Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract

Elysium Technologies Private Limited
Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad |
Pondicherry | Trivandrum | Salem | Erode | Tirunelveli
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ETPL
BME-001
Convolving Engineering and Medical Pedagogies for Training of Tomorrow's Health
Care Professionals
Abstract: Several fundamental benefits justify why biomedical engineering and medicine should form a
more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers.
Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the
era of molecular biology well into today's era of molecular systems biology, which focuses on
understanding the rules that govern the behavior of complex living systems. This has important medical
implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in
molecular systems biology to higher levels of biological organization (organ, system, and organismal
levels) and then to develop new medical therapeutics based on simulation and medical informatics
analysis. Higher education in biological and medical sciences must adapt to a new set of training
objectives. This will involve a shifting away from reductionist problem solving toward more integrative,
continuum, and predictive modeling approaches which traditionally have been more associated with
engineering science. Future biomedical engineers and MDs must be able to predict clinical response to
therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing
rules of complex system behavior and skill sets in manipulating these systems to achieve a practical
desired outcome are taught. Similarly, graduate biomedical engineering programs will include more
practical exposure to clinical problem solving.
ETPL
BME-002
Accurate Dialysis Dose Evaluation and Extrapolation Algorithms During Online
Optical Dialysis Monitoring
Abstract: The aim of this study was to propose an improved method for accurate dialysis dose evaluation
and extrapolation by means of Kt/$V$ from online UV-absorbance measurements for real time and
continuous treatment monitoring. The study included a total of 24 treatments from ten uremic patients,
seven of whom were male and three females. All patients were on chronic thrice-weekly hemodialysis
therapy. The study included both stable and unstable treatments. A known signal processing algorithm,
Levenberg–Marquardt, and the newly developed SMART were utilized for the removal of disturbances
not relevant for dialysis dose evaluation. Finally, the results were compared with the Kt/$V$ values based
on the blood samples. The new data processing algorithm, SMART, removes disturbances, helps estimate
the online Kt/$V$ with significant precision increase and without any time delay, and more effectively
predicts the end Kt/$V$ for the treatment than the known algorithms.
ETPL
BME-003
Toward Robot-Assisted Neurosurgical Lasers
Abstract: Despite the potential increase in precision and accuracy, laser technology is not widely used in
neurological surgery. This in part relates to challenges associated with the early introduction of lasers into
neurosurgery. Considerable advances in laser technology have occurred, which together with robotic
technology could create an ideal platform for neurosurgical application. In this study, a 980-nm contact
diode laser was integrated with neuroArm. Preclinical evaluation involved partial hepatectomy, bilateral

nephrectomy, splenectomy, and bilateral submandibular gland excision in a Sprague-Dawley rat model (n
= 50). Total surgical time, blood loss as weight of surgical gauze before and after the procedure, and the
incidence of thermal, vascular, or lethal injury were recorded and converted to an overall performance
score. Thermal damage was evaluated in the liver using tissue samples stained with hematoxylin and
eosin. Clinical studies involved step-wise integration of the 980-nm laser system into four neurosurgical
cases. Results demonstrate the successful integration of contact laser technology into microsurgery, with
and without robotic assistance. In preclinical studies, the laser improved microsurgical performance and
reduced thermal damage, while neuroArm decreased intra- and intersurgeon variability. Clinical studies
demonstrate dutility in meningioma resection (n = 4). Together, laser and robotic technology offered a
more consistent, expedient, and precise tool for microsurgery.
ETPL
BME-004
Relevance of Laser Doppler and Laser Speckle Techniques for Assessing Vascular
Function: State of the Art and Future Trend
Abstract: In clinical and research applications, the assessment of vascular function has become of major
importance to evaluate and follow the evolution of cardiovascular pathologies, diabetes, hypertension, or
foot ulcers. Therefore, the development of engineering methodologies able to monitor noninvasively
blood vessel activities-such as endothelial function-is a significant and emerging challenge. Laser-based
techniques have been used to respond-as much as possible-to these requirements. Among them, laser
Doppler flowmetry (LDF) and laser Doppler imaging (LDI) were proposed a few decades ago. They
provide interesting vascular information but possess drawbacks that prevent an easy use in some clinical
situations. Recently, the laser speckle contrast imaging (LSCI) technique, a noninvasive camera-based
tool, was commercialized and overcomes some of the LDF and LDI weaknesses. Our paper describes
how-using engineering methodologies-LDF, LDI, and LSCI can meet the challenging clinician needs in
assessing vascular function, with a special focus on the state of the art and future trends.
ETPL
BME-005
Quantitative Analysis of Locomotive Behavior of Human Sperm Head and Tail
Abstract: Sperm selection plays a significant role in in vitro fertilization (IVF). Approaches for assessing
sperm quality include noninvasive techniques based on sperm morphology and motility as well as
invasive techniques for checking DNA integrity. In 2006, a new device using hyaluronic acid (HA)-
coated dish for sperm selection was cleared by the Food and Drug Administration (FDA) and entered IVF
clinics. In this technique, only sperms with DNA integrity bind to the HA droplet, after which these
bound sperm stop revealing head motion and their tail movement becomes more vigorous. However,
selecting a single sperm cell from among HA-bound sperms is ad hoc in IVF clinics. Different from
existing sperm tracking algorithms that are largely limited to tracking sperm head only and are only able
to track one sperm at a time, this paper presents a multisperm tracking algorithm that tracks both sperm
heads and low-contrast sperm tails. The tracking results confirm a significant correlation between sperm
head velocity and tail beating amplitude, demonstrate that sperms bound to HA generally have a higher
velocity (before binding) than those sperms that are not able to bind to HA microdots, and quantitatively
reveal that HA-bound sperms' tail beating amplitudes are different among HA-bound sperms.

ETPL
BME-006
Grand Challenge: Applying Regulatory Science and Big Data to Improve Medical
Device Innovation
Abstract: Understanding how proposed medical devices will interface with humans is a major challenge
that impacts both the design of innovative new devices and approval and regulation of existing devices.
Today, designing and manufacturing medical devices requires extensive and expensive product cycles.
Bench tests and other preliminary analyses are used to understand the range of anatomical conditions, and
animal and clinical trials are used to understand the impact of design decisions upon actual device
success. Unfortunately, some scenarios are impossible to replicate on the bench, and competitive
pressures often accelerate initiation of animal trials without sufficient understanding of parameter
selections. We believe that these limitations can be overcome through advancements in data-driven and
simulation-based medical device design and manufacturing, a research topic that draws upon and
combines emerging work in the areas of Regulatory Science and Big Data. We propose a cross-
disciplinary grand challenge to develop and holistically apply new thinking and techniques in these areas
to medical devices in order to improve and accelerate medical device innovation.
ETPL
BME-007
Coaxial Needle Insertion Assistant With Enhanced Force Feedback
Abstract: Many medical procedures involving needle insertion into soft tissues, such as anesthesia,
biopsy, brachytherapy, and placement of electrodes, are performed without image guidance. In such
procedures, haptic detection of changing tissue properties at different depths during needle insertion is
important for needle localization and detection of subsurface structures. However, changes in tissue
mechanical properties deep inside the tissue are difficult for human operators to sense, because the
relatively large friction force between the needle shaft and the surrounding tissue masks the smaller tip
forces. A novel robotic coaxial needle insertion assistant, which enhances operator force perception, is
presented. This one-degree-of-freedom cable-driven robot provides to the operator a scaled version of the
force applied by the needle tip to the tissue, using a novel design and sensors that separate the needle tip
force from the shaft friction force. The ability of human operators to use the robot to detect membranes
embedded in artificial soft tissue was tested under the conditions of 1) tip force and shaft force feedback,
and 2) tip force only feedback. The ratio of successful to unsuccessful membrane detections was
significantly higher (up to 50%) when only the needle tip force was provided to the user.
ETPL
BME-008
Reducing False Intracranial Pressure Alarms Using Morphological Waveform
Features
Abstract: False alarms produced by patient monitoring systems in intensive care units are a major issue
that causes alarm fatigue, waste of human resources, and increased patient risks. While alarms are
typically triggered by manually adjusted thresholds, the trend and patterns observed prior to threshold
crossing are generally not used by current systems. This study introduces and evaluates, a smart alarm
detection system for intracranial pressure signal (ICP) that is based on advanced pattern recognition
methods. Models are trained in a supervised fashion from a comprehensive dataset of 4791 manually

