Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: Cell volume, together with membrane potential and
intracellular hydrogen ion concentration, is an essential biophysical
parameter for normal cellular activity. Cell volumes can be altered by
osmotically active compounds and extracellular tonicity.
In this study, a simple mathematical model of osmotically induced
cell swelling and shrinking is presented. Emphasis is given to water
diffusion across the membrane. The mathematical description of the
cellular behavior consists in a system of coupled ordinary differential
equations. We compare experimental data of cell volume alterations
driven by differences in osmotic pressure with mathematical
simulations under hypotonic and hypertonic conditions. Implications
for a future model are also discussed.
Abstract: Precise capture of plantar 3D surface of the foot at the
loading gait phases on rigid substrates was found to be valuable for
the assessment of the physiology, health and problems of the feet.
Photogrammetry, a precision 3D spatial data capture technique is
suitable for this type of dynamic application. In this research, the
technique is utilised to study the plantar deformation as a result of
having a strip of kinesiology tape on the plantar surface during the
loading phase of gait. For this pilot study, one healthy adult male
subject was recruited under the University’s human research ethics
guidelines for this preliminary study. The 3D plantar deformation
data with and without applying the tape were analysed. The results
and analyses are presented together with detailed findings.
Abstract: The ultrasound imaging is very popular to diagnosis
the disease because of its non-invasive nature. The ultrasound
imaging slowly produces low quality images due to the presence of
spackle noise and wave interferences. There are several algorithms to
be proposed for the segmentation of ultrasound carotid artery images
but it requires a certain limit of user interaction. The pixel in an
image is highly correlated so the spatial information of surrounding
pixels may be considered in the process of image segmentation which
improves the results further. When data is highly correlated, one pixel
may belong to more than one cluster with different degree of
membership. There is an important step to computerize the evaluation
of arterial disease severity using segmentation of carotid artery lumen
in 2D and 3D ultrasonography and in finding vulnerable
atherosclerotic plaques susceptible to rupture which can cause stroke.
Abstract: Electroencephalogram (EEG) is a noninvasive
technique that registers signals originating from the firing of neurons
in the brain. The Emotiv EEG Neuroheadset is a consumer product
comprised of 14 EEG channels and was used to record the reactions
of the neurons within the brain to two forms of stimuli in 10
participants. These stimuli consisted of auditory and visual formats
that provided directions of ‘right’ or ‘left.’ Participants were
instructed to raise their right or left arm in accordance with the
instruction given. A scenario in OpenViBE was generated to both
stimulate the participants while recording their data. In OpenViBE,
the Graz Motor BCI Stimulator algorithm was configured to govern
the duration and number of visual stimuli. Utilizing EEGLAB under
the cross platform MATLAB®, the electrodes most stimulated during
the study were defined. Data outputs from EEGLAB were analyzed
using IBM SPSS Statistics® Version 20. This aided in determining
the electrodes to use in the development of a brain-machine interface
(BMI) using real-time EEG signals from the Emotiv EEG
Neuroheadset. Signal processing and feature extraction were
accomplished via the Simulink® signal processing toolbox. An
Arduino™ Duemilanove microcontroller was used to link the Emotiv
EEG Neuroheadset and the right and left Mecha TE™ Hands.
Abstract: The purpose of this study is to investigate the kinematic
characteristics and differences of the snatch barbell trajectory of 53 kg
class female weight lifters. We take the 2014 Taiwan College Cup
players as examples, and tend to make kinematic applications through
the proven weightlifting barbell track system. The competition videos
are taken by consumer camcorder with a tripod which set up at the side
of the lifter. The results will be discussed in three parts, the first part is
various lifting phase, the second part is the compare lifting between
success and unsuccessful, and the third part is to compare the
outstanding player with the general. Conclusion through the barbell
can be used to observe the trajectories of our players lifting the usual
process cannot be observed in the presence of malfunction or habits, so
that the coach can find the problem and guide the players more
accurately. Our system can be applied in practice and competition to
increase the resilience of the lifter on the field.
Abstract: Robotic surgery is used to enhance minimally invasive
surgical procedure. It provides greater degree of freedom for surgical
tools but lacks of haptic feedback system to provide sense of touch to
the surgeon. Surgical robots work on master-slave operation, where
user is a master and robotic arms are the slaves. Current, surgical
robots provide precise control of the surgical tools, but heavily rely
on visual feedback, which sometimes cause damage to the inner
organs. The goal of this research was to design and develop a realtime
Simulink based robotic system to study force feedback
mechanism during instrument-object interaction. Setup includes three
VelmexXSlide assembly (XYZ Stage) for three dimensional
movement, an end effector assembly for forceps, electronic circuit for
four strain gages, two Novint Falcon 3D gaming controllers,
microcontroller board with linear actuators, MATLAB and Simulink
toolboxes. Strain gages were calibrated using Imada Digital Force
Gauge device and tested with a hard-core wire to measure
instrument-object interaction in the range of 0-35N. Designed
Simulink model successfully acquires 3D coordinates from two
Novint Falcon controllers and transfer coordinates to the XYZ stage
and forceps. Simulink model also reads strain gages signal through
10-bit analog to digital converter resolution of a microcontroller
assembly in real time, converts voltage into force and feedback the
output signals to the Novint Falcon controller for force feedback
mechanism. Experimental setup allows user to change forward
kinematics algorithms to achieve the best-desired movement of the
XYZ stage and forceps. This project combines haptic technology
with surgical robot to provide sense of touch to the user controlling
forceps through machine-computer interface.
