Ieee projects 2012 2013 - Bio Medical

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IEEE FINAL YEAR PROJECTS 2012 – 2013
Bio- Medical
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IEEE Final Year Projects 2012 |Student Projects | Bio-Medical Projects


BIO-MEDICAL 2012 – 2013

EGC A 64-Channel Transmitter for Investigating Parallel Transmit MRI
5201

Multiple channel radiofrequency (RF) transmitters are being used in magnetic resonance imaging to investigate a
number of active research topics, including transmit SENSE and B$_1$ shimming. Presently, the cost and availability of
multiple channel transmitters restricts their use to relatively few sites. This paper describes the development and testing
of a relatively inexpensive transmit system that can be easily duplicated by users with a reasonable level of RF hardware
design experience. The system described here consists of 64 channels, each with 100 W peak output level. The
hardware is modular at the level of four channels, easily accommodating larger or smaller channel counts. Unique
aspects of the system include the use of vector modulators to replace more complex IQ direct digital modulators, 100 W
MOSFET RF amplifiers with partial microstrip matching networks, and the use of digital potentiometers to replace more
complex and costly digital-to-analog converters to control the amplitude and phase of each channel. Although mainly
designed for B $_1$ shimming, the system is capable of dynamic modulation necessary for transmit SENSE by replacing
the digital potentiometers controlling the vector modulators with commercially available analog output boards. The
system design is discussed in detail and bench and imaging data are shown, demonstrating the ability to perform phase
and amplitude control for B$_1$ shimming as well as dynamic modulation for transmitting complex RF pulses

EGC A Minimal Model of Tumor Growth Inhibition in Combination Regimens Under the
5202
Hypothesis of No Interaction Between Drugs

One important issue in the preclinical development of an anticancer drug is the assessment of the compound under
investigation when administered in combination with other drugs. Several experiments are routinely conducted in
xenograft mice to evaluate if drugs interact or not. Experimental data are generally qualitatively analyzed on empirical
basis. The ability of deriving from single drug experiments a reference response to the joint administrations, assuming
no interaction, and comparing it to real responses would be key to recognize synergic and antagonist compounds.
Therefore, in this paper, the minimal model of tumor growth inhibition (TGI), previously developed for a single drug, is
reformulated to account for the effects of noninteracting drugs and simulate, under this hypothesis, combination
regimens. The model is derived from a minimal set of basic assumptions that include and extend those formulated at
cellular level for the single drug administration. The tumor growth dynamics is well approximated by the deterministic
evolution of its expected value that is obtained through the solution of an ordinary and several partial differential



equations. Under suitable assumptions on the cell death process, the model reduces to a lumped parameter model that
represents the extension of the very popular Simeoni TGI model to the combined administration of noninteracting drugs.

EGC A Robust and Sensitive Metric for Quantifying Movement Smoothness
5203

The need for movement smoothness quantification to assess motor learning and recovery has resulted in various
measures that look at different aspects of a movement’s profile. This paper first shows that most of the previously
published smoothness measures lack validity, consistency, sensitivity, or robustness. It then introduces and evaluates
the spectral arc-length metric that uses a movement speed profile’s Fourier magnitude spectrum to quantify movement
smoothness. This new metric is systematically tested and compared to other smoothness metrics, using experimental
data from stroke and healthy subjects as well as simulated movement data. The results indicate that the spectral arc-
length metric is a valid and consistent measure of movement smoothness, which is both sensitive to modifications in
motor behavior and robust to measurement noise. We hope that the systematic analysis of this paper is a step toward
the standardization of the quantitative assessment of movement smoothness.

EGC A Stable and Real-Time Nonlinear Elastic Approach to Simulating Guidewire and Catheter
5204
Insertions Based on Cosserat Rod

Interventional Radiology procedures (e.g., angioplasty, embolization, stent graft placement) provide minimally invasive
therapy to treat a wide range of conditions. These procedures involve the use of flexible tipped guidewires to advance
diagnostic or therapeutic catheters into a patient’s vascular or visceral anatomy. This paper presents a real-time
physically based hybrid modeling approach to simulating guidewire insertions. The long, slender body of the guidewire
shaft is simulated using nonlinear elastic Cosserat rods, and the shorter flexible tip composed of a straight, curved, or
angled design is modeled using a more efficient generalized bending model. Therefore, the proposed approach
efficiently computes intrinsic dynamic behaviors of guidewire interactions within vascular structures. The efficacy of the
proposed method is demonstrated using detailed numerical simulations inside 3-D blood vessel structures derived from
preprocedural volumetric data. A validation study compares positions of four physical guidewires deployed within a
vascular phantom, with the co-ordinates of the corresponding simulated guidewires within a virtual model of the
phantom. An optimization algorithm is also implemented to further improve the accuracy of the simulation. The
presented simulation model is suitable for interactive virtual reality-based training and for treatment planning.