labeled alarm episodes extracted from 108 neurosurgical patients. The comparative analysis provided
between spectral regression, kernel spectral regression, and support vector machines indicates the
significant improvement of the proposed framework in detecting false ICP alarms in comparison to a
threshold-based technique that is conventionally used. Another contribution of this work is to exploit an
adaptive discretization to reduce the dimensionality of the input features. The resulting features lead to a
decrease of 30% of false ICP alarms without compromising sensitivity.
ETPL
BME-009
Grand Challenges in Bioengineered Nanorobotics for Cancer Therapy
Abstract: One of the grand challenges currently facing engineering, life sciences, and medicine is the
development of fully functional nanorobots capable of sensing, decision making, and actuation. These
nanorobots may aid in cancer therapy, site-specific drug delivery, circulating diagnostics, advanced
surgery, and tissue repair. In this paper, we will discuss, from a bioinspired perspective, the challenges
currently facing nanorobotics, including core design, propulsion and power generation, sensing, actuation,
control, decision making, and system integration. Using strategies inspired from microorganisms, we will
discuss a potential bioengineered nanorobot for cancer therapy.
ETPL
BME-010
Neuromodulation for Brain Disorders: Challenges and Opportunities
Abstract: The field of neuromodulation encompasses a wide spectrum of interventional technologies that
modify pathological activity within the nervous system to achieve a therapeutic effect. Therapies
including deep brain stimulation, intracranial cortical stimulation, transcranial direct current stimulation,
and transcranial magnetic stimulation have all shown promising results across a range of neurological and
neuropsychiatric disorders. While the mechanisms of therapeutic action are invariably different among
these approaches, there are several fundamental neuroengineering challenges that are commonly
applicable to improving neuromodulation efficacy. This paper reviews the state-of-the-art of
neuromodulation for brain disorders and discusses the challenges and opportunities available for
clinicians and researchers interested in advancing neuromodulation therapies.
ETPL
BME-011
Minimizing Cytosol Dilution in Whole-Cell Patch-Clamp Experiments
Abstract: During a conventional whole-cell patch clamp experiment, diffusible cytosolic ions or
molecules absent in the pipette solution can become diluted by a factor of one million or more, leading to
diminished current or fluorescent signals. Existing methods to prevent or limit cytosol diffusion include
reducing the diameter of the pipette's orifice, adding cytosolic extract or physiological entities to the
pipette solution, and using the perforated patch clamp configuration. The first method introduces
measurement error in recorded signals from increased series resistance and the latter two are cumbersome
to perform. In addition, most perforated patch configurations, prevent investigators from using test
compounds in the pipette solution. We present a method to overcome these limitations by minimizing

cytosol dilution using a novel pipette holder. Cell-attached configuration is obtained with the pipette filled
with pipette solution. Most of the pipette solution is then replaced with mineral oil so that cytosol dilution
can be minimized in whole-cell configuration. To accomplish this requires a suction line and two
Ag/AgCl electrodes inside the pipette. Testing our novel pipette holder with Chinese Hamster Ovarian
cells, we demonstrate cytosol dilution factors between 76 and 234. For large cells with somas greater than
40 μm, cytosol dilution factors of 10 or less are achievable.
ETPL
BME-012
Engineering Stem Cells For Future Medicine
Abstract: Despite their great potential in regenerative medicine applications, stem cells (especially
pluripotent ones) currently show a limited clinical success, partly due to a lack of biological knowledge,
but also due to a lack of specific and advanced technological instruments able to overcome the current
boundaries of stem cell functional maturation and safe/effective therapeutic delivery. This paper aims at
describing recent insights, current limitations, and future horizons related to therapeutic stem cells, by
analyzing the potential of different bioengineering disciplines in bringing stem cells toward a safe clinical
use. First, we clarify how and why stem cells should be properly engineered and which could be in a near
future the challenges and the benefits connected with this process. Second, we identify different routes
toward stem cell differentiation and functional maturation, relying on chemical, mechanical,
topographical, and direct/indirect physical stimulation. Third, we highlight how multiscale modeling
could strongly support and optimize stem cell engineering. Finally, we focus on future robotic tools that
could provide an added value to the extent of translating basic biological knowledge into clinical
applications, by developing ad hoc enabling technologies for stem cell delivery and control.
ETPL
BME-013
Surgical Robotics Through a Keyhole: From Today's Translational Barriers to
Tomorrow's ―Disappearing‖ Robots,
Abstract: In the last century, engineering advances have transformed the practice of surgery. Keyhole
surgical techniques offer a number of advantages over traditional open approaches including less
postoperative pain, fewer wound complications, and reduced length of stay in hospital. However, they
also present considerable technical challenges, particularly to surgeons performing new operative
approaches, such as those through natural orifices. Advances in surgical robots have improved surgical
visualization, dexterity, and manipulation consistency, thus greatly enhancing surgical performance and
patient care. Clinically, however, robotic surgery is still in its infancy, and its use has remained limited to
relatively few operations. In the paper, we will discuss the economic-, clinical-, and research-related
factors that may act as barriers to the widespread utilization and development of surgical robots. In
overcoming these barriers through a synergistic effort of both engineering and medicine, we highlight our
future vision of robotic surgery, in both the short and long term.
ETPL
BME-014
Continuous Detection of Muscle Aspect Ratio Using Keypoint Tracking in
Ultrasonography

Abstract: Muscle aspect ratio of cross-sectional area is one of the most widely used parameters for
quantifying muscle function in both diagnosis and rehabilitation assessment. Ultrasound imaging has been
frequently used to noninvasively study the characteristics of human muscles as a reliable method.
However, the aspect ratio measurement is traditionally conducted by the manual digitization of reference
points; thus, it is subjective, time-consuming, and prone to errors. In this paper, a novel method is
proposed to continuously detect the muscle aspect ratio. Two keypoint pairs are manually digitized on the
lateral and longitudinal borders at the first frame, and automatically tracked by an optical flow technique
at the subsequent frames. The muscle aspect ratio is thereby obtained based on the estimated muscle
width and thickness. Six ultrasound sequences from different subjects are used to evaluate this method,
and the overall coefficient of multiple correlation of the results between manual and proposed methods is
0.97 ± 0.02. The linear regression shows that a good linear correlation
ETPL
BME-015
Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast
Cancer From Entire Histopathology Slides
Abstract: Modified Bloom–Richardson (mBR) grading is known to have prognostic value in breast cancer
(BCa), yet its use in clinical practice has been limited by intra- and interobserver variability. The
development of a computerized system to distinguish mBR grade from entire estrogen receptor-positive
(ER+) BCa histopathology slides will help clinicians identify grading discrepancies and improve overall
confidence in the diagnostic result. In this paper, we isolate salient image features characterizing tumor
morphology and texture to differentiate entire hematoxylin and eosin (H and E) stained histopathology
slides based on mBR grade. The features are used in conjunction with a novel multi-field-of-view (multi-
FOV) classifier—a whole-slide classifier that extracts features from a multitude of FOVs of varying
sizes—to identify important image features at different FOV sizes. Image features utilized include those
related to the spatial arrangement of cancer nuclei (i.e., nuclear architecture) and the textural patterns
within nuclei (i.e., nuclear texture). Using slides from 126 ER+ patients (46 low, 60 intermediate, and 20
high mBR grade), our grading system was able to distinguish low versus high, low versus intermediate,
and intermediate versus high grade patients with area under curve values of 0.93, 0.72, and 0.74,
respectively. Our results suggest that the multi-FOV classifier is able to 1) successfully discriminate low,
medium, and high mBR grade and 2) identify specific image features at different FOV sizes that are
important for distinguishing mBR grade in H and E stained ER+ BCa histology slides.
ETPL
BME-016
Simplified Design Equations for Class-E Neural Prosthesis Transmitters
Abstract: Extreme miniaturization of implantable electronic devices is recognized as essential for the next
generation of neural prostheses, owing to the need for minimizing the damage and disruption of the
surrounding neural tissue. Transcutaneous power and data transmission via a magnetic link remains the
most effective means of powering and controlling implanted neural prostheses. Reduction in the size of
the coil, within the neural prosthesis, demands the generation of a high-intensity radio frequency magnetic
field from the extracoporeal transmitter. The Class-E power amplifier circuit topology has been

recognized as a highly effective means of producing large radio frequency currents within the transmitter
coil. Unfortunately, design of a Class-E circuit is most often fraught by the need to solve a complex set of
equations so as to implement both the zero-voltage-switching and zero-voltage-derivative-switching
conditions that are required for efficient operation. This paper presents simple explicit design equations
for designing the Class-E circuit topology. Numerical design examples are presented to illustrate the
design procedure.
ETPL
BME-017
A 3-D Reconstruction Solution to Current Density Imaging Based on Acoustoelectric
Effect by Deconvolution: A Simulation Study
Abstract: Hybrid imaging modality combining ultrasound scanning and electrical current density imaging
through the acoustoelectric (AE) effect may potentially provide solutions to imaging electrical activities
and properties of biological tissues with high spatial resolution. In this study, a 3-D reconstruction
solution to ultrasound current source density imaging (UCSDI) by means of Wiener deconvolution is
proposed and evaluated through computer simulations. As compared to previous 2-D UCSDI problem, in
a 3-D volume conductor with broadly distributed current density field, the AE signal becomes a 3-D
convolution between the electric field and the acoustic field, and effective 3-D reconstruction algorithm
has not been developed so far. In the proposed method, a 3-D ultrasound scanning is performed while the
corresponding AE signals are collected from multiple electrode pairs attached on the surface of the
imaging object. From the collected AE signals, the acoustic field and electric field were first decoupled by
Wiener deconvolution. Then, the current density distribution was reconstructed by inverse projection. Our
simulations using artificial current fields in homogeneous phantoms suggest that the proposed method is
feasible and robust against noise. It is also shown that using the proposed method, it is feasible to
reconstruct 3-D current density distribution in an inhomogeneous conductive medium.
ETPL
BME-018
Applying Combined Optical Tweezers and Fluorescence Microscopy Technologies to
Manipulate Cell Adhesions for Cell-to-Cell Interaction Study
Abstract: Cell-to-cell interactions are important for the regulation of various cell activities, such as
proliferation, differentiation, and apoptosis. This paper presents an approach to studying cell-to-cell
interactions at a single-cell level through manipulating cell adhesions with optical tweezers. Experiments
are performed on leukemia cancer cells and stromal cells to demonstrate the feasibility of this method.
After the adhesion properties of leukemia cells on stromal cells are characterized, fluorescence intensity is
used as a label to study the Wnt signaling pathway of leukemia cells. The activities of the Wnt signaling
pathway of K562 cells on M210B4 and HS5 cells are examined based on fluorescence analysis. The
reliability of the fluorescence imaging is confirmed through comparison with traditional flow cytometry
analysis. The proposed approach will offer new avenues to investigate otherwise inaccessible mechanisms
in cell-to-cell interactions.
ETPL
BME-019
Far-Field RF Powering of Implantable Devices: Safety Considerations

