Abstract: Efficient diagnosis of chronic wound depends on the quality of digital
image that has reached the Tele-Medical Hub through Tele-Wound Network.
However, how much ever precaution we take, while capturing the image by
digital camera or by smartphone, presence of random/impulse noise would be
always there to corrupt the captured image. The wound images give the vital
information such as size, wound status, tissue composition and healing rate. In
this paper, we have proposed adaptive filtering technique for chronic wound
(CW) image analysis under Tele-wound network to improve the diagnosis.
Here, the best filter has been chosen which can help to improve the diagnosis of
wound.Acomparative study of 16 different filters has also been performed on
72 different wound images. The experimental results are given by comparing
8 different parameters. These various parameters are Peak Signal to Noise
Ratio (PSNR), Mean Square Error (MSE), Signal to Noise Ratio (SNR),
NegativeAbsolute Error (NAE), Maximum Difference (MD), Mean Structural
Similarity Index (MSSIM), Universal Image Quality Index (UIQI) and Mean
Absolute Error (MAE). Simulated results shows adaptive median provides
better performances with respect to high value of PSNR (66.23), SNR (58.05)
and lower value ofMSE(3.01),MAE(0.29), andNAE(0.01) between original
and filtered image. The proposed methodology will assist the clinicians to take
better decision towards diagnosis ofCWin terms of qualitative at low-resource
setup.
Keywords: Adaptive Median Filter; Chronic Wound; Wound Image Analysis;
Tele-Wound Network.
Abstract: The parameters of the human voice change according to a mix of emotional,
psychological and physical body conditions. However, while it is evident
that this change occurs because of happiness, sadness, euphoria, depression,
excitement, and so ahead, there is less evidence of a direct correlation of
the change of the voice with respect to specific physical and/or pathological
conditions and/or diseases. This work intends to demonstrate such a correlation
in the specific case of the tuberculosis disease, evidencing differences in the
voice parameters of unhealthy with respect healthy people.
Keywords: Screening, tuberculosis, voice parameters.
Abstract: Determining the person who spoke a given speech utterance from a group
of people is referred to as Speaker Identification. It is used in crime scenes,
surveillance and consumer electronic products like smart TV. But it faces
poor performance due to a mismatch between the train and the test speech
data, that arises because of the adoption of voice disguise. Therefore, this paper
studies the effect of three different types of voice disguises, namely, Fast (nonimitative),
Synchronous (Imitative) and Repetitive Synchronous Imitation
along with the normal speaking from the CHAINS corpus on the speaker
identification performance. Finally, a system combining different frame rates
for feature extraction and reliable frame selection at the decision level has
been proposed. The evaluated system showed an overall better performance
than the baseline systems.
Keywords: Robust speaker identification, voice disguise, biometric, frame
selection
Abstract: The use ofUWB(Ultra-Wide Band) radar microwave imaging in stroke detection
opens the possibility to develop low cost, fast response and transportable
diagnostic devices, which could play a key role in emergency scenarios. The
feasibility of such a device is strictly related to the trade-off performancecomplexity,
which depends from the chosen beamforming algorithm, the
number of antennas and the radar mode (monostatic/multistatic). This paper
aims to provide a better understanding of this trade-off for several beamforming
algorithms and radar configurations (monostatic/multistatic) applied
to stroke detection. Comparisons are performed assuming an antenna system
with a low number of antennas (namely 8) with respect to more commonly
considered settings for this application (from 16 to 48 antennas). The study is
based on FDTD simulations and considered beamforming algorithms are:
Delay & Sum (considered in most of the works on UWB radar stroke
detection); MIST algorithms and adapted versions of the MIST and RAR
algorithms originally proposed for breast cancer detection.
Keywords: Brain stroke detection, beamforming algorithms, microwave
UWB radar.
Abstract: In this paper radio positioning techniques using “Signals of Opportunity
(SOP)” are discussed. In some applications of navigation and positioning,
Global Navigation Satellite Systems (GNSS), in general, and the Global
Positioning System (GPS), in particular, do not work well and therefore
researchers are interested in using other sources of radio signals (which
are intended for other purposes) for the navigation and radio positioning
applications. In this contribution first we mention some drawbacks of GPS.
Then several types of signals of opportunity for positioning are enlisted and
the advantages and disadvantages of these signals as well as methods of
measurements are presented. The most crucial challenges of SOP for radio
positioning are explained. Finally, a brief conclusion on the usage of signals
of opportunity is presented.
Keywords:
