
the true starting and end points of QRS complex would be masked by
the residual noise and sensitive to the noise level. Several studies and
commercial machines have used a fixed number of heart beats
(typically between 200 to 600 beats) or set a predefined noise level
(typically between 0.3 to 1.0 μV) in each X, Y and Z lead to perform
SAECG analysis. However different criteria or methods used to
perform SAECG would cause the discrepancies of the noise levels
among study subjects. According to the recommendations of 1991
ESC, AHA and ACC Task Force Consensus Document for the use of
SAECG, the determinations of onset and offset are related closely to
the mean and standard deviation of noise sample. Hence this study
would try to perform SAECG using consistent root-mean-square
(RMS) noise levels among study subjects and analyze the noise level
effects on SAECG. This study would also evaluate the differences
between normal subjects and chronic renal failure (CRF) patients in
the time-domain SAECG parameters.
The study subjects were composed of 50 normal Taiwanese and 20
CRF patients. During the signal-averaged processing, different RMS
noise levels were adjusted to evaluate their effects on three time
domain parameters (1) filtered total QRS duration (fQRSD), (2) RMS
voltage of the last QRS 40 ms (RMS40), and (3) duration of the low
amplitude signals below 40 μV (LAS40). The study results
demonstrated that the reduction of RMS noise level can increase
fQRSD and LAS40 and decrease the RMS40, and can further increase
the differences of fQRSD and RMS40 between normal subjects and
CRF patients. The SAECG may also become abnormal due to the
reduction of RMS noise level. In conclusion, it is essential to establish
diagnostic criteria of SAECG using consistent RMS noise levels for
the reduction of the noise level effects.
Abstract: The processing of the electrocardiogram (ECG) signal consists essentially in the detection of the characteristic points of
signal which are an important tool in the diagnosis of heart diseases. The most suitable are the detection of R waves. In this paper, we
present various mathematical tools used for filtering ECG using digital filtering and Discreet Wavelet Transform (DWT) filtering. In
addition, this paper will include two main R peak detection methods
by applying a windowing process: The first method is based on calculations derived, the second is a time-frequency method based on
Dyadic Wavelet Transform DyWT.
Abstract: The Virtual Reality (VR) is becoming increasingly
important for business, education, and entertainment, therefore VR
technology have been applied for training purposes in the areas of
military, safety training and flying simulators. In particular, the
superior and high reliability VR training system is very important in
immersion. Manipulation training in immersive virtual environments
is difficult partly because users must do without the hap contact with
real objects they rely on in the real world to orient themselves and
their manipulated.
In this paper, we create a convincing questionnaire of immersion
and an experiment to assess the influence of immersion on
performance in VR training system. The Immersion Questionnaire
(IQ) included spatial immersion, Psychological immersion, and
Sensory immersion. We show that users with a training system
complete visual attention and detection of signals. Twenty subjects
were allocated to a factorial design consisting of two different VR
systems (Desktop VR and Projector VR). The results indicated that
different VR representation methods significantly affected the
participants- Immersion dimensions.
Abstract: The multi-agent system for processing Bio-signals
will help the medical practitioners to have a standard examination
procedure stored in web server. Web Servers supporting any standard
Search Engine follow all possible combinations of the search
keywords as an input by the user to a Search Engine. As a result, a
huge number of Web-pages are shown in the Web browser. It also
helps the medical practitioner to interact with the expert in the field
his need in order to make a proper judgment in the diagnosis phase
[3].A web server uses a web server plug in to establish and
maintained the medical practitioner to make a fast analysis. If the
user uses the web server client can get a related data requesting their
search. DB agent, EEG / ECG / EMG agents- user placed with
difficult aspects for updating medical information-s in web server.
Abstract: The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.
Abstract: Monitoring lightning electromagnetic pulses (sferics)
and other terrestrial as well as extraterrestrial transient radiation signals
is of considerable interest for practical and theoretical purposes
in astro- and geophysics as well as meteorology. Managing a continuous
flow of data, automisation of the detection and classification
process is important. Features based on a combination of wavelet and
statistical methods proved efficient for analysis and characterisation
of transients and as input into a radial basis function network that is
trained to discriminate transients from pulse like to wave like.
Abstract: The information revealed by derivatives can help to
better characterize digital near-end crosstalk signatures with the
ultimate goal of identifying the specific aggressor signal.