Abstract: Far-field RF powering is an attractive solution to the challenge of remotely powering devices
implanted in living tissue. The purpose of this study is to characterize the peak obtainable power levels in
a wireless myoelectric sensor implanted in a patient while maintaining safe local temperature and RF
powering conditions. This can serve as a guide for the design of onboard electronics in related medical
implants and provide motivation for more efficient power management strategies for implantable
integrated circuits. Safe powering conditions and peak received power levels are established using a
simplified theoretical analysis and Federal Communications Commission-established limits for radiating
antennas. These conditions are subsequently affirmed and improved upon using the finite-element method
and temperature modeling in bovine muscle.
ETPL
BME-020
Blood Perfusion Values of Laser Speckle Contrast Imaging and Laser Doppler
Flowmetry: Is a Direct Comparison Possible?
Abstract: Laser Doppler flowmetry (LDF) and laser speckle contrast imaging (LSCI) allow the
monitoring of microvascular blood perfusion. The relationship between the measurements obtained by
these two techniques remains unclear. In the present contribution, we demonstrate, experimentally and
theoretically, that skin blood flow measurements obtained by LDF and LSCI techniques cannot be
compared directly even after ―classical‖ normalization procedure. This technical problem is generated by
the nonlinear relationship existing between LDF and LSCI flow data. The experiments have been
performed on five healthy voluntary subjects (forearm) by using repeated ischemia/reperfusion cycles to
induce the necessary skin blood flow changes. LDF and LSCI data were simultaneously acquired on the
same region of interest. Considering the importance of this problem from the clinical point of view, it is
concluded that the definition of new corrected algorithms for LSCI is probably a mandatory step that must
be taken into account if LDF and LSCI blood flow have to be compared.
ETPL
BME-021
Assessing the Effects of Pharmacological Agents on Respiratory Dynamics Using Time-
Series Modeling
Abstract: Developing quantitative descriptions of how stimulant and depressant drugs affect the
respiratory system is an important focus in medical research. Respiratory variables-respiratory rate, tidal
volume, and end tidal carbon dioxide-have prominent temporal dynamics that make it inappropriate to use
standard hypothesis-testing methods that assume independent observations to assess the effects of these
pharmacological agents. We present a polynomial signal plus autoregressive noise model for analysis of
continuously recorded respiratory variables. We use a cyclic descent algorithm to maximize the
conditional log likelihood of the parameters and the corrected Akaike's information criterion to choose
simultaneously the orders of the polynomial and the autoregressive models. In an analysis of respiratory
rates recorded from anesthetized rats before and after administration of the respiratory stimulant
methylphenidate, we use the model to construct within-animal z-tests of the drug effect that take account
of the time-varying nature of the mean respiratory rate and the serial dependence in rate measurements.
We correct for the effect of model lack-of-fit on our inferences by also computing bootstrap confidence
intervals for the average difference in respiratory rate pre- and postmethylphenidate treatment. Our time-

series modeling quantifies within each animal the substantial increase in mean respiratory rate and
respiratory dynamics following methylphenidate administration. This paradigm can be readily adapted to
analyze the dynamics of other respiratory variables before and after pharmacologic treatments.
ETPL
BME-022
2-D–3-D Frequency Registration Using a Low-Dose Radiographic System for Knee
Motion Estimation
Abstract: In this paper, a new method is presented to study the feasibility of the pose and the position
estimation of bone structures using a low-dose radiographic system, the entrepreneurial operating system
(designed by EOS-Imaging Company). This method is based on a 2-D-3-D registration of EOS bi-planar
X-ray images with an EOS 3-D reconstruction. This technique is relevant to such an application thanks to
the EOS ability to simultaneously make acquisitions of frontal and sagittal radiographs, and also to
produce a 3-D surface reconstruction with its attached software. In this paper, the pose and position of a
bone in radiographs is estimated through the link between 3-D and 2-D data. This relationship is
established in the frequency domain using the Fourier central slice theorem. To estimate the pose and
position of the bone, we define a distance between the 3-D data and the radiographs, and use an iterative
optimization approach to converge toward the best estimation. In this paper, we give the mathematical
details of the method. We also show the experimental protocol and the results, which validate our
approach.
ETPL
BME-023
The Transesophageal Echocardiography Simulator Based on Computed Tomography
Images
Abstract: Simulators are a new tool in education in many fields, including medicine, where they greatly
improve familiarity with medical procedures, reduce costs, and, importantly, cause no harm to patients.
This is so in the case of transesophageal echocardiography (TEE), in which the use of a simulator
facilitates spatial orientation and helps in case studies. The aim of the project described in this paper is to
simulate an examination by TEE. This research makes use of available computed tomography data to
simulate the corresponding echocardiographic view. This paper describes the essential characteristics that
distinguish these two modalities and the key principles of the wave phenomena that should be considered
in the simulation process, taking into account the conditions specific to the echocardiography. The
construction of the CT2TEE (Web-based TEE simulator) is also presented. The considerations include
ray-tracing and ray-casting techniques in the context of ultrasound beam and artifact simulation. An
important aspect of the interaction with the user is raised.
ETPL
BME-024
Quantitative Evaluation of Two-Factor Analysis Applied to Hepatic Perfusion Study
Using Contrast-enhanced Ultrasound,
Abstract: Focal liver lesions (FLLs) are usually quantitatively assessed by time-intensity curves (TICs)
extracted from contrast-enhanced ultrasound (CEUS) image sequences. To overcome the subjectivity of
manual region of interest (ROI) selection and automatically extract TICs, a novel factor analysis method
called replace approximation (RA) was proposed. Assuming that the two factors are the arterial and portal

vein phases, respectively, the high-dimensional time-series data are mapped into 1-D space, where the
TIC at each pixel in the image becomes a point along a one-dimensional axis. The RA method aims to
seek two apexes corresponding to the factor curves (the targeted TICs) in the subspace. This method was
tested on 18 free-breathing datasets with respiratory motion correction. The experimental results showed
that the RA method extracted physiological factor curves and the corresponding factor images efficiently.
The mean correlation coefficient between the factor curves and the corresponding ROI measurements was
0.95 ± 0.02. Furthermore, the wash-in time ratio indexes of FLLs derived from the factor curves were
used to perform parametric imaging, which could represent the characteristics of different types of FLLs.
These results indicate that two-factor analysis has the potential to perform quantitative analysis of hepatic
perfusion, which would be helpful to the differential diagnosis of FLLs.
ETPL
BME-025
Evaluation of Optical Coherence Tomography for the Measurement of the Effects of
Activators and Anticoagulants on the Blood Coagulation In Vitro
Abstract: Optical properties of human blood during coagulation were studied using optical coherence
tomography (OCT) and the parameter of clotting time derived from the 1/$e$ light penetration depth
$(d_{1/e})$ versus time was developed in our previous work. In this study, in order to know if a new
OCT test can characterize the blood-coagulation process under different treatments in vitro, the effects of
two different activators (calcium ions and thrombin) and anticoagulants, i.e., acetylsalicylic acid (ASA, a
well-known drug aspirin) and melagatran (a direct thrombin inhibitor), at various concentrations are
evaluated. A swept-source OCT system with a 1300 nm center wavelength is used for detecting the
blood-coagulation process in vitro under a static condition. A dynamic study of $d_{1/e}$ reveals a
typical behavior due to coagulation induced by both calcium ions and thrombin, and the clotting time is
concentration-dependent. Dose-dependent ASA and melagatran prolong the clotting times. ASA and
melagatran have different effects on blood coagulation. As expected, melagatran is much more effective
than ASA in anticoagulation by the OCT measurements. The OCT assay appears to be a simple method
for the measurement of blood coagulation to assess the effects of activators and anticoagulants, which can
be used for activator and anticoagulant screening.
ETPL
BME-026
Classification of Simultaneous Movements Using Surface EMG Pattern Recognition
Abstract: Advanced upper limb prostheses capable of actuating multiple degrees of freedom (DOFs) are
now commercially available. Pattern recognition algorithms that use surface electromyography (EMG)
signals show great promise as multi-DOF controllers. Unfortunately, current pattern recognition systems
are limited to activate only one DOF at a time. This study introduces a novel classifier based on Bayesian
theory to provide classification of simultaneous movements. This approach and two other classification
strategies for simultaneous movements were evaluated using nonamputee and amputee subjects
classifying up to three DOFs, where any two DOFs could be classified simultaneously. Similar results
were found for nonamputee and amputee subjects. The new approach, based on a set of conditional
parallel classifiers was the most promising with errors significantly less ( $p < 0.05$) than a single linear
discriminant analysis (LDA) classifier or a parallel approach. For three-DOF classification, the