EGC Accelerating Cardiac Bidomain Simulations Using Graphics Processing Units
5205



Anatomically realistic and biophysically detailed multiscale computer models of the heart are playing an increasingly
important role in advancing our understanding of integrated cardiac function in health and disease. Such detailed
simulations, however, are computationally vastly demanding, which is a limiting factor for a wider adoption of in-silico
modeling. While current trends in high-performance computing (HPC) hardware promise to alleviate this problem,
exploiting the potential of such architectures remains challenging since strongly scalable algorithms are necessitated to
reduce execution times. Alternatively, acceleration technologies such as graphics processing units (GPUs) are being
considered. While the potential of GPUs has been demonstrated in various applications, benefits in the context of
bidomain simulations where large sparse linear systems have to be solved in parallel with advanced numerical
techniques are less clear. In this study, the feasibility of multi-GPU bidomain simulations is demonstrated by running
strong scalability benchmarks using a state-of-the-art model of rabbit ventricles. The model is spatially discretized using
the finite element methods (FEM) on fully unstructured grids. The GPU code is directly derived from a large pre-existing
code, the Cardiac Arrhythmia Research Package (CARP), with very minor perturbation of the code base. Overall,
bidomain simulations were sped up by a factor of 11.8 to 16.3 in benchmarks running on 6–20 GPUs compared to the
same number of CPU cores. To match the fastest GPU simulation which engaged 20 GPUs, 476 CPU cores were required
on a national supercomputing facility.

EGC An Implantable RF Solenoid for Magnetic Resonance Microscopy and
5206
Microspectroscopy

Miniature solenoids routinely enhance small volume nuclear magnetic resonance imaging and spectroscopy; however,
no such techniques exist for patients. We present an implantable microcoil for diverse clinical applications, with a
microliter coil volume. The design is loosely based on implantable depth electrodes, in which a flexible tube serves as
the substrate, and a metal stylet is inserted into the tube during implantation. The goal is to provide enhanced signal-to-
noise ratio (SNR) of structures that are not easily accessed by surface coils. The first-generation prototype was
designed for implantation up to 2 cm, and provided initial proof-of-concept for microscopy. Subsequently, we optimized
the design to minimize the influence of lead inductances, and to thereby double the length of the implantable depth (4
cm). The second-generation design represents an estimated SNR improvement of over 30% as compared to the original
design when extended to 4 cm. Impedance measurements indicate that the device is stable for up to 24 h in body
temperature saline. We evaluated the SNR and MR-related heating.

EGC An Optimization-Based Study of Equivalent Circuit Models for Representing Recordings
5207
at the Neuron–Electrode Interface

Extracellular neuroelectronic interfacing is an emerging field with important applications in the fields of neural
prosthetics, biological computation, and biosensors. Traditionally, neuron–electrode interfaces have been modeled as
linear point or area contact equivalent circuits but it is now being increasingly realized that such models cannot explain



the shapes and magnitudes of the observed extracellular signals. Here, results were compared and contrasted from an
unprecedented optimization-based study of the point contact models for an extracellular ―on-cell‖ neuron–patch
electrode and a planar neuron–microelectrode interface. Concurrent electrophysiological recordings from a single
neuron simultaneously interfaced to three distinct electrodes (intracellular, ―on-cell‖ patch, and planar microelectrode)
allowed novel insights into the mechanism of signal transduction at the neuron–electrode interface. After a systematic
isolation of the nonlinear neuronal contribution to the extracellular signal, a consistent underestimation of the simulated
suprathreshold extracellular signals compared to the experimentally recorded signals was observed. This conclusively
demonstrated that the dynamics of the interfacial medium contribute nonlinearly to the process of signal transduction at
the neuron–electrode interface. Further, an examination of the optimized model parameters for the experimental
extracellular recordings from sub- and suprathreshold stimulations of the neuron–electrode junctions revealed that ionic
transport at the ―on-cell‖ neuron–patch electrode is dominated by diffusion whereas at the neuron–microelectrode
interface the electric double layer (EDL) effects dominate. Based on this study, the limitations of the equivalent circuit
models in their failure to account for the nonlinear EDL and ionic electrodiffusion effects occurring during signal trans-
uction at the neuron–electrode interfaces are discussed.