Unfortunately, derivatives tend to be very sensitive to even low
levels of noise. In this work we approximated the derivatives of both
quiet and noisy digital signals using a wavelet-based technique. The
results are presented for Gaussian digital edges, IBIS Model digital
edges, and digital edges in oscilloscope data captured from an actual
printed circuit board. Tradeoffs between accuracy and noise
immunity are presented. The results show that the wavelet technique
can produce first derivative approximations that are accurate to
within 5% or better, even under noisy conditions. The wavelet
technique can be used to calculate the derivative of a digital signal
edge when conventional methods fail.
Abstract: This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot signal for the new generation of high data rate communication systems. In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. In this paper, we propose to derive an improved algorithm based on the calculation of the mean and the variance of the adjacent pilot signals for a specific distribution of the pilot signals in the OFDM frequency-time grid then calculating of the entire unknown channel coefficients from the equation of the mean and the variance. Simulation results shows that the performance of the OFDM system increase as the length of the channel increase where the accuracy of the estimated channel will be increased using this low complexity algorithm, also the number of the pilot signal needed to be inserted in the OFDM signal will be reduced which lead to increase in the throughput of the signal over the OFDM system in compared with other type of the distribution such as Comb type and Block type channel estimation.
Abstract: The technological concepts such as wireless hospital
and portable cardiac telemetry system require the development of
physiological signal acquisition devices to be easily integrated into
the hospital database. In this paper we present the low cost, portable
wireless ECG acquisition hardware that transmits ECG signals to a
dedicated computer.The front end of the system obtains and
processes incoming signals, which are then transmitted via a
microcontroller and wireless Bluetooth module. A monitoring
purpose Bluetooth based end user application integrated with patient
database management module is developed for the computers. The
system will act as a continuous event recorder, which can be used to
follow up patients who have been resuscitatedfrom cardiac arrest,
ventricular tachycardia but also for diagnostic purposes for patients
with arrhythmia symptoms. In addition, cardiac information can be
saved into the patient-s database of the hospital.
Abstract: The standard investigational method for obstructive
sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG),
which consists of a simultaneous, usually overnight recording of
multiple electro-physiological signals related to sleep and
wakefulness. This is an expensive, encumbering and not a readily
repeated protocol, and therefore there is need for simpler and easily
implemented screening and detection techniques. Identification of
apnea/hypopnea events in the screening recordings is the key factor
for the diagnosis of OSAS. The analysis of a solely single-lead
electrocardiographic (ECG) signal for OSAS diagnosis, which may
be done with portable devices, at patient-s home, is the challenge of
the last years. A novel artificial neural network (ANN) based
approach for feature extraction and automatic identification of
respiratory events in ECG signals is presented in this paper. A
nonlinear principal component analysis (NLPCA) method was
considered for feature extraction and support vector machine for
classification/recognition. An alternative representation of the
respiratory events by means of Kohonen type neural network is
discussed. Our prospective study was based on OSAS patients of the
Clinical Hospital of Pneumology from Iaşi, Romania, males and
females, as well as on non-OSAS investigated human subjects. Our
computed analysis includes a learning phase based on cross signal
PSG annotation.
Abstract: This paper presented two new efficient algorithms
for contour approximation. The proposed algorithm is compared
with Ramer (good quality), Triangle (faster) and Trapezoid (fastest)
in this work; which are briefly described. Cartesian co-ordinates of
an input contour are processed in such a manner that finally
contours is presented by a set of selected vertices of the edge of the
contour. In the paper the main idea of the analyzed procedures for
contour compression is performed. For comparison, the mean
square error and signal-to-noise ratio criterions are used.
Computational time of analyzed methods is estimated depending on
a number of numerical operations. Experimental results are
obtained both in terms of image quality, compression ratios, and
speed. The main advantages of the analyzed algorithm is small
numbers of the arithmetic operations compared to the existing
algorithms.
Abstract: The aim of this study was to remove the two principal
noises which disturb the surface electromyography signal
(Diaphragm). These signals are the electrocardiogram ECG artefact
and the power line interference artefact. The algorithm proposed
focuses on a new Lean Mean Square (LMS) Widrow adaptive
structure. These structures require a reference signal that is correlated
with the noise contaminating the signal. The noise references are
then extracted : first with a noise reference mathematically
constructed using two different cosine functions; 50Hz (the
fundamental) function and 150Hz (the first harmonic) function for
the power line interference and second with a matching pursuit
technique combined to an LMS structure for the ECG artefact
estimation. The two removal procedures are attained without the use
of supplementary electrodes. These techniques of filtering are
validated on real records of surface diaphragm electromyography
signal. The performance of the proposed methods was compared with
already conducted research results.
