final year ieee project 2013-2014 - bio medical engineering project title and abstract

7/27/2019 Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract

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Elysium Technologies Private LimitedSingapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad |

Pondicherry | Trivandrum | Salem | Erode | Tirunelveli

http://www.elysiumtechnologies.com, [email protected]

3 Years of Experience

Automated Services

4/7 Help Desk Support

xperience & Expertise Developers

Advanced Technologies & Tools

egitimate Member of all Journals

Having 1,50,000 Successive records in

ll Languages

More than 12 Branches in Tamilnadu,

Kerala & Karnataka.

icketing & Appointment Systems.

ndividual Care for every Student.

Around 250 Developers & 20

Researchers


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227-230 Church Road, Anna Nagar, Madurai625020.

0452-4390702, 4392702, + 91-9944793398.

[email protected], [email protected]

S.P.Towers, No.81 Valluvar Kottam High Road, Nungambakkam,

Chennai - 600034. 044-42072702, +91-9600354638,

[email protected]

15, III Floor, SI Towers, Melapudur main Road, Trichy620001.

0431-4002234, + 91-9790464324.

[email protected]

577/4, DB Road, RS Puram, Opp to KFC, Coimbatore641002

0422- 4377758, +91-9677751577.

[email protected]
mailto:[email protected]:[email protected]:[email protected]:[email protected]


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Plot No: 4, C Colony, P&T Extension, Perumal puram, Tirunelveli-

627007. 0462-2532104, +919677733255,

[email protected]

1st Floor, A.R.IT Park, Rasi Color Scan Building, Ramanathapuram

- 623501. 04567-223225,

[email protected]

74, 2nd floor, K.V.K Complex,Upstairs Krishna Sweets, Mettur

Road, Opp. Bus stand, Erode-638 011. 0424-4030055, +91-

9677748477 [email protected]

No: 88, First Floor, S.V.Patel Salai, Pondicherry605 001. 0413

4200640 +91-9677704822

[email protected]

TNHB A-Block, D.no.10, Opp: Hotel Ganesh Near Busstand. Salem

636007, 0427-4042220, +91-9894444716.

[email protected]


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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 withengineering 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 andcontinuous 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,

LevenbergMarquardt, 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


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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-005Quantitative 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 fromexisting 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.


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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 areasto medical devices in order to improve and accelerate medical device innovation.

ETPL

BME-007Coaxial 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 tipforces. 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


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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-009Grand 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 challengescurrently 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-010Neuromodulation 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 andneuropsychiatric 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-011Minimizing 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 todiminished 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


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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 m, cytosol dilution factors of 10 or less are achievable.

ETPL

BME-012Engineering 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 atdescribing 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.

ETPLBME-013

Surgical Robotics Through a Keyhole: From Today's Translational Barriers toTomorrow'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


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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 BloomRichardson (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) classifiera whole-slide classifier that extracts features from a multitude of FOVs of varying

sizesto identify important image features at different FOV sizes. Image features utilized include thoserelated 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-016Simplified 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


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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 isproposed 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-019Far-Field RF Powering of Implantable Devices: Safety Considerations


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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-


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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-D3-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 isestablished 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


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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 effectivethan 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-026Classification 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


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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 learningdata. 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 suitabilityof 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


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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 andwavelet algorithms, can greatly reduce code execution in CPU in the data compression stage.

ETPL

BME-030Clinical 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 DISTqwithin an eight-day period.SI values from the EIC and two DISTq variants (four-sample DISTq and two-

sample DISTq30) were compared with correlation, BlandAltman 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


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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 ar tifacts 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-032Cross-Scale Coefficient Selection for Volumetric Medical Image Fusion

Abstract: Joint analysis of medical data collected from different imaging modalities has become acommon 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-033Estimation of Tool Pose Based on ForceDensity 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.


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ETPL

BME-034Ephaptic 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 cellulargeometry. 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-035Raven-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 sphericalpositioning 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


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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 healthyvolunteers 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.

ETPLBME-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


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minimally invasive surgery and other domains such as wireless body area networks.

ETPLBME-039

Quantifying Limb Movements in Epileptic Seizures Through Color-Based VideoAnalysis

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-040Automatic 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-041Simultaneously 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


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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-042Safety 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 thisstudy, 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.

ETPLBME-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


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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-045A 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 moreattention 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


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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-048Noninvasive 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 showsignificant 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) signalsrecorded 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


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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.

ETPLBME-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 to30 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).


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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.

ETPLBME-054

Validation of Statistical Channel Models for 60 GHz Radio Systems in HospitalEnvironments

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. Thethroughput 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-055Multistructure 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


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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-056ECG 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 wastrained 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

final year ieee project 2013-2014 - bio medical engineering project title and abstract

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