EGC Automated Fiducial Localization in CT Images Based on Surface Processing and
5208
Geometrical Prior Knowledge for Radiotherapy Applications

We propose a novel method for radio-opaque external marker localization in CT scans for infrared (IR) patient set-up in
radiotherapy. Efforts were focused on the quantification of uncertainties in marker localization in the CT dataset as a
function of algorithm performance. We implemented a 3-D approach to fiducial localization based on surface extraction
and marker recognition according to geometrical prior knowledge. The algorithm parameters were optimized on a
clinical CT dataset coming from 35 cranial and extra-cranial patients; the localization accuracy was benchmarked at
variable image resolution versus laser tracker measurements. The applicability of conventional IR optical tracking
systems for localizing external surrogates in daily patient set-up procedures was also investigated in 121 proton therapy
treatment sessions. Our study shows that the implemented algorithm features surrogates localization with uncertainties
lower than 0.3 mm and with a true positive rate of 90.1%, being this latter mainly influenced by fiducial homogeneity in
the CT images. The reported clinical validation in proton therapy confirmed the submillimetric accuracy and the
expected algorithm sensitivity. Geometrical prior knowledge allows judging the reliability of the extracted fiducial
coordinates, ensuring the highest accuracy in patient set-up.

EGC Automatic Segmentation of Polyps in Colonoscopic Narrow-Band Imaging Data
5209

Colorectal cancer is the third most common type of cancer worldwide. However, this disease can be prevented by
detection and removal of precursor adenomatous polyps during optical colonoscopy (OC). During OC, the endoscopist



looks for colon polyps. While hyperplastic polyps are benign lesions, adenomatous polyps are likely to become
cancerous. Hence, it is a common practice to remove all identified polyps and send them to subsequent histological
analysis. But removal of hyperplastic polyps poses unnecessary risk to patients and incurs unnecessary costs for
histological analysis. In this paper, we develop the first part of a novel optical biopsy application based on narrow-band
imaging (NBI). A barrier to an automatic system is that polyp classification algorithms require manual segmentations of
the polyps, so we automatically segment polyps in colonoscopic NBI data. We propose an algorithm, Shape-UCM, which
is an extension of the gPb-OWT-UCM algorithm, a state-of-the-art algorithm for boundary detection and segmentation.
Shape-UCM solves the intrinsic scale selection problem of gPb-OWT-UCM by including prior knowledge about the shape
of the polyps. Shape-UCM outperforms previous methods with a specificity of 92%, a sensitivity of 71%, and an accuracy
of 88% for automatic segmentation of a test set of 87 images.

EGC Bioimpedance Analysis for the Characterization of Breast Cancer Cells in Suspension
5210

The bioimpedance spectroscopy (BIS) technique is potentially a useful tool to differentiate malignancy based on the
variation of electrical properties presented by different tissues and cells. The different tissues and cells present variant
electrical resistance and reactance when excited at different frequencies. The main purpose of this area of research is to
use impedance measurements over a low-frequency bandwidth ranging from 1 kHz to 3 MHz to 1) differentiate the
pathological stages of cancer cells under laboratory conditions and 2) permit the extraction of electrical parameters
related to cellular information for further analysis. This provides evidence to form the basis of bioimpedance
measurement at the cellular level and aids the potential future development of rapid diagnostics from biopsy materials.
Three cell lines, representing normal breast epithelia and different pathological stages of breast cancer, have been
measured using a standard impedance analyzer driving a four-electrode chamber filled with different cell suspensions.
We identify the specific BIS profile for each cell type and determine whether these can be differentiated. In addition, the
electrical parameters, e.g., the intracellular conductivity, membrane capacitance/capacity, characteristic frequency, are
extracted by the use of equivalent circuit models and physical models to provide details of the cell electric signatures
for further analysis of cancer cell pathology.

EGC Biopsy Needle Localization Using Magnetic Induction Imaging Principles: A Feasibility
5211 Study

The accurate navigation and location of a biopsy needle is of main clinical interest in cases of image-guided biopsies for
patients with suspected cancerous lesions. Magnetic induction (MI) imaging is a relatively new simple and low-cost
noninvasive imaging modality that can be used for measuring the changes of electrical conductivity distribution inside a
biological tissue. The feasibility of using MI principles for measuring and imaging the location of a biopsy needle in a
tissue with suspected lesion was studied in simulations and with an experimental system. A contactless
excitation/sensing unit was designed, and raster scan was performed on a thin tissue slab with an inserted standard 22



gauge stainless steel biopsy needle. A 30-mA, 50-kHz excitation field was employed, and the secondary-induced
electromotive force (emf$_s$ ) was measured and plotted on a 2-D plane in order to yield an image of the needle
location. The simulations demonstrated the significance of utilizing a ferrimagnetic core for the excitation coil in order to
increase induced currents magnitude and scanning resolution. The experimental reconstructed images of the emf $_s$
spatial distribution revealed the needle position and orientation, with an accuracy of 0.1 mm and a signal-to-background
ratio of ∼30 dB. High correlation (R$^2$ = 0.89) between the experimental and simulation results was observed. We
conclude that MI principles exhibit a potential alternative to existing imaging modalities for needle biopsy procedures.