Abstract: Object-oriented modeling is spreading in current
simulation of physiological systems through the use of the individual
components of the model and its interconnections to define the
underlying dynamic equations. In this paper we describe the use of
both the SIMSCAPE and MODELICA simulation environments in
the object-oriented modeling of the closed loop cardiovascular
system. The performance of the controlled system was analyzed by
simulation in light of the existing hypothesis and validation tests
previously performed with physiological data. The described
approach represents a valuable tool in the teaching of physiology for
graduate medical students.
Abstract: The arm length, hand length, hand breadth and middle
finger length of 1540 right-handed industrial workers of Haryana
state was used to assess the relationship between the upper limb
dimensions and stature. Initially, the data were analyzed using basic
univariate analysis and independent t-tests; then simple and multiple
linear regression models were used to estimate stature using SPSS
(version 17). There was a positive correlation between upper limb
measurements (hand length, hand breadth, arm length and middle
finger length) and stature (p < 0.01), which was highest for hand
length. The accuracy of stature prediction ranged from ± 54.897 mm
to ± 58.307 mm. The use of multiple regression equations gave better
results than simple regression equations. This study provides new
forensic standards for stature estimation from the upper limb
measurements of male industrial workers of Haryana (India). The
results of this research indicate that stature can be determined using
hand dimensions with accuracy, when only upper limb is available
due to any reasons likewise explosions, train/plane crashes, mutilated
bodies, etc. The regression formula derived in this study will be
useful for anatomists, archaeologists, anthropologists, design
engineers and forensic scientists for fairly prediction of stature using
regression equations.
Abstract: This paper provides a quantitative measure of the
time-varying multiunit neuronal spiking activity using an entropy
based approach. To verify the status embedded in the neuronal activity
of a population of neurons, the discrete wavelet transform (DWT) is
used to isolate the inherent spiking activity of MUA. Due to the
de-correlating property of DWT, the spiking activity would be
preserved while reducing the non-spiking component. By evaluating
the entropy of the wavelet coefficients of the de-noised MUA, a
multiresolution Shannon entropy (MRSE) of the MUA signal is
developed. The proposed entropy was tested in the analysis of both
simulated noisy MUA and actual MUA recorded from cortex in rodent
model. Simulation and experimental results demonstrate that the
dynamics of a population can be quantified by using the proposed
entropy.
Abstract: The efficiency of the actuation system of exoskeletons
and active orthoses for lower limbs is a significant aspect of the
design of such devices because it affects their efficacy. The F-IVT is
an innovative actuation system to power artificial knee joint with
energy recovery capabilities. Its key and non-conventional elements
are a flywheel that acts as a mechanical energy storage system, and
an Infinitely Variable Transmission (IVT). The design of the F-IVT
can be optimized for a certain walking condition, resulting in a heavy
reduction of both the electric energy consumption and of the electric
peak power. In this work, by means of simulations of level ground
walking at different speeds, it is demonstrated that the F-IVT is still
an advantageous actuator which permits to save energy consumption
and to downsize the electric motor even when it does not work in
nominal conditions.
Abstract: This study aimed to investigate the magnetic resonance
(MR) signal enhancement ratio (ER) of contrast-enhanced MR
angiography (CE-MRA) in normal rats with gadobenate dimeglumine
(Gd-BOPTA) using a clinical 3T scanner and an extremity coil. The
relaxivities of Gd-BOPTA with saline only and with 4.5% human
serum albumin (HSA) were also measured. Compared with
Gadolinium diethylenetriaminepentaacetic acid (Gd-DTPA),
Gd-BOPTA had higher relaxivities. The maximum ER of aorta (ERa),
kidney, liver and muscle with Gd-BOPTA were higher than those with
Gd-DTPA. The maximum ERa appeared at 1.2 min and decayed to half
at 10 min after Gd-BOPTA injection. This information is helpful for
the design of CE-MRA study of rats.