conditional parallel approach had error rates of 6.6% on discrete and 10.9% on combined motions, while
the single LDA had error rates of 9.4% on discrete and 14.1% on combined motions. The low error rates
demonstrated suggest than pattern recognition techniques on surface EMG can be extended to identify
simultaneous movements, which could provide more life-like motions for amputees compared to
exclusively classifying sequential movements.
ETPL
BME-027
Simultaneous Design of FIR Filter Banks and Spatial Patterns for EEG Signal
Classification
Abstract: The spatial weights for electrodes called common spatial pattern (CSP) are known to be
effective in EEG signal classification for motor imagery-based brain-computer interface (MI-BCI). To
achieve accurate classification in CSP, it is necessary to find frequency bands that relate to brain activities
associated with BCI tasks. Several methods that determine such a set of frequency bands have been
proposed. However, the existing methods cannot find the multiple frequency bands by using only learning
data. To address this problem, we propose discriminative filter bank CSP (DFBCSP) that designs finite
impulse response filters and the associated spatial weights by optimizing an objective function which is a
natural extension of that of CSP. The optimization is conducted by sequentially and alternatively solving
subproblems into which the original problem is divided. By experiments, it is shown that DFBCSP can
effectively extract discriminative features for MI-BCI. Moreover, experimental results exhibit that
DFBCSP can detect and extract the bands related to brain activities of motor imagery.
ETPL
BME-028
Development of Surrogate Spinal Cords for the Evaluation of Electrode Arrays Used in
Intraspinal Implants
Abstract: We report the development of a surrogate spinal cord for evaluating the mechanical suitability
of electrode arrays for intraspinal implants. The mechanical and interfacial properties of candidate
materials (including silicone elastomers and gelatin hydrogels) for the surrogate cord were tested. The
elastic modulus was characterized using dynamic mechanical analysis, and compared with values of
actual human spinal cords from the literature. Forces required to indent the surrogate cords to specified
depths were measured to obtain values under static conditions. Importantly, to quantify surface properties
in addition to mechanical properties normally considered, interfacial frictional forces were measured by
pulling a needle out of each cord at a controlled rate. The measured forces were then compared to those
obtained from rat spinal cords. Formaldehyde-crosslinked gelatin, 12 wt% in water, was identified as the
most suitable material for the construction of surrogate spinal cords. To demonstrate the utility of
surrogate spinal cords in evaluating the behavior of various electrode arrays, cords were implanted with
two types of intraspinal electrode arrays (one made of individual microwires and another of microwires
anchored with a solid base), and cord deformation under elongation was evaluated. The results
demonstrate that the surrogate model simulates the mechanical and interfacial properties of the spinal
cord, and enables in vitro screening of intraspinal implants.
ETPL
BME-029
Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive
Fetal ECG Via Block Sparse Bayesian Learning

Abstract: Fetal ECG (FECG) telemonitoring is an important branch in telemedicine. The design of a
telemonitoring system via a wireless body area network with low energy consumption for ambulatory use
is highly desirable. As an emerging technique, compressed sensing (CS) shows great promise in
compressing/reconstructing data with low energy consumption. However, due to some specific
characteristics of raw FECG recordings such as nonsparsity and strong noise contamination, current CS
algorithms generally fail in this application. This paper proposes to use the block sparse Bayesian learning
framework to compress/reconstruct nonsparse raw FECG recordings. Experimental results show that the
framework can reconstruct the raw recordings with high quality. Especially, the reconstruction does not
destroy the interdependence relation among the multichannel recordings. This ensures that the
independent component analysis decomposition of the reconstructed recordings has high fidelity.
Furthermore, the framework allows the use of a sparse binary sensing matrix with much fewer nonzero
entries to compress recordings. Particularly, each column of the matrix can contain only two nonzero
entries. This shows that the framework, compared to other algorithms such as current CS algorithms and
wavelet algorithms, can greatly reduce code execution in CPU in the data compression stage.
ETPL
BME-030
Clinical Validation of the Quick Dynamic Insulin Sensitivity Test
Abstract: The quick dynamic insulin sensitivity test (DISTq) can yield an insulin sensitivity result
immediately after a 30-min clinical protocol. The test uses intravenous boluses of 10 g glucose and 1 U
insulin at $t$ = 1 and 11 min, respectively, and measures glucose levels in samples taken at $t$ = 0, 10,
20, and 30 min. The low clinical cost of the protocol is enabled via robust model formulation and a series
of population-derived relationships that estimate insulin pharmacokinetics as a function of insulin
sensitivity ( SI). Fifty individuals underwent the gold standard euglycaemic clamp (EIC) and DISTq
within an eight-day period.SI values from the EIC and two DISTq variants (four-sample DISTq and two-
sample DISTq30) were compared with correlation, Bland–Altman and receiver operator curve analyses.
DISTq and DISTq30 correlated well with the EIC [$R$ = 0.76 and 0.75, and receiver operator curve c-
index = 0.84 and 0.85, respectively]. The median differences between EIC and DISTq/DISTq30 SI values
were 13% and 22%, respectively. The DISTq estimation method predicted individual insulin responses
without specific insulin assays with relative accuracy and thus high equivalence to EIC SI values was
achieved. DISTq produced very inexpensive, relatively accurate immediate results, and can thus enable a
number of applications that are impossible with established SI tests.
ETPL
BME-031
Spine Image Fusion Via Graph Cuts
Abstract: This study investigates a novel CT/MR spine image fusion algorithm based on graph cuts. This
algorithm allows physicians to visually assess corresponding soft tissue and bony detail on a single image
eliminating mental alignment and correlation needed when both CT and MR images are required for
diagnosis. We state the problem as a discrete multilabel optimization of an energy functional that balances
the contributions of three competing terms: (1) a squared error, which encourages the solution to be

similar to the MR input, with a preference to strong MR edges; (2) a squared error, which encourages the
solution to be similar to the CT input, with a preference to strong CT edges; and (3) a prior, which favors
smooth solutions by encouraging neighboring pixels to have similar fused-image values. We further
introduce a transparency-labeling formulation, which significantly reduces the computational load. The
proposed graph-cut fusion guarantees nearly global solutions, while avoiding the pix elation artifacts that
affect standard wavelet-based methods. We report several quantitative evaluations/comparisons over 40
pairs of CT/MR images acquired from 20 patients, which demonstrate a very competitive performance in
comparisons to the existing methods. We further discuss various case studies, and give a representative
sample of the results.
ETPL
BME-032
Cross-Scale Coefficient Selection for Volumetric Medical Image Fusion
Abstract: Joint analysis of medical data collected from different imaging modalities has become a
common clinical practice. Therefore, image fusion techniques, which provide an efficient way of
combining and enhancing information, have drawn increasing attention from the medical community. In
this paper, we propose a novel cross-scale fusion rule for multiscale-decomposition-based fusion of
volumetric medical images taking into account both intrascale and interscale consistencies. An optimal set
of coefficients from the multiscale representations of the source images is determined by effective
exploitation of neighborhood information. An efficient color fusion scheme is also proposed. Experiments
demonstrate that our fusion rule generates better results than existing rules.
ETPL
BME-033
Estimation of Tool Pose Based on Force–Density Correlation During Robotic Drilling
Abstract: The application of image-guided systems with or without support by surgical robots relies on
the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry
out the procedure based on the information provided by the navigation system, usually without being able
to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial
registration error are often used to describe the success of the registration process, while a lack of
methods describing the effects of navigation errors, such as those caused by tracking or calibration, may
prevent the application of image guidance in certain accuracy-critical interventions. During minimally
invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the
mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull.
Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that
injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on
drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool
during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous
bone density in the mastoid extracted from 3-D image data. We present here one possible implementation
of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool
localization accuracy of 0.29 mm was observed.

ETPL
BME-034
Ephaptic Coupling in Cardiac Myocytes
Abstract: While it is widely believed that conduction in cardiac tissue is regulated by gap junctions, recent
experimental evidence suggests that the extracellular space may play a significant role in action potential
propagation. Cardiac tissue with low gap junctional coupling still exhibits conduction, with conflicting
degrees of slowing that may be due to variations in the extracellular space. Inhomogeneities in the
extracellular space caused by the complex cellular structure in cardiac tissue can lead to ephaptic, or field
effect, coupling. Here, we present data from simulations of a cylindrical strand of cells in which we see
the dramatic effect highly resistant extracellular spaces have on propagation velocity. We find that
ephaptic effects occur in all areas of small extracellular spaces and are not restricted to the junctional cleft
between cells. This previously unrecognized type of field coupling, which we call lateral coupling, can
allow conduction in the absence of gap junctions. We compare our results with the classically used cable
theory, demonstrating the quantitative difference in propagation velocity arising from the cellular
geometry. Ephaptic effects are shown to be highly dependent upon parameter values, frequently
enhancing, but sometimes decreasing propagation speed. Our mathematical analysis incorporates the
inhomogeneities in the extracellular microdomains that cannot be directly measured by experimental
techniques and will aid in optimizing cardiac treatments that require manipulation of the cellular
geometry and understanding heart functionality.
ETPL
BME-035
Raven-II: An Open Platform for Surgical Robotics Research
Abstract: The Raven-II is a platform for collaborative research on advances in surgical robotics. Seven
universities have begun research using this platform. The Raven-II system has two 3-DOF spherical
positioning mechanisms capable of attaching interchangeable four DOF instruments. The Raven-II
software is based on open standards such as Linux and ROS to maximally facilitate software
development. The mechanism is robust enough for repeated experiments and animal surgery experiments,
but is not engineered to sufficient safety standards for human use. Mechanisms in place for interaction
among the user community and dissemination of results include an electronic forum, an online software
SVN repository, and meetings and workshops at major robotics conferences.
ETPL
BME-036
Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy
Consumption and Inexpensive Hardware
Abstract: Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an
evolving direction in personalized medicine. Among various constraints in designing such a system, three
important constraints are energy consumption, data compression, and device cost. Conventional data
compression methodologies, although effective in data compression, consumes significant energy and
cannot reduce device cost. Compressed sensing (CS), as an emerging data compression methodology, is
promising in catering to these constraints. However, EEG is nonsparse in the time domain and also
nonsparse in transformed domains (such as the wavelet domain). Therefore, it is extremely difficult for