EGC Ex Vivo Measurement of Postmortem Tissue Changes in the Crystalline Lens by
5212 Brillouin Spectroscopy and Confocal Reflectance Microscopy

Use of Brillouin spectroscopy in ophthalmology enables noninvasive, spatially resolved determination of the rheological
properties of crystalline lens tissue. Furthermore, the Brillouin shift correlates with the protein concentration inside the
lens. In vitro measurements on extracted porcine lenses demonstrate that results obtained with Brillouin spectroscopy
depend strongly on time after death. The intensity of the Brillouin signal decreases significantly as early as 5 h
postmortem. Moreover, the fluctuation of the Brillouin frequency shift inside the lens increases with postmortem time.
Images of lens tissue taken with a confocal reflectance microscope between measurements reveal a degenerative aging
process. These tissue changes correlate with our results from Brillouin spectroscopy. It is concluded that only in vivo
measurements appropriately reflect the rheological properties of the eye lens and its protein concentration.

EGC Fractional-Order Time Series Models for Extracting the Haemodynamic Response From
5213
Functional Magnetic Resonance Imaging Data

The postprocessing of functional magnetic resonance imaging (fMRI) data to study the brain functions deals mainly with
two objectives: signal detection and extraction of the haemodynamic response. Signal detection consists of exploring
and detecting those areas of the brain that are triggered due to an external stimulus. Extraction of the haemodynamic
response deals with describing and measuring the physiological process of activated regions in the brain due to
stimulus. The haemodynamic response represents the change in oxygen levels since the brain functions require more
glucose and oxygen upon stimulus that implies a change in blood flow. In the literature, different approaches to estimate
and model the haemodynamic response have been proposed. These approaches can be discriminated in model
structures that either provide a proper representation of the obtained measurements but provide no or a limited amount
of physiological information, or provide physiological insight but lacks a proper fit to the data. In this paper, a novel
model structure is studied for describing the haemodynamics in fMRI measurements: fractional models. We show that



these models are flexible enough to describe the gathered data with the additional merit of providing physiological
information.

EGC
5214
Gaze Estimation Interpolation Methods Based on Binocular Data

In this paper, we study periodic query scheduling for data aggregation with minimum delay under various wireless
Video oculography (VOG) is one of the most commonly used techniques for gaze tracking because it enables
nonintrusive eye detection and tracking. Improving the eye tracking’s accuracy and tolerance to user head movements
is a common task in the field of gaze tracking; thus, a thorough study of how binocular information can improve a gaze
tracking system’s accuracy and tolerance to user head movements has been carried out. The analysis is focused on
interpolation-based methods and systems with one and two infrared lights. New mapping features are proposed based
on the commonly used pupil-glint vector using different distances as the normalization factor. For this study, an
experimental procedure with six users based on a real VOG gaze tracking system was performed, and the results were
contrasted with an eye simulator. Important conclusions have been obtained in terms of configuration, equation, and
mapping features, such as the outperformance of the interglint distance as the normalization factor. Furthermore, the
binocular gaze tracking system was found to have a similar or improved level of accuracy compared to that of the
monocular gaze tracking system.

EGC Heterogeneity of Intrinsic Repolarization Properties Within the Human Heart: New
5215
Insights From Simulated Three-Dimensional Current Surfaces

Heterogeneity of repolarization properties is pivotal for both physiology and pathology of the heart and mathematical
models of different cardiac cell types that are tuned to experimental data in order to reproduce it in silico. Repolarization
heterogeneity is described most of the times with reference to one or the other of the many repolarization parameters,
like action potential (AP) form and duration, or the maximum conductance of a given ion current, which are nonlinearly
connected and frequently overdetermined. A compact representation of models dynamics would help their
standardization, their use, and the understanding of the underlying physiology. A 3-D representation of cardiac AP
derived from the measure of instantaneous current–voltage relationships during repolarization has been previously
described. Here, it is shown that such a representation compactly summarizes important features of repolarization
which are relevant particularly for what concerns its electrotonic modulation within the human heart. It is found that,
according to the tested models, late phase of AP repolarization displays autoregenerativity only within the ventricle, and
that this property is heterogeneously distributed across the wall. Three-dimensional current representations of the AP
also provide precise estimation of the time course of membrane resistance, which changes throughout the heart, and
can be used to predict entrainment of repolarization during AP propagation.