Abstract: There are many perceived advantages of microwave
ablation have driven researchers to develop innovative antennas to
effectively treat deep-seated, non-resectable hepatic tumors. In this
paper a coaxial antenna with a miniaturized sleeve choke has been
discussed for microwave interstitial ablation therapy, in order to
reduce backward heating effects irrespective of the insertion depth
into the tissue. Two dimensional Finite Element Method (FEM) is
used to simulate and measure the results of miniaturized sleeve choke
antenna. This paper emphasizes the importance of factors that can
affect simulation accuracy, which include mesh resolution, surface
heating and reflection coefficient. Quarter wavelength choke
effectiveness has been discussed by comparing it with the unchoked
antenna with same dimensions.
Abstract: Cerebellar ataxia is a steadily progressive
neurodegenerative disease associated with loss of motor control,
leaving patients unable to walk, talk, or perform activities of daily
living. Direct motor instruction in cerebella ataxia patients has limited
effectiveness, presumably because an inappropriate closed-loop
cerebellar response to the inevitable observed error confounds motor
learning mechanisms. Could the use of EEG based BCI provide
advanced biofeedback to improve motor imagery and provide a
“backdoor” to improving motor performance in ataxia patients? In
order to determine the feasibility of using EEG-based BCI control in
this population, we compare the ability to modulate mu-band power
(8-12 Hz) by performing a cued motor imagery task in an ataxia
patient and healthy control.
Abstract: Mammography is widely used technique for breast cancer
screening. There are various other techniques for breast cancer screening
but mammography is the most reliable and effective technique. The
images obtained through mammography are of low contrast which
causes problem for the radiologists to interpret. Hence, a high quality
image is mandatory for the processing of the image for extracting any
kind of information from it. Many contrast enhancement algorithms have
been developed over the years. In the present work, an efficient
morphology based technique is proposed for contrast enhancement of
masses in mammographic images. The proposed method is based on
Multiscale Morphology and it takes into consideration the scale of the
structuring element. The proposed method is compared with other stateof-
the-art techniques. The experimental results show that the proposed
method is better both qualitatively and quantitatively than the other
standard contrast enhancement techniques.
Abstract: The paper presents a novel screening method to
indicate congenital heart diseases (CHD), which otherwise could
remain undetected because of their low level. Therefore, not
belonging to the high-risk population, the pregnancies are not subject
to the regular fetal monitoring with ultrasound echocardiography.
Based on the fact that CHD is a morphological defect of the heart
causing turbulent blood flow, the turbulence appears as a murmur,
which can be detected by fetal phonocardiography (fPCG). The
proposed method applies measurements on the maternal abdomen
and from the recorded sound signal a sophisticated processing
determines the fetal heart murmur. The paper describes the problems
and the additional advantages of the fPCG method including the
possibility of measurements at home and its combination with the
prescribed regular cardiotocographic (CTG) monitoring. The
proposed screening process implemented on a telemedicine system
provides an enhanced safety against hidden cardiac diseases.
Abstract: Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.
Abstract: In this paper, the cable model of dendrites have been
considered. The dendrites are cylindrical cables of various segments
having variable length and reducing radius from start point at synapse
and end points. For a particular event signal being received by a
neuron in response only some dendrite are active at a particular
instance. Initial current signals with different current flows in
dendrite are assumed. Due to overlapping and coupling of active
dendrite, they induce currents in the dendrite segments of each other
at a particular instance. But how these currents are induced in the
various segments of active dendrites due to coupling between these
dendrites, It is not presented in the literature. Here the paper presents
a model for induced currents in active dendrite segments due to
mutual coupling at the starting instance of an activity in dendrite. The
model is as discussed further.
Abstract: This paper presents the design, development and
evaluation of an application prototype developed to support
tuberculosis (TB) patients’ treatment adherence. The system makes
use of graphics and voice reminders as opposed to text messaging to
encourage patients to follow their medication routine. To evaluate the
effect of the prototype applications, participants were given mobile
phones on which the reminder system was installed. Thirty-eight
people, including TB health workers and patients from Zanzibar,
Tanzania, participated in the evaluation exercises. The results
indicate that the participants found the mobile image-based
application is useful to support TB treatment. All participants
understood and interpreted the intended meaning of every image
correctly. The study findings revealed that the use of a mobile visualbased
application may have potential benefit to support TB patients
(both literate and illiterate) in their treatment processes.
Abstract: Studying stress and strain trends in the femur and
recognizing femur failure mechanism is very important for
preventing hip fracture in the elderly. The aim of this study was to
identify high stress and strain regions in the femur during normal
walking and falling to find the mechanical behavior and failure
mechanism of the femur. We developed a finite element model of the
femur from the subject’s quantitative computed tomography (QCT)
image and used it to identify potentially high stress and strain regions
during the single-leg stance and the sideways fall. It was found that
fracture may initiate from the superior region of femoral neck and
propagate to the inferior region during a high impact force such as
sideways fall. The results of this study showed that the femur bone is
more sensitive to strain than stress which indicates the effect of
strain, in addition to effect of stress, should be considered for failure
analysis.