current CS algorithms to recover EEG with the quality that satisfies the requirements of clinical diagnosis
and engineering applications. Recently, block sparse Bayesian learning (BSBL) was proposed as a new
method to the CS problem. This study introduces the technique to the telemonitoring of EEG.
Experimental results show that its recovery quality is better than state-of-the-art CS algorithms, and
sufficient for practical use. These results suggest that BSBL is very promising for telemonitoring of EEG
and other nonsparse physiological signals.
ETPL
BME-037
The Alpha Band of the Resting Electroencephalogram Under Pulsed and Continuous
Radio Frequency Exposures
Abstract: The effect of GSM-like electromagnetic fields with the resting electroencephalogram (EEG)
alpha band activity was investigated in a double-blind cross-over experimental paradigm, testing the
hypothesis that pulsed but not continuous radio frequency (RF) exposure would affect alpha activity, and
the hypothesis that GSM-like pulsed low frequency fields would affect alpha. Seventy-two healthy
volunteers attended a single recording session where the eyes open resting EEG activity was recorded.
Four exposure intervals were presented (sham, pulsed modulated RF, continuous RF, and pulsed low
frequency) in a counterbalanced order where each exposure lasted for 20 min. Compared to sham, a
suppression of the global alpha band activity was observed under the pulsed modulated RF exposure, and
this did not differ from the continuous RF exposure. No effect was seen in the extremely low frequency
condition. That there was an effect of pulsed RF that did not differ significantly from continuous RF
exposure does not support the hypothesis that ―pulsed‖ RF is required to produce EEG effects. The results
support the view that alpha is altered by RF electromagnetic fields, but suggest that the pulsing nature of
the fields is not essential for this effect to occur.
ETPL
BME-038
A Wireless Robot for Networked Laparoscopy
Abstract: State-of-the-art laparoscopes for minimally invasive abdominal surgery are encumbered by
cabling for power, video, and light sources. Although these laparoscopes provide good image quality,
they interfere with surgical instruments, occupy a trocar port, require an assistant in the operating room to
control the scope, have a very limited field of view, and are expensive. MARVEL is a wireless Miniature
Anchored Robotic Videoscope for Expedited Laparoscopy that addresses these limitations by providing
an inexpensive in vivo wireless camera module (CM) that eliminates the surgical-tool bottleneck
experienced by surgeons in current laparoscopic endoscopic single-site (LESS) procedures. The
MARVEL system includes1) multiple CMs that feature awirelessly controlled pan/tilt camera platform,
which enable a full hemisphere field of view inside the abdominal cavity, wirelessly adjustable focus, and
a multiwavelength illumination control system; 2) a master control module that provides a near-zero
latency video wireless communications link, independent wireless control for multiple MARVEL CMs,
digital zoom; and 3) a wireless human-machine interface that gives the surgeon full control over CM
functionality. The research reported in this paper is the first step in developing a suite of semiautonomous
wirelessly controlled and networked robotic cyberphysical devices to enable a paradigm shift in

minimally invasive surgery and other domains such as wireless body area networks.
ETPL
BME-039
Quantifying Limb Movements in Epileptic Seizures Through Color-Based Video
Analysis
Abstract: This paper proposes a color-based video analytic system for quantifying limb movements in
epileptic seizure monitoring. The system utilizes colored pyjamas to facilitate limb segmentation and
tracking. Thus, it is unobtrusive and requires no sensor/marker attached to patient's body. We employ
Gaussian mixture models in background/foreground modeling and detect limbs through a coarse-to-fine
paradigm with graph-cut-based segmentation. Next, we estimate limb parameters with domain knowledge
guidance and extract displacement and oscillation features from movement trajectories for seizure
detection/analysis. We report studies on sequences captured in an epilepsy monitoring unit. Experimental
evaluations show that the proposed system has achieved comparable performance to EEG-based systems
in detecting motor seizures.
ETPL
BME-040
Automatic Segmentation of Antenatal 3-D Ultrasound Images
Abstract: The development of 3-D ultrasonic probes and 3-D ultrasound (3DUS) imaging offers new
functionalities that call for specific image processing developments. In this paper, we propose an original
method for the segmentation of the utero-fetal unit (UFU) from 3DUS volumes, acquired during the first
trimester of gestation. UFU segmentation is required for a number of tasks, such as precise organ
delineation, 3-D modeling, quantitative measurements, and evaluation of the clinical impact of 3-D
imaging. The segmentation problem is formulated as the optimization of a partition of the image into two
classes of tissues: the amniotic fluid and the fetal tissues. A Bayesian formulation of the partition problem
integrates statistical models of the intensity distributions in each tissue class and regularity constraints on
the contours. An energy functional is minimized using a level set implementation of a deformable model
to identify the optimal partition. We propose to combine Rayleigh, Normal, Exponential, and Gamma
distribution models to compute the region homogeneity constraints. We tested the segmentation method
on a database of 19 antenatal 3DUS images. Promising results were obtained, showing the flexibility of
the level set formulation and the interest of learning the most appropriate statistical models according to
the idiosyncrasies of the data and the tissues. The segmentation method was shown to be robust to
different types of initialization and to provide accurate results, with an average overlap measure of 0.89
when comparing with manual segmentations.
ETPL
BME-041
Simultaneously Identifying All True Vessels From Segmented Retinal Images
Abstract: Measurements of retinal blood vessel morphology have been shown to be related to the risk of
cardiovascular diseases. The wrong identification of vessels may result in a large variation of these
measurements, leading to a wrong clinical diagnosis. In this paper, we address the problem of
automatically identifying true vessels as a postprocessing step to vascular structure segmentation. We

model the segmented vascular structure as a vessel segment graph and formulate the problem of
identifying vessels as one of finding the optimal forest in the graph given a set of constraints. We design a
method to solve this optimization problem and evaluate it on a large real-world dataset of 2446 retinal
images. Experiment results are analyzed with respect to actual measurements of vessel morphology. The
results show that the proposed approach is able to achieve 98.9% pixel precision and 98.7% recall of the
true vessels for clean segmented retinal images, and remains robust even when the segmented image is
noisy.
ETPL
BME-042
Safety Auxiliary Feedback Element for the Artificial Pancreas in Type 1 Diabetes
Abstract: The artificial pancreas aims at the automatic delivery of insulin for glycemic control in patients
with type 1 diabetes, i.e., closed-loop glucose control. One of the challenges of the artificial pancreas is to
avoid controller overreaction leading to hypoglycemia, especially in the late postprandial period. In this
study, an original proposal based on sliding mode reference conditioning ideas is presented as a way to
reduce hypoglycemia events induced by a closed-loop glucose controller. The method is inspired in the
intuitive advantages of two-step constrained control algorithms. It acts on the glucose reference sent to the
main controller shaping it so as to avoid violating given constraints on the insulin-on-board. Some
distinctive features of the proposed strategy are that 1) it provides a safety layer which can be adjusted
according to medical criteria; 2) it can be added to closed-loop controllers of any nature; 3) it is robust
against sensor failures and overestimated prandial insulin doses; and 4) it can handle nonlinear models.
The method is evaluated in silico with the ten adult patients available in the FDA-accepted UVA
simulator.
ETPL
BME-043
Cuffless Differential Blood Pressure Estimation Using Smart Phones
Abstract: Smart phones today have become increasingly popular with the general public for their diverse
functionalities such as navigation, social networking, and multimedia facilities. These phones are
equipped with high-end processors, high-resolution cameras, and built-in sensors such as accelerometer,
orientation-sensor, and light-sensor. According to comScore survey, 26.2% of U.S. adults use smart
phones in their daily lives. Motivated by this statistic and the diverse capability of smart phones, we focus
on utilizing them for biomedical applications. We present a new application of the smart phone with its
built-in camera and microphone replacing the traditional stethoscope and cuff-based measurement
technique, to quantify vital signs such as heart rate and blood pressure. We propose two differential blood
pressure estimating techniques using the heartbeat and pulse data. The first method uses two smart phones
whereas the second method replaces one of the phones with a customized external microphone. We
estimate the systolic and diastolic pressure in the two techniques by computing the pulse pressure and the
stroke volume from the data recorded. By comparing the estimated blood pressure values with those
measured using a commercial blood pressure meter, we obtained encouraging results of 95-100%
accuracy.
ETPL
BME-044
Design and Implementation of a Wireless Capsule Suitable for Autofluorescence
Intensity Detection in Biological Tissues