EGC
Intention-Based EMG Control for Powered Exoskeletons
5216


Electromyographical (EMG) signals have been frequently used to estimate human muscular torques. In the field of
human-assistive robotics, these methods provide valuable information to provide effectively support to the user.
However, their usability is strongly limited by the necessity of complex user-dependent and session-dependent
calibration procedures, which confine their use to the laboratory environment. Nonetheless, an accurate estimate of
muscle torque could be unnecessary to provide effective movement assistance to users. The natural ability of human
central nervous system of adapting to external disturbances could compensate for a lower accuracy of the torque
provided by the robot and maintain the movement accuracy unaltered, while the effort is reduced. In order to explore
this possibility, in this paper we study the reaction of ten healthy subjects to the assistance provided through a
proportional EMG control applied by an elbow powered exoskeleton. This system gives only a rough estimate of the
user muscular torque but does not require any specific calibration. Experimental results clearly show that subjects
adapt almost instantaneously to the assistance provided by the robot and can reduce their effort while keeping full
control of the movement under different dynamic conditions (i.e., no alterations of movement accuracy are observed).

EGC
Mapping Infected Cell Phenotype
5217

Quantitative modeling of the phenotypic changes in the host cell during the bacterial infection makes it possible to
explore an empirical relation between the infection stages and the quantifiable host-cell phenotype. A statistically
reliable model of this relation can facilitate therapeutic defense against threats due to natural and genetically engineered
bacterium. In the preliminary experiment, we have collected several thousand cell images over a period of 72 h of
infection with a 2-h sampling frequency that covers various stages of infection by Francisella tularenesis (Ft).
Segmentation of macrophages in images was accomplished using a fully automatic, parallel region growing technique.
Over two thousand feature descriptors for the host cell were calculated. Multidimensional scaling, followed by
hierarchical clustering, was used to group the cells. Preliminary results show that the host-cell phenotype, as defined by
the set of measureable features, groups into different classes that can be mapped to the stages of infection.

EGC Multilead Measurement System for the Time-Domain Analysis of Bioimpedance
5218 Magnitude

Bioimpedance measurement applications range from the characterization of organic matter to the monitoring of
biological signals and physiological parameters. Occasionally, multiple bioimpedances measured in different locations
are combined in order to solve complex problems or produce enhanced physiological measures. The present multilead
bioimpedance measurement methods are mainly focused on electrical impedance tomography. Systems designed to
suit other multilead applications are lacking. In this study, a novel multilead bioimpedance measurement system was



designed. This was particularly aimed at the time-domain analysis of bioimpedance magnitude. Frequency division
multiplexing was used to avoid overlapping between excitation signals; undersampling, to reduce the hardware
requirements; and power isolated active current sources, to reduce the electrical interactions between leads. These
theoretical concepts were implemented on a prototype device. The prototype was tested on equivalent circuits and a
saline tank in order to assess excitation signal interferences and electrical interactions between leads. The results
showed that the proposed techniques are functional and the system’s validity was demonstrated on a real application,
multilead impedance pneumography. Potential applications and further improvements were discussed. It was concluded
that the novel approach potentially enables accurate and relatively low-power multilead bioimpedance measurements
systems.

EGC Noninvasive Measurement of Physiological Signals on a Modified Home Bathroom Scale
5219

A commercial bathroom scale with both handlebar and footpad electrodes was modified to enable measurement of four
physiological signals: the ballistocardiogram (BCG), electrocardiogram (ECG), lower body impedance plethysmogram
(IPG), and lower body electromyogram (EMG). The BCG, which describes the reaction of the body to cardiac ejection of
blood, was measured using the strain gauges in the scale. The ECG was detected using handlebar electrodes with a two-
electrode amplifier. For the lower body IPG, the two electrodes under the subject's toes were driven with an ac current
stimulus, and the resulting differential voltage across the heels was measured and demodulated synchronously with the
source. The voltage signal from the same two footpad electrodes under the heels was passed through a passive low-
pass filter network into another amplifier, and the output was the lower body EMG signal. The signals were measured
from nine healthy subjects, and the average signal-to-noise ratio (SNR) while the subjects were standing still was
estimated for the four signals as follows: BCG, 7.6 dB; ECG, 15.8 dB; IPG, 10.7 dB. During periods of motion, the
decrease in SNR for the BCG signal was found to be correlated to the increase in rms power for the lower body EMG (r =
0.89, p < 0.01). The EMG could, thus, be used to flag noise-corrupted segments of the BCG, increasing the measurement
robustness. This setup could be used for monitoring the cardiovascular health of patients at home.