Abstract: Biological reactions of individuals of a testing animal
to toxic substance are unique and can be used as an indication of the
existing of toxic substance. However, to distinguish such phenomenon
need a very complicate system and even more complicate to analyze
data in 3 dimensional. In this paper, a system to evaluate in vitro
biological activities to acute toxicity of stochastic self-affine
non-stationary signal of 3D goldfish swimming by using fractal
analysis is introduced. Regular digital camcorders are utilized by
proposed algorithm 3DCCPC to effectively capture and construct 3D
movements of the fish. A Critical Exponent Method (CEM) has been
adopted as a fractal estimator. The hypothesis was that the swimming
of goldfish to acute toxic would show the fractal property which
related to the toxic concentration. The experimental results supported
the hypothesis by showing that the swimming of goldfish under the
different toxic concentration has fractal properties. It also shows that
the fractal dimension of the swimming related to the pH value of FD Ôëê
0.26pH + 0.05. With the proposed system, the fish is allowed to swim
freely in all direction to react to the toxic. In addition, the trajectories
are precisely evaluated by fractal analysis with critical exponent
method and hence the results exhibit with much higher degree of
confidence.
Abstract: In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is proposed. Also, reduced bits are used to enhance sound quality. The performance of the proposed algorithm is evaluated by sound quality and bit reduction rates in clean and frame loss conditions.
Abstract: Navigation is the processes of monitoring and
controlling the movement of an object from one place to another.
Currently, Global Positioning System (GPS) is the main navigation
system used all over the world for navigation applications. GPS
receiver receives signals from at least three satellites to locate and
display itself. Displayed positioning information is updated
continuously. Update rate is the number of times per second that a
display is illuminated. The speed of update is governed by receiver
update rate. A higher update rate decreases display lag time and
improves distance measurements and tracking especially when
moving on a curvy route. The majority of GPS receivers used
nowadays are updated every second continuously. This period is
considered reasonable for some applications while it is long relatively
for high speed applications. In this paper, the suitability and
feasibility of GPS receiver with different update rates will be
evaluated for various applications according to the level of speed and
update rate needed for particular applications.
Abstract: This paper presents the application of a signal
intensity independent registration criterion for 2D rigid body
registration of medical images using 1D binary projections. The
criterion is defined as the weighted ratio of two projections. The ratio
is computed on a pixel per pixel basis and weighting is performed by
setting the ratios between one and zero pixels to a standard high
value. The mean squared value of the weighted ratio is computed
over the union of the one areas of the two projections and it is
minimized using the Chebyshev polynomial approximation using
n=5 points. The sum of x and y projections is used for translational
adjustment and a 45deg projection for rotational adjustment. 20 T1-
T2 registration experiments were performed and gave mean errors
1.19deg and 1.78 pixels. The method is suitable for contour/surface
matching. Further research is necessary to determine the robustness
of the method with regards to threshold, shape and missing data.
Abstract: Partitions can play a significant role in minimising cochannel
interference of Wireless LANs by attenuating signals across
room boundaries. This could pave the way towards higher density
deployments in home and office environments through spatial
channel reuse. Yet, due to protocol limitations, the latest incantation
of IEEE 802.11 standard is still unable to take advantage of this fact:
Despite having clearly adequate Signal to Interference Ratio (SIR)
over co-channel neighbouring networks in other rooms, its goodput
falls significantly lower than its maximum in the absence of cochannel
interferers. In this paper, we describe how this situation can
be remedied via modest modifications to the standard.
Abstract: Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification
Abstract: Attitude Determination (AD) of a spacecraft using the
phase measurements of the Global Navigation Satellite System
(GNSS) is an active area of research. Various attitude determination
algorithms have been developed in yester years for spacecrafts using
different sensors but the last two decades have witnessed a
phenomenal increase in research related with GPS receivers as a
stand-alone sensor for determining the attitude of satellite using the
phase measurements of the signals from GNSS. The GNSS-based
Attitude determination algorithms have been experimented in many
real missions. The problem of AD algorithms using GNSS phase
measurements has two important parts; the ambiguity resolution and
the determining of attitude. Ambiguity resolution is the widely
addressed topic in literature for implementing the AD algorithm
using GNSS phase measurements for achieving the accuracy of
millimeter level. This paper broadly overviews the different
techniques for resolving the integer ambiguities encountered in AD
using GNSS phase measurements.
Abstract: Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.