Abstract: We report on the design, fabrication, testing, and packaging of a miniaturized system capable of
detecting autofluorescence (AF) from mammalian intestinal tissue. The system comprises an application-
specific integrated circuit (ASIC), light-emitting diode, optical filters, control unit, and radio transmitter.
The ASIC contains a high-voltage charge pump and single-photon avalanche diode detector (SPAD). The
charge pump biases the SPAD above its breakdown voltage to operate in Geiger mode. The SPAD offers
a photon detection efficiency of 37% at 520 nm, which corresponds to the AF emission peak of the
principle human intestinal fluorophore, flavin adenine dinucleotide. The ASIC was fabricated using a
commercial triple-well high-voltage CMOS process. The complete device operates at 3 V and draws an
average of 7.1 mA, enabling up to 23 h of continuous operation from two 165-mAh SR44 batteries.
ETPL
BME-045
A Dynamic Risk Score to Identify Increased Risk for Heart Failure Decompensation
Abstract: A method for combining heart failure (HF) diagnostic information in a Bayesian belief network
(BBN) framework to improve the ability to identify when patients are at risk for HF hospitalization
(HFH) is investigated in this paper. Implantable devices collect HF related diagnostics, such as
intrathoracic impedance, atrial fibrillation (AF) burden, ventricular rate during AF, night heart rate, heart
rate variability, and patient activity, on a daily basis. Features were extracted that encoded information
regarding out of normal range values as well as temporal changes at weekly and monthly time scales. A
BBN is used to combine the features to generate a risk score defined as the probability of a HFH given the
diagnostic evidence. Patients with a very high risk score at follow-up are 15 times more likely to have a
HFH in the next 30 days compared to patients with a low-risk score. The combined score has improved
ability to identify patients at risk for HFH compared to the individual diagnostic parameters. A score of
this nature allows clinicians to manage patients by exception; a patient with higher risk score needs more
attention than a patient with lower risk score.
ETPL
BME-046
Design and Optimization of Reaction Chamber and Detection System in Dynamic
Labs-on-Chip for Proteins Detection
Abstract: In this paper, the lab-on-chip section for a protein assay is designed and optimized. To avoid
severe reliability problems related to activated surface stability, a dynamic assay approach is adopted:
protein-to-protein neutralization is performed while proteins diffuse freely in the reaction chamber. The
related refraction index change is detected via an integrated interferometer. The structure is also design to
provide a functional test of the reference protein solution, which is generally required for qualification for
medical uses.
ETPL
BME-047
An Approach to Rapid Calculation of Temperature Change in Tissue Using Spatial
Filters to Approximate Effects of Thermal Conduction
Abstract: We present an approach to performing rapid calculations of temperature within tissue by
interleaving, at regular time intervals, 1) an analytical solution to the Pennes (or other desired) bioheat

equation excluding the term for thermal conduction and 2) application of a spatial filter to approximate
the effects of thermal conduction. Here, the basic approach is presented with attention to filter design. The
method is applied to a few different cases relevant to magnetic resonance imaging, and results are
compared to those from a full finite-difference (FD) implementation of the Pennes bioheat equation. It is
seen that results of the proposed method are in reasonable agreement with those of the FD approach, with
about 15% difference in the calculated maximum temperature increase, but are calculated in a fraction of
the time, requiring less than 2% of the calculation time for the FD approach in the cases evaluated.
ETPL
BME-048
Noninvasive Biomagnetic Detection of Isolated Ischemic Bowel Segments
Abstract: The slow wave activity was measured in the magnetoenterogram (MENG) of normal porcine
subjects ( N = 5) with segmental intestinal ischemia. The correlation changes in enteric slow wave
activity were determined in MENG and serosal electromyograms (EMG). MENG recordings show
significant changes in the frequency and power distribution of enteric slow-wave signals during
segmental ischemia, and these changes agree with changes observed in the serosal EMG. There was a
high degree of correlation between the frequency of the electrical activity recorded in MENG and in
serosal EMG (r = 0.97). The percentage of power distributed in brady- and normoenteric frequency
ranges exhibited significant segmental ischemic changes. Our results suggest that noninvasive MENG
detects ischemic changes in isolated small bowel segments.
ETPL
BME-049
A New Strategy for Model Order Identification and Its Application to Transfer
Entropy for EEG Signals Analysis
Abstract: The background objective of this study is to analyze electrenocephalographic (EEG) signals
recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different
phases are observed during the seizure evolution, including a fast onset activity. We aim to ascertain how
cerebral structures get involved during this phase, in particular whether some structures ―drive‖ other
ones. Regarding a recent theoretical information measure, namely the transfer entropy (TE), we propose
two criteria, the first one is based on Akaike's information criterion, the second on the Bayesian
information criterion, to derive models’ orders that constitute crucial parameters in the TE estimation. A
normalized index, named partial transfer entropy (PTE), allows for quantifying the contribution or the
influence of a signal to the global information flow between a pair of signals. Experiments are first
conducted on linear autoregressive models, then on a physiology-based model, and finally on real
intracerebral EEG epileptic signals to detect and identify directions of causal interdependence. Results
support the relevance of the new measures for characterizing the information flow propagation whatever
unidirectional or bidirectional interactions.
ETPL
BME-050
Surface Electrocardiogram Reconstruction From Intracardiac Electrograms Using a
Dynamic Time Delay Artificial Neural Network
Abstract: This study proposes a method to facilitate the remote follow up of patients suffering from

cardiac pathologies and treated with an implantable device, by synthesizing a 12-lead surface ECG from
the intracardiac electrograms (EGM) recorded by the device. Two methods (direct and indirect), based on
dynamic time-delay artificial neural networks (TDNNs) are proposed and compared with classical linear
approaches. The direct method aims to estimate 12 different transfer functions between the EGM and
each surface ECG signal. The indirect method is based on a preliminary orthogonalization phase of the
available EGM and ECG signals, and the application of the TDNN between these orthogonalized signals,
using only three transfer functions. These methods are evaluated on a dataset issued from 15 patients.
Correlation coefficients calculated between the synthesized and the real ECG show that the proposed
TDNN methods represent an efficient way to synthesize 12-lead ECG, from two or four EGM and
perform better than the linear ones. We also evaluate the results as a function of the EGM configuration.
Results are also supported by the comparison of extracted features and a qualitative analysis performed by
a cardiologist.
ETPL
BME-051
Segmentation of Dermoscopy Images Using Wavelet Networks
Abstract: This paper introduces a new approach for the segmentation of skin lesions in dermoscopic
images based on wavelet network (WN). The WN presented here is a member of fixed-grid WNs that is
formed with no need of training. In this WN, after formation of wavelet lattice, determining shift and
scale parameters of wavelets with two screening stage and selecting effective wavelets, orthogonal least
squares algorithm is used to calculate the network weights and to optimize the network structure. The
existence of two stages of screening increases globality of the wavelet lattice and provides a better
estimation of the function especially for larger scales. R, G, and B values of a dermoscopy image are
considered as the network inputs and the network structure formation. Then, the image is segmented and
the skin lesions exact boundary is determined accordingly. The segmentation algorithm were applied to
30 dermoscopic images and evaluated with 11 different metrics, using the segmentation result obtained by
a skilled pathologist as the ground truth. Experimental results show that our method acts more effectively
in comparison with some modern techniques that have been successfully used in many medical imaging
problems.
ETPL
BME-052
Prediction of Uterine Contractions Using Knowledge-Assisted Sequential Pattern
Analysis
Abstract: The usage of the systemic opioid remifentanil in relieving the labor pain has attracted much
attention recently. An optimal dosing regimen for administration of remifentanil during labor relies on
anticipating the timing of uterine contractions. These predictions should be made early enough to
maximize analgesia efficacy during contractions and minimize the impact of the medication between
contractions. We have designed a knowledge-assisted sequential pattern analysis framework to 1) predict
the intrauterine pressure in real time; 2) anticipate the next contraction; and 3) develop a sequential
association rule mining approach to identify the patterns of the contractions from historical patient
tracings (HT).