EGC Novel Passive Element Circuits for Microdosimetry of Nanosecond Pulsed Electric Fields
5220

Microdosimetric models for biological cells have assumed increasing significance in the development of nanosecond
pulsed electric field technology for medical applications. In this paper, novel passive element circuits, able to take into
account the dielectric dispersion of the cell, are provided. The circuital analyses are performed on a set of input pulses
classified in accordance with the current literature. Accurate data in terms of transmembrane potential are obtained in
both time and frequency domains for different cell models. In addition, a sensitivity study of the transfer function for the



cell geometrical and dielectric parameters has been carried out. This analysis offers a new, simple, and efficient tool to
characterize the nsPEFs’ action at the cellular level.

EGC Online Removal of Eye Movement and Blink EEG Artifacts Using a High-Speed Eye
5221
Tracker

Route A novel approach is presented for using an eye tracker-based reference instead of EOG for methods that require
an EOG reference to remove ocular artifacts (OA) from EEG. It uses a high-speed eye tracker and a new online algorithm
for extracting the time course of a blink from eye tracker images to remove both eye movement and blink artifacts. It
eliminates the need for EOG electrodes attached to the face, which is critical for practical daily applications. The ability
of two adaptive filters (RLS and H$^infty$ ) to remove OA is measured using: 1) EOG; 2) frontal EEG only (fEEG); and 3)
the eye tracker with frontal EEG (ET + fEEG) as reference inputs. The results are compared for different eye movements
and blinks of varying amplitudes at electrodes across the scalp. Both the RLS and H$^infty$ methods were shown to
benefit from using the proposed eye tracker-based reference (ET + fEEG) instead of either an EOG reference or a
reference based on frontal EEG alone.

EGC Phase Synchronization Analysis of EEG Signals: An Evaluation Based on Surrogate
5222
Tests

Phase synchronization (PS) analysis has been demonstrated to be a useful method to infer functional connectivity with
multichannel neural signals, e.g., electroencephalography (EEG). Methodological problems on quantifying functional
connectivity with PS analysis have been investigated extensively, but some of them have not been fully solved yet. For
example, how long a segment of EEG signal should be used in estimating PS index? Which methods are more suitable
to infer the significant level of estimated PS index? To address these questions, this paper performs an intensive
computation study on PS analysis based on surrogate tests with 1) artificial surrogate data generated by shuffling the
rank order, the phase spectra, or the instantaneous frequency of original EEG signals, and 2) intersubject EEG pairs
under the assumption that the EEG signals of different subjects are independent. Results show that 1) the phase-
shuffled surrogate method is workable for significance test of estimated PS index and yields results similar to those by
intersubject EEG surrogate test; 2) generally, a duration of EEG waves covering about $3sim 16$ cycles is suitable for
PS analysis; and 3) the PS index based on mean phase coherence is more suitable for PS analysis of EEG signals
recorded at relatively low sampling rate.

EGC Points of Interest and Visual Dictionaries for Automatic Retinal Lesion Detection
5223



The In this paper, we present an algorithm to detect the presence of diabetic retinopathy (DR)-related lesions from
fundus images based on a common analytical approach that is capable of identifying both red and bright lesions without
requiring specific pre- or postprocessing. Our solution constructs a visual word dictionary representing points of
interest (PoIs) located within regions marked by specialists that contain lesions associated with DR and classifies the
fundus images based on the presence or absence of these PoIs as normal or DR-related pathology. The novelty of our
approach is in locating DR lesions in the optic fundus images using visual words that combines feature information
contained within the images in a framework easily extendible to different types of retinal lesions or pathologies and
builds a specific projection space for each class of interest (e.g., white lesions such as exudates or normal regions)
instead of a common dictionary for all classes. The visual words dictionary was applied to classifying bright and red
lesions with classical cross validation and cross dataset validation to indicate the robustness of this approach. We
obtained an area under the curve (AUC) of 95.3% for white lesion detection and an AUC of 93.3% for red lesion detection
using fivefold cross validation and our own data consisting of 687 images of normal retinae, 245 images with bright
lesions, 191 with red lesions, and 109 with signs of both bright and red lesions. For cross dataset analysis, the visual
dictionary also achieves compelling results using our images as the training set and the RetiDB and Messidor images as
test sets. In this case, the image classification resulted in an AUC of 88.1% when classifying the RetiDB dataset and in
an AUC of 89.3% when classifying the Messidor dataset, both cases for bright lesion detection. The results indicate the
potential for training with different acquisition images under different setup con- itions with a high accuracy of referral
based on the presence of either red or bright lesions or both. The robustness of the visual dictionary against image
quality (blurring), resolution, and retinal background, makes it a strong candidate for DR screening of large, diverse
communities with varying cameras and settings and levels of expertise for image capture.

EGC
5224
Robust Closed-Loop Minimal Sampling Method for HIV Therapy Switching Strategies

Abstract— The emergence of drug-resistant strains of human immunodeficiency virus during antiretroviral therapy is a
major cause of treatment failure and disease progression. Development of a resistant strain necessitates switching to a
new antiretroviral regimen composed of novel drugs. Recent work has shown that current methods of switching antiviral
therapies carry significant unnecessary risk of subsequent failures, and optimal switching schedules to minimize this
risk have been proposed. These switching schedules require frequent sampling of viral load during an induced phase of
transient viral load reduction, with the goal of switching to the new antiviral regimen at an induced viral load minimum.
The proposed frequent sampling carries an unacceptable level of cost both in terms of measurement expense and
inconvenience to the patient. In this paper, we propose a closed-loop sampling algorithm to reduce the number of
samples required to achieve the desired reduction in risk. We demonstrate through the Monte-Carlo analysis that the
proposed method is able to robustly achieve an average 50% reduction in the number of required samples while
maintaining a reduction in the risk of subsequent failure to under 3%, despite experimentally verified levels of model and
measurement uncertainty



EGC Points of Interest and Visual Dictionaries for Automatic Retinal Lesion Detection
5225

In this paper, we present an algorithm to detect the presence of diabetic retinopathy (DR)-related lesions from fundus
images based on a common analytical approach that is capable of identifying both red and bright lesions without
requiring specific pre- or postprocessing. Our solution constructs a visual word dictionary representing points of
interest (PoIs) located within regions marked by specialists that contain lesions associated with DR and classifies the
fundus images based on the presence or absence of these PoIs as normal or DR-related pathology. The novelty of our
approach is in locating DR lesions in the optic fundus images using visual words that combines feature information
contained within the images in a framework easily extendible to different types of retinal lesions or pathologies and
builds a specific projection space for each class of interest (e.g., white lesions such as exudates or normal regions)
instead of a common dictionary for all classes. The visual words dictionary was applied to classifying bright and red
lesions with classical cross validation and cross dataset validation to indicate the robustness of this approach. We
obtained an area under the curve (AUC) of 95.3% for white lesion detection and an AUC of 93.3% for red lesion detection
using fivefold cross validation and our own data consisting of 687 images of normal retinae, 245 images with bright
lesions, 191 with red lesions, and 109 with signs of both bright and red lesions. For cross dataset analysis, the visual
dictionary also achieves compelling results using our images as the training set and the RetiDB and Messidor images as
test sets. In this case, the image classification resulted in an AUC of 88.1% when classifying the RetiDB dataset and in
an AUC of 89.3% when classifying the Messidor dataset, both cases for bright lesion detection. The results indicate the
potential for training with different acquisition images under different setup con- itions with a high accuracy of referral
based on the presence of either red or bright lesions or both. The robustness of the visual dictionary against image
quality (blurring), resolution, and retinal background, makes it a strong candidate for DR screening of large, diverse
communities with varying cameras and settings and levels of expertise for image capture.

EGC Slip Speed Feedback for Grip Force Control
5226

Grasp stability in the human hand has been resolved by means of an intricate network of mechanoreceptors integrating
numerous cues about mechanical events, through an ontogenetic grasp practice. An engineered prosthetic interface
introduces considerable perturbation risks in grasping, calling for feedback modalities that address the underlying slip
phenomenon. In this study, we propose an enhanced slip feedback modality, with potential for myoelectric-based
prosthetic applications that relays information regarding slip events, particularly slip occurrence and slip speed. The
proposed feedback modality, implemented using electrotactile stimulation, was evaluated in psychophysical studies of
slip control in a simplified setup. The obtained results were compared with vision and a binary slip feedback that
transmits on–off information about slip detection. The slip control efficiency of the slip speed display is comparable to
that obtained with vision feedback, and it clearly outperforms the efficiency of the on–off slip modality in such tasks.
These results suggest that the proposed tactile feedback is a promising sensory method for the restoration of stable
grasp in prosthetic applications.