ETPL
BME-053
Development of a Wireless Sensor for the Measurement of Chicken Blood Flow Using
the Laser Doppler Blood Flow Meter Technique
Abstract: Here, we report the development of an integrated laser Doppler blood flow micrometer for
chickens. This sensor weighs only 18 g and is one of the smallest-sized blood flow meters, with no wired
line, these are features necessary for attaching the sensor to the chicken. The structure of the sensor chip
consists of two silicon cavities with a photo diode and a laser diode, which was achieved using the
microelectromechanical systems technique, resulting in its small size and significantly low power
consumption. In addition, we introduced an intermittent measuring arrangement in the measuring system
to reduce power consumption and to enable the sensor to work longer. We were successfully able to
measure chicken blood flow for five consecutive days, and discovered that chicken blood flow shows
daily fluctuations.
ETPL
BME-054
Validation of Statistical Channel Models for 60 GHz Radio Systems in Hospital
Environments
Abstract: Statistical channel models for $hbox{60}$ GHz communications systems in hospital
environments are validated using channel capacity and throughput of a physical layer as figures of merit.
The channel models are validated by comparing the performance figures with channels from the
measurements and the channel models. The throughput evaluation is based on system specifications given
by the IEEE 802.15.3 c standard for high data rate wireless personal area networks, namely orthogonal
frequency division multiplexing and single carrier transmissions. The channel capacity serves as a metric
of the potential of the two transmission schemes since it defines the upper bound of the throughput. The
capacity is derived based on the signal formats of the transmission schemes. The capacity shows that
$hbox{97}$ % of the measurement results are within $2sigma$ range of the modeled results. The
throughput shows that the channel models predict the maximum achievable throughput of the measured
channels precisely, while the mean throughput in some cases shows difference because of the
interpolation effect of the small-scale fading in the statistical channel models. Due to the interpolation
effect, the channel model is more suitable for a precise analysis of the outage performance than the
measurements where the number of channel samples is limited and the worst faded channels are not
necessarily included.
ETPL
BME-055
Multistructure Large Deformation Diffeomorphic Brain Registration
Abstract: Whole brain MRI registration has many useful applications in group analysis and morphometry,
yet accurate registration across different neuropathological groups remains challenging. Structure-specific
information, or anatomical guidance, can be used to initialize and constrain registration to improve
accuracy and robustness. We describe here a multistructure diffeomorphic registration approach that uses
concurrent subcortical and cortical shape matching to guide the overall registration. Validation
experiments carried out on openly available datasets demonstrate comparable or improved alignment of
subcortical and cortical brain structures over leading brain registration algorithms. We also demonstrate

that a group-wise average atlas built with multistructure registration accounts for greater intersubject
variability and provides more sensitive tensor-based morphometry measurements
ETPL
BME-056
ECG Signal Quality During Arrhythmia and Its Application to False Alarm Reduction
Abstract: An automated algorithm to assess electrocardiogram (ECG) quality for both normal and
abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU)
monitors. A particular focus is given to the quality assessment of a wide variety of arrhythmias. Data
from three databases were used: the Physionet Challenge 2011 dataset, the MIT-BIH arrhythmia database,
and the MIMIC II database. The quality of more than 33 000 single-lead 10 s ECG segments were
manually assessed and another 12 000 bad-quality single-lead ECG segments were generated using the
Physionet noise stress test database. Signal quality indices (SQIs) were derived from the ECGs segments
and used as the inputs to a support vector machine classifier with a Gaussian kernel. This classifier was
trained to estimate the quality of an ECG segment. Classification accuracies of up to 99% on the training
and test set were obtained for normal sinus rhythm and up to 95% for arrhythmias, although performance
varied greatly depending on the type of rhythm. Additionally, the association between 4050 ICU alarms
from the MIMIC II database and the signal quality, as evaluated by the classifier, was studied. Results
suggest that the SQIs should be rhythm specific and that the classifier should be trained for each rhythm
call independently. This would require a substantially increased set of labeled data in order to train an
accurate algorithm.
ETPL
BME-057
Tissue Classification Using Ultrasound-Induced Variations in Acoustic Backscattering
Features
Abstract: Ultrasound (US) radio-frequency (RF) time series is an effective tissue classification method
that enables accurate cancer diagnosis, but the mechanisms underlying this method are not completely
understood. This paper presents a model to describe the variations in tissue temperature and sound speed
that take place during the RF time series scanning procedures and relate these variations to US
backscattering. The model was used to derive four novel characterization features. These features were
used to classify three animal tissues, and they obtained accuracies as high as 88.01%. The performance of
the proposed features was compared with RF time series features proposed in a previous study. The
results indicated that the US-induced variations in tissue temperature and sound speed, which were used
to derive the proposed features, were important contributors to the tissue typing capabilities of the RF
time series. Simulations carried out to estimate the heating induced during the scanning procedure
employed in this study showed temperature rises lower than 2 °C. The model and results presented in this
paper can be used to improve the RF time series.
ETPL
BME-058
On-Chip Systolic Networks for Real-Time Tracking of Pairwise Correlations Between
Neurons in a Large-Scale Network
Abstract: The correlation map of neurons emerges as an important mathematical framework for a

spectrum of applications including neural circuit modeling, neurologic disease bio-marking and
neuroimaging. However, constructing a correlation map is computationally expensive, especially when
the number of neurons is large. This paper proposes a hardware design using hierarchical systolic arrays
to calculate pairwise correlations between neurons. Through mapping a computationally efficient
algorithm for cross-correlation onto a massively parallel structure, the hardware is able to construct the
correlation maps in a much shorter time. The proposed architecture was evaluated using a field
programmable gate array. The results show that the computational delay of the hardware for constructing
correlation maps increases linearly with the number of neurons, whereas the growth of delay is quadratic
for a software-based serial approach. Also, the efficiency of our method for detecting abnormal behaviors
of neural circuits is demonstrated by analyzing correlation maps of retinal neurons.
ETPL
BME-059
An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System:
Improved Overnight Safety of Type-1 Diabetic Subjects
Abstract: Sensors for real-time continuous glucose monitoring (CGM) and pumps for continuous
subcutaneous insulin infusion (CSII) have opened new scenarios for Type-1 diabetes treatment. However,
occasional failures of either CGM or CSII may expose diabetic patients to possibly severe risks,
especially overnight (e.g., inappropriate insulin administration). In this contribution, we present a method
to detect in real time such failures by simultaneously using CGM and CSII data streams and a black-box
model of the glucose-insulin system. First, an individualized state-space model of the glucose-insulin
system is identified offline from CGM and CSII data collected during a previous monitoring. Then, this
model, CGM and CSII real-time data streams are used online to obtain predictions of future glucose
concentrations together with their confidence intervals by exploiting a Kalman filtering approach. If
glucose values measured by the CGM sensor are not consistent with the predictions, a failure alert is
generated in order to mitigate the risks for patient safety. The method is tested on 100 virtual patients
created by using the UVA/Padova Type-1 diabetic simulator. Three different types of failures have been
simulated: spike in the CGM profile, loss of sensitivity of glucose sensor, and failure in the pump delivery
of insulin. Results show that, in all cases, the method is able to correctly generate alerts, with a very
limited number of false negatives and a number of false positives, on average, lower than 10%. The use of
the method in three subjects supports the simulation results, demonstrating that the accuracy of the
method in generating alerts in presence of failures of the CGM sensor-CSII pump system can
significantly improve safety of Type-1 diabetic patients overnight
ETPL
BME-060
Quantitative Evaluation of Transform Domains for Compressive Sampling-Based
Recovery of Sparsely Sampled Volumetric OCT Images
Abstract: Recently, compressive sampling has received significant attention as an emerging technique for
rapid volumetric imaging. We have previously investigated volumetric optical coherence tomography
(OCT) image acquisition using compressive sampling techniques and showed that it was possible to
recover image volumes from a subset of sampled images. Our previous findings used the
multidimensional wavelet transform as the domain of sparsification for recovering OCT image volumes.
In this report, we analyzed and compared the potential and efficiency of three other image transforms to

reconstruct the same volumetric OCT image. Two quantitative measures, the mean square error and the
structural similarity index, were applied to compare the quality of the reconstructed volumetric images.
We observed that fast Fourier transformation and wavelet both are capable of reconstructing OCT image
volumes for the orthogonal sparse sampling masks used in this report, but with different merits.
ETPL
BME-061
The Use of a Bone-Anchored Device as a Hard-Wired Conduit for Transmitting EMG
Signals From Implanted Muscle Electrodes
Abstract: The use of a bone-anchored device to transmit electrical signals from internalized muscle
electrodes was studied in a sheep model. The bone-anchored device was used as a conduit for the passage
of a wire connecting an internal epimysial electrode to an external signal-recording device. The bone-
anchored device was inserted into an intact tibia and the electrode attached to the adjacent M. peroneus
tertius. ―Physiological‖ signals with low signal-to-noise ratios were successfully obtained over a 12-week
period by walking the sheep on a treadmill. Reliable transmission of multiple muscle signals across the
skin barrier is essential for providing intuitive, biomimetic upper limb prostheses. This technology has the
potential to provide a better functional and reliable solution for upper limb amputee rehabilitation:
attachment and control.
ETPL
BME-062
The iFit: An Integrated Physical Fitness Testing System to Evaluate the Degree of
Physical Fitness of the Elderly
Abstract: This paper presents an integrated physical fitness testing system (iFit) that evaluates the
physical fitness of older adults. The intent of the test is to help them manage and promote their health and
mitigate the effects of aging. National protocols of physical fitness were implemented to support the
assessment. The proposed system encompasses four modules of physical fitness assessment for both users
and medical professionals. The test information will be recorded and managed through a wireless sensor
network that will enable a better understanding of users' fitness states. Furthermore, the iFit has been
validated by a test session attended by elderly participants. The results show that there is a significant
correlation between iFit use in the test of flexibility, grip strength, and balance, compared to conventional
methods.
ETPL
BME-063
Multichannel Weighted Speech Classification System for Prediction of Major
Depression in Adolescents
Abstract: Early identification of adolescents at high imminent risk for clinical depression could
significantly reduce the burden of the disease. This study demonstrated that acoustic speech analysis and
classification can be used to determine early signs of major depression in adolescents, up to two years
before they meet clinical diagnostic criteria for the full-blown disorder. Individual contributions of four
different types of acoustic parameters [prosodic, glottal, Teager's energy operator (TEO), and spectral] to
depression-related changes of speech characteristics were examined. A new computational methodology
for the early prediction of depression in adolescents was developed and tested. The novel aspect of this
methodology is in the introduction of multichannel classification with a weighted decision procedure. It