EGC
5227
Uncertainty Analysis of Ventricular Mechanics Using the Probabilistic Collocation Method

Uncertainty and variability in material parameters are fundamental challenges in computational biomechanics. Analyzing
and quantifying the resulting uncertainty in computed results with parameter sweeps or Monte Carlo methods has
become very computationally demanding. In this paper, we consider a stochastic method named the probabilistic
collocation method, and investigate its applicability for uncertainty analysis in computing the passive mechanical
behavior of the left ventricle. Specifically, we study the effect of uncertainties in material input parameters upon
response properties such as the increase in cavity volume, the elongation of the ventricle, the increase in inner radius,
the decrease in wall thickness, and the rotation at apex. The numerical simulations conducted herein indicate that the
method is well suited for the problem of consideration, and is far more efficient than the Monte Carlo simulation method
for obtaining a detailed uncertainty quantification. The numerical experiments also give interesting indications on which
material parameters are most critical for accurately determining various global responses.

EGC Variation of Respiratory Resistance Suggests Optimization of Airway Caliber
5228

Physiologically optimized processes, such as respiration, walking, and cardiac function, usually show a range of
variability about the optimized value. Airway resistance has, in the past, been noted as variable, and this variability has
been connected to pulmonary disease (e.g., asthma). A hypothesis was presented many years ago that postulated
airway resistance as an optimized parameter in healthy individuals, and we have noticed that respiratory measurements
made with the airflow perturbation device (APD) tend to be variable in nature. It was posited that this variability indicates
that respiratory resistance is optimized similarly to other physiological processes. Fifty subjects with a wide range of
demographics volunteered to have 100 measurements made of their respiratory resistances. Resistances were
separated into inhalation and exhalation phases. These were plotted and shown to have frequency distributions that
were consistent with expectations for an optimized process. The frequency distributions were not quite symmetrical,
being skewed slightly toward upper resistances. Comparison between subject data and data from a mechanical
respiratory analog showed that subject resistance variation is overwhelmingly from the respiratory system and not from
the APD.

EGC Vibro- and Electrotactile User Feedback on Hand Opening for Myoelectric Forearm
5229 Prostheses



Many of the currently available myoelectric forearm prostheses stay unused because of the lack of sensory feedback.
Vibrotactile and electrotactile stimulation have high potential to provide this feedback. In this study, performance of a
grasping task is investigated for different hand opening feedback conditions on 15 healthy subjects and validated on
three patients. The opening of a virtual hand was controlled by a scroll wheel. Feedback about hand opening was given
via an array of eight vibrotactile or electrotactile stimulators placed on the forearm, relating to eight hand opening
positions. A longitudinal and transversal orientation of the array and four feedback conditions were investigated: no
feedback, visual feedback, feedback through vibrotactile or electrotactile stimulation, and addition of an extra stimulator
for touch feedback. No influence of array orientation was shown for all outcome parameters (duration of the task, the
percentage of correct hand openings, the mean position error, and the percentage deviations up to one position).
Vibrotactile stimulation enhances the performance compared to the nonfeedback conditions. The addition of touch
feedback further increases the performance, but at the cost of an increased duration. The same effects were found for
the patient group, but the task duration was around 25% larger.

EGC
Vision-Based Proximity Detection in Retinal Surgery
5230

In retinal surgery, surgeons face difficulties such as indirect visualization of surgical targets, physiological tremor, and
lack of tactile feedback, which increase the risk of retinal damage caused by incorrect surgical gestures. In this context,
intraocular proximity sensing has the potential to overcome current technical limitations and increase surgical safety. In
this paper, we present a system for detecting unintentional collisions between surgical tools and the retina using the
visual feedback provided by the opthalmic stereo microscope. Using stereo images, proximity between surgical tools
and the retinal surface can be detected when their relative stereo disparity is small. For this purpose, we developed a
system comprised of two modules. The first is a module for tracking the surgical tool position on both stereo images.
The second is a disparity tracking module for estimating a stereo disparity map of the retinal surface. Both modules
were specially tailored for coping with the challenging visualization conditions in retinal surgery. The potential clinical
value of the proposed method is demonstrated by extensive testing using a silicon phantom eye and recorded rabbit in
vivo data.

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Ieee projects 2012 2013 - Bio Medical

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Ieee projects 2012 2013 - Bio Medical