was observed that single-channel classification was effective in predicting depression with a desirable
specificity-to-sensitivity ratio and accuracy higher than chance level only when using glottal or prosodic
features. The best prediction performance was achieved with the new multichannel method, which used
four features (prosodic, glottal, TEO, and spectral). In the case of the person-based approach with two sets
of weights, the new multichannel method provided a high accuracy level of 73% and the sensitivity-to-
specificity ratio of 79%/67% for predicting future depression.
ETPL
BME-064
Improved Multimodality Data Fusion of Late Gadolinium Enhancement MRI to Left
Ventricular Voltage Maps in Ventricular Tachycardia Ablation
Abstract: Electroanatomical voltage mapping (EAVM) is commonly performed prior to catheter ablation
of scar-related ventricular tachycardia (VT) to locate the arrhythmic substrate and to guide the ablation
procedure. EAVM is used to locate the position of the ablation catheter and to provide a 3-D
reconstruction of left-ventricular anatomy and scar. However, EAVM measurements only represent the
endocardial scar with no transmural or epicardial information. Furthermore, EAVM is a time-consuming
procedure, with a high operator dependence and has low sampling density, i.e., spatial resolution. Late
gadolinium enhancement (LGE) magnetic resonance imaging (MRI) allows noninvasive assessment of
scar morphology that can depict 3-D scar architecture. Despite the potential use of LGE as a roadmap for
VT ablation for identification of arrhythmogenic substrate, its utility has been very limited. To allow for
identification of VT substrate, a correlation is needed between the substrates identified by EAVM as the
gold standard and LGE-MRI scar characteristics. To do so, a system must be developed to fuse the
datasets from these modalities. In this study, a registration pipeline for the fusion of LGE-MRI and
EAVM data is presented. A novel surface registration algorithm is proposed, integrating the matching of
global scar areas as an additional constraint in the registration process. A preparatory landmark
registration is initially performed to expedite the convergence of the algorithm. Numerical simulations
were performed to evaluate the accuracy of the registration in the presence of errors in identifying
landmarks in EAVM or LGE-MRI datasets as well as additional errors due to respiratory or cardiac
motion. Subsequently, the accuracy of the proposed fusion system was evaluated in a cohort of ten
patients undergoing VT ablation where both EAVM and LGE-MRI data were available. Compared to
landmark registration and surface registration, the presented method achieved significant improvemen- in
registration error. The proposed data fusion system allows the fusion of EAVM and LGE-MRI data in VT
ablation with registration errors less than 3.5 mm.
ETPL
BME-065
A Navigation Platform for Guidance of Beating Heart Transapical Mitral Valve Repair
Abstract: Traditional surgical approaches for repairing diseased mitral valves (MVs) have relied on
placing the patient on cardiopulmonary bypass (on pump), stopping the heart and accessing the arrested
heart directly. However, because this approach has the potential for adverse neurological, vascular, and
immunological sequelae, less invasive beating heart alternatives are desirable. Emerging beating heart
techniques have been developed to offer high-risk patients MV repair using ultrasound guidance alone
without stopping the heart. This paper describes the first porcine trials of the NeoChord DS1000

(Minnetonka, MN), employed to attach neochordae to a MV leaflet using the traditional ultrasound-
guided protocol augmented by dynamic virtual geometric models. The distance errors of the tracked tool
tip from the intended midline trajectory (5.2 ± 2.4 mm versus 16.8 ± 10.9 mm, p = 0.003), navigation
times (16.7 ± 8.0 s versus 92.0 ± 84.5 s, p = 0.004), and total path lengths (225.2 ± 120.3 mm versus
1128.9 ± 931.1 mm, p = 0.003) were significantly shorter in the augmented ultrasound compared to
navigation with ultrasound alone,1 indicating a substantial improvement in the safety and simplicity of
the procedure.
ETPL
BME-066
A Wideband Dual-Antenna Receiver for Wireless Recording From Animals Behaving
in Large Arenas
Abstract: A low-noise wideband receiver (Rx) is presented for a multichannel wireless implantable neural
recording (WINeR) system that utilizes time-division multiplexing of pulse width modulated (PWM)
samples. The WINeR-6 Rx consists of four parts: 1) RF front end; 2) signal conditioning; 3) analog
output (AO); and 4) field-programmable gate array (FPGA) back end. The RF front end receives RF-
modulated neural signals in the 403-490 MHz band with a wide bandwidth of 18 MHz. The frequency-
shift keying (FSK) PWM demodulator in the FPGA is a time-to-digital converter with 304 ps resolution,
which converts the analog pulse width information to 16-bit digital samples. Automated frequency
tracking has been implemented in the Rx to lock onto the free-running voltage-controlled oscillator in the
transmitter (Tx). Two antennas and two parallel RF paths are used to increase the wireless coverage area.
BCI-2000 graphical user interface has been adopted and modified to acquire, visualize, and record the
recovered neural signals in real time. The AO module picks three demultiplexed channels and converts
them into analog signals for direct observation on an oscilloscope. One of these signals is further
amplified to generate an audio output, offering users the ability to listen to ongoing neural activity.
Bench-top testing of the Rx performance with a 32-channel WINeR-6 Tx showed that the input referred
noise of the entire system at a Tx-Rx distance of 1.5 m was 4.58 μVrms with 8-bit resolution at 640 kSps.
In an in vivo experiment, location-specific receptive fields of hippocampal place cells were mapped
during a behavioral experiment in which a rat completed 40 laps in a large circular track. Results were
compared against those acquired from the same animal and the same set of electrodes by a commercial
hardwired recording system to validate the wirelessly recorded signals.
ETPL
BME-067
iBalance-ABF: A Smartphone-Based Audio-Biofeedback Balance System
Abstract: This paper proposes an implementation of a Kalman filter, using inertial sensors of a
smartphone, to estimate 3-D angulation of the trunk. The developed system monitors the trunk angular
evolution during bipedal stance and helps the user to improve balance through a configurable and
integrated auditory-biofeedback (ABF) loop. A proof-of-concept study was performed to assess the
effectiveness of this so-called iBalance-ABF-smartphone-based audio-biofeedback system-in improving
balance during bipedal standing. Results showed that young healthy individuals were able to efficiently
use ABF on sagittal trunk tilt to improve their balance in the medial-lateral direction. These findings
suggest that the iBalance-ABF system as a telerehabilitation system could represent a suitable solution for

ambient assisted living technologies.
ETPL
BME-068
A Reconfigurable Digital Filterbank for Hearing-Aid Systems With a Variety of Sound
Wave Decomposition Plans
Abstract: Current hearing-aid systems have fixed sound wave decomposition plans due to the use of fixed
filterbanks, thus cannot provide enough flexibility for the compensation of different hearing impairment
cases. In this paper, a reconfigurable filterbank that consists of a multiband-generation block and a
subband-selection block is proposed. Different subbands can be produced according to the control
parameters without changing the structure of the filterbank system. The use of interpolation, decimation,
and frequency-response masking enables us to reduce the computational complexity by realizing the
entire system with only three prototype filters. Reconfigurability of the proposed filterbank enables
hearing-impaired people to customize hearing aids based on their own specific conditions to improve their
hearing ability. We show, by means of examples, that the proposed filterbank can achieve a better
matching to the audiogram and has smaller complexity compared with the fixed filterbank. The drawback
of the proposed method is that the throughput delay is relatively long (>20 ms), which needs to be further
reduced before it can be used in a real hearing-aid application.
ETPL
BME-069
A Fully Constrained Optimization Method for Time-Resolved Multispectral
Fluorescence Lifetime Imaging Microscopy Data Unmixing
Abstract: This paper presents a new unmixing methodology of multispectral fluorescence lifetime
imaging microscopy (m-FLIM) data, in which the spectrum is defined as the combination of time-domain
fluorescence decays at multiple emission wavelengths. The method is based on a quadratic constrained
optimization (CO) algorithm that provides a closed-form solution under equality and inequality
restrictions. In this paper, it is assumed that the time-resolved fluorescence spectrum profiles of the
constituent components are linearly independent and known a priori. For comparison purposes, the
standard least squares (LS) solution and two constrained versions nonnegativity constrained least squares
(NCLS) and fully constrained least squares (FCLS) (Heinz and Chang, 2001) are also tested. Their
performance was evaluated by using synthetic simulations, as well as imaged samples from fluorescent
dyes and ex vivo tissue. In all the synthetic evaluations, the CO obtained the best accuracy in the
estimations of the proportional contributions. CO could achieve an improvement ranging between 41%
and 59% in the relative error compared to LS, NCLS, and FCLS at different signal-to-noise ratios. A
liquid mixture of fluorescent dyes was also prepared and imaged in order to provide a controlled scenario
with real data, where CO and FCLS obtained the best performance. The CO and FCLS were also tested
with 20 ex vivo samples of human coronary arteries, where the expected concentrations are qualitatively
known. A certainty measure was employed to assess the confidence in the estimations made by each
algorithm. The experiments confirmed a better performance of CO, since this method is optimal with
respect to equality and inequality restrictions in the linear unmixing formulation. Thus, the evaluation
showed that CO achieves an accurate characterization of the samples. Furthermore, CO is a computational
efficient alternative to estimate the abundance of components in m-FLIM data, since a global optima-

Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract

Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract

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Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract