Medical Imaging
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Title: 3D
Ultrasound with Kinect (Medical Imaging)
João Sanches
Ultrasound (US) imaging is a useful technology in many fields,
including medical, due
to it’s portability and low cost. Although 2D data analysis is the
standard, results are affected by inaccuracies and subjectivities
associated with data acquisition and operator-dependent image
selection. 3D data reconstruction could circumvent these limitations,
but the costs of the traditional 3D ultrasound systems are usually the
bottleneck that prevent its widespread utilization. In this work an
alternative is considered where the low cost Kinect sensor is the core
of a free-hand 3D ultrasound for carotid atherosclerotic plaque 3D
reconstruction.
Objecives:
The goal of this work is the development of a free-hand 3D ultrasound
system for atherosclerotic plaque 3D reconstruction for computed aided
diagnosis (CAD) purposes. The core of the system is the Kynect sensor,
from Microsoft.
Description:
Carotid Plaque Atherosclerosis accurate and objective characterization
is very important for surgical decision making for carotid
endarterectomy, a surgical intervention for plaque removal. Recently
Activity Index (AI) and Enhanced Activity Index scores were proposed
based on clinical data and features extracted from 2D ultrasound images
to quantify the risk of stroke. The aim of this work is to design and
implement a low cost free-hand 3D ultrasound based on the Kinect
sensor, designed to the Microsoft XBox video game console, to
obtain a 3D reconstruction of the plaque and improve the EAI score with
3D information about the plaque.
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Title: WebCam based
optical Tracker
for free-hand US
(10/1/2013)
3D reconstruction of the carotid bifurcation from sequences of nearly
parallel cross sections, in a free-hand US basis, is very important for
carotid atherosclerosis characterization, quantification and diagnosis.
The traditional free hand systems use optical or electromagnetic
trackers to measure the position and orientation of the US probe during
the acquisition process needed to produce accurate reconstruction
results. However, the spatial locators usually used in this type of
applications are very expensive because they are general purposes and
accurate for a wide spatial range.
In the present application, however, the region of interest is small
and the expected probe trajectory is well know, as well as the
orientation of the probe, that is expected to present only slight
change during the whole course.
Objectives
The goal of this working thesis is to produce an optical spatial
locator based on two high-resolution webcams to track the US probe
positions and orientations along the acquisition of the image sequences
used for 3D reconstruction of the carotid bifurcation and
atherosclerotic plaque.
The acquisition protocol imposes tight restrictions to the movement of
the probe in order to make the speed as uniform as possible and
orientation variations minimal. This constraints should be taken into
account in the hardware conception and algorithm designing in
order to maximize the accuracy of the system while keeping it simple
and low cost.
Description
The core of the experimental setup is composed by two webcams located
near the neck of the patient where the probe is visible during the
whole course. A geometric marker placed at the probe is detected in
both images of the stero system and the corresponding location and
orientation with respect to the 3D real world referential is computed
and associated with the acquired US image.
The specific simplified geometry of the problem is taken into account
in order to optimize the accuracy of the system, in particular, a
Kalman filter is used where the expected dynamics of the probe
displacement is used to minimize the measurement errors.
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Title: ASL Adpative Optimal Sampling
Strategy (AOSS)
Perfusion describes the distribution of nutrients to the tissues by
blood flow through the capillary bed and is defined as volume of blood
per unit time and per unit volume of tissue. Arterial spin labeling
(ASL) magnetic resonance imaging (MRI) techniques offer a non-invasive
way of generating perfusion images that are potentially quantitative
[1]. They consist on magnetically labeling the water molecules in the
blood and then measuring the magnetization of the tissues after a
certain time interval, the inversion time (TI). The magnetization
difference M(t) as a function of TI in pulsed ASL (PASL) can be
described by a standard kinetic model [2], depending on several
parameters: perfusion, arterial transit time, bolus time width, blood
relaxation rate and a constant related with the tissue relaxation rate.
In principle, the magnetization collected at a single TI point is
sufficient to obtain a perfusion estimate, provided that the values of
the other model parameters are available or can be assumed. However,
this is not always the case, particularly in pathological conditions
such as cerebrovascular disease. In these cases, it would be possible
to estimate perfusion, as well as other unknown parameters, by fitting
the PASL model to M(t) data collected at multiple TI points [3].
However, the accuracy of the estimated parameters strongly depends on
the distribution of the TI sampling points. Optimal sampling strategies
have previously been designed based on the Fisher information matrix
optimality criterion for the simultaneous estimation of perfusion and
the arterial transit time [4]. However, the optimal time points must be
defined a priori and could not be changed adaptively during the
acquisition process.
Objectives
Perfusion describes the distribution of nutrients to the tissues by
blood flow through the capillary bed and is defined as volume of blood
per unit time and per unit volume of tissue. Arterial spin labeling
(ASL) magnetic resonance imaging (MRI) techniques offer a non-invasive
way of generating perfusion images that are potentially quantitative
[1]. They consist on magnetically labeling the water molecules in the
blood and then measuring the magnetization of the tissues after a
certain time interval, the inversion time (TI). The magnetization
difference M(t) as a function of TI in pulsed ASL (PASL) can be
described by a standard kinetic model [2], depending on several
parameters: perfusion, arterial transit time, bolus time width, blood
relaxation rate and a constant related with the tissue relaxation rate.
In principle, the magnetization collected at a single TI point is
sufficient to obtain a perfusion estimate, provided that the values of
the other model parameters are available or can be assumed. However,
this is not always the case, particularly in pathological conditions
such as cerebrovascular disease. In these cases, it would be possible
to estimate perfusion, as well as other unknown parameters, by fitting
the PASL model to M(t) data collected at multiple TI points [3].
However, the accuracy of the estimated parameters strongly depends on
the distribution of the TI sampling points. Optimal sampling strategies
have previously been designed based on the Fisher information matrix
optimality criterion for the simultaneous estimation of perfusion and
the arterial transit time [4]. However, the optimal time points must be
defined a priori and could not be changed adaptively during the
acquisition process.
Description
Here, we propose to design, implement and test a different approach
where each time sampling is selected in real time according the data
previously acquired. Since up to this moment there is no equipment
available in our country to run this type of acquisition sequences, we
propose to test and validate the algorithm with synthetic data.
References
[1] E T Petersen, I Zimine, Y-C L Ho, and X Golay, Non-invasive
measurement of perfusion: a critical review of arterial spin labelling
techniques, Br J Radiol, vol. 79, no. 944, pp. 688?701, 2006.
[2] Richard B. Buxton, Lawrence R. Frank, Eric C. Wong, Bettina
Siewert, Steven Warach, and Robert R. Edelman, A general kinetic model
for quantitative perfusion imaging with arterial spin labeling,
Magnetic Resonance in Medicine, vol. 40, no. 3, pp. 383-396, 1998.
[3] P. M. Figueiredo, S. Clare, and P. Jezzard, Quantitative perfusion
measurements using pulsed arterial spin labeling: effects of large
region-ofinterest analysis., Journal of Magnetic Resonance Imaging,
vol. 21, no. 6, pp. 676-682, June 2005.
[4] J. Xie, D. Gallichan, R. N. Gunn, and P. Jezzard, Optimal design of
pulsed arterial spin labeling mri experiments., Magnetic Resonance in
Medicine, vol. 59, no. 4, pp. 826-834, April 2008.
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Biological Imaging and Modeling
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Title: E-cadherin 3D
spatial
distribution characterization for the pathogenicity discrimination of
missense mutations from confocal imunofluorescence images
(10/1/2013)
In collaboration with IPATIMUP
Advisers: João
Sanches (ISR(IST) and Raquel Seruca(IPATIMUP/FMUP)
Structural and mechanical properties of the tissues are dependent
on the physical linkage between cells. E-cadherin is a key component on
this adhesion mechanism and mutations on its coding gene may produce
dysfunctional molecules that compromise the cell-cell linkage and
increase the risk of cancer.
The homeostatic distribution of E-cadherin within a cell is
characterized by a strong and clear concentration at the membrane where
it plays its adhesion role. However, for mutated molecules, the
trafficking dynamics of E-Cadherin is disturbed and altered
distributions of E-cadherin across the cell are observed.
Objectives
The goal of this project is to design a method to characterize
E-cadherin distribution in the cell with a special emphasis at the
junction contacts of cell-cell pairs. Immunofluorescence confocal
images will be used. A typical E-cadherin concentration profile along
the average linkage of cell pairs is computed representing the
distributions for wild type (WT) and mutated molecules.
These characteristic profiles are able to discriminate functional from
dys- functional molecules/mutations and can be used for diagnosis
purposes. Additional, they can be useful to extract measures with
biological meaning such as the expression level of E-cadherin and the
relative concentration of the molecule at the membrane aiming to infer
the adhesion strength.
Description
In epithelia, cell-cell adhesion is achieved by the establishment of
homophilic interactions between two adjacent cells. One of the pivotal
molecules to attain this homeostatic interaction between cells is the
correct localization and function of the transmembrane protein E-
cadherin and its interaction with other members of the adhesion complex.
In cancer, somatic changes in the expression or function of E-cadherin
have been implicated in all steps of tumour progression, including
detachment of tumour cells from the primary site, invasion of the
adjacent tissue, intravasation into the blood stream, extravasation
into distant target organs, and formation of secondary lesions or
metastasis. In hereditary forms of gastric cancer germline E-cadherin
mutations are causing events. In this lethal cancer disease patients
develop highly invasive isolated carcinomas that still pose a very
important clinical problem since no effective tools of image screening
(endoscopy, MRI and PET) are available yet.
Due to this limitation it is of great importance to develop methods to
classify E-cadherin mutants and disclose those who are clinically
relevant. We have been focusing on developing in vitro assays to
determine the pathogenic relevance of germline E-cadherin mutations in
terms of function. However, it is of crucial importance to evaluate the
localization and the pattern of E-cadherin expression at the cellular
level since aberrant distribution of the protein indicates loss of its
normal function: failure in cell-cell adhesion and increased cancer
cell invasion. Moreover it is well known that whenever cells lose
cell-cell adhesion, the polarity of cells is compromised and the
distance between the nucleus in adjacent cells is perturbed.
Additionally, this project should investigate the hypothesis of
estimating and discriminating the cell cycle phase from DAPI (blue)
images of the nucleus. This information could be very useful for an
accurate characterization of the E-cadherin distribution at different
phases of the cell cycle.
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Title: Celular adhesion
from
fluorescence microscopy images (Characterization
of the E-cadherin spatial distribution at a cellular level)
In collaboration with IPATIMUP
Advisers: Raquel Seruca(IPATIMUP), J. Miguel Sanches
(ISR/IST)
Physical adhesive linkages are crucial for the maintenance of tissue
architecture and E-cadherin dependent cell-cell adhesion is central in
this process. In cancer, alterations of E-cadherin are very common and
significantly associated to loss of cell-cell adhesion and increased
invasion potential of cancer cells. In familial forms of gastric cancer
(HDGC), E-cadherin mutations may occur at germline level and
individuals carrying these mutants are at high risk of developing
early-onset (<40 years) invasive gastric cancer without any evidence
of symptoms. This is a tragic clinical situation and we urgently need
to set-up novel methods to establish the functional relevance of
E-cadherin mutations in order to improve the screening and surveillance
of these cancer families.
At IPATIMUP, it was developed an in vitro assay to study the effect of
E-cadherin mutations in terms of cell invasion, cell-cell adhesion and
expression of E-cadherin at cellular level. The later method is based
on tagging E-cadherin molecules with fluorescent dyes to observe its
distribution in the intra and inter cellular space. In particular, the
intensity and distribution of fluorescent E-cadherin at cell membrane,
as well as its aberrant presence at the cytoplasm of the cell, is very
relevant. This analysis is directly related to the stability of
E-cadherin at cell membrane, where it is expected to be in a
homeostatic situation establishing a competent cell-cell adhesion
complex.
Figure 1 - E-Cadherin distribution patterns associated
with several mutations.
Objectives:
The goal of this work is to characterize E-cadherin
distribution, designing and testing several metrics and features
extracted from fluorescence images of the cell with tagged E-cadherin.
This analysis will allow the prediction of E-cadherin functional
behavior (disease related versus non-disease related). The
quantification of E-Cadherin concentration at specific locations, such
as the cellular membrane as well as its distribution in the cytoplasm,
provides valuable biological information to assess the functional
relevance of the mutant forms and to predict the underlying molecular
mechanisms associated with its aberrant expression.
Description:
The scope of this work is image processing of
fluorescence microscopy images. The distribution of normal E-Cadherin
molecules in cells is mainly observed at the membrane, in order to
accomplish its role in cell-cell adhesion. In this case, the image
intensities at the membrane are stronger than that at the other
locations as displayed in Fig.1/WT. Additionally, the distribution of
the molecules at the cytoplasm is uniform with a characteristic
distribution pattern (textural characterization). On the contrary, the
mutated molecules follow a different distribution. Large concentrations
in the cytoplasm or lack of E-cadherin signals in some locations are
common features for almost all mutations and are associated with loss
of cell-cell adhesion. The main goal of this work is to extract
morphological and textural features from the microscope images in order
to characterize the distribution of E-Cadherin, advance in the
underlying molecular mechanisms and predict its role in the adhesion
process. The following outputs assume particular relevance for
oncologists and biologists dedicated to cancer.
- Width of signal intensity in cell to cell contact
(Fig.2a)
- Number of cell to cell contact points between cells
(Fig.2b)
- Loss of signal intensity at cell membrane
(Fig.2c)
- Aberrant cytoplasmic signal intensity (Fig.2c)
Figure 2 - Biological measures
Due to the small amount of detected fluorescence dots and amplification
steps related to the assay, the data collected by these imaging systems
exhibit a severe limiting item related to quantification and
distribution of the signal per cell and signal-dependent noise. This
limitation must be attenuated before functional conclusions can be/are
made by the biomedical researcher. In fact, an important task in image
processing in this case is the signal quantification and localization
within the cell (membrane versus cytoplasm) and denoising, since the
data measured by imaging instruments always contain noise and blur.
Although being unattainable to build devices that produce data with
arbitrary fidelity, it is possible to mathematically reconstruct the
underlying images from the corrupted data obtained from real-world
instruments. Therefore, that information present but hidden in the data
can be revealed with less blur and noise.
Requirements:
Image processing knowledge and programming experience, e.g., MatLab or
C++.
Expected results:
Publications in international conferences and journals and a software
prototype to process this type of images.
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Title: RNA splicing
stochastic model
and dynamics from spinning disk confocal microscopy images
(In collaboration with IMM/FMUL)
Advisers: José Rino
(IMM), Carmo Fonseca (IMM), J. Miguel Sanches (IST)
DNA transcription is one of the central mechanisms involved in the
protein synthesis within the cell. This process and in particular the
introns removal step, called RNA maturation or splicing, are not
completely known and are object of a very active researching work. The
improvement and invention of new microscopy image modalities and
techniques made it possible impressive advances in this area of
biological research. The biologists developed new fluorescent dyes that
bind to specific introns. By this, it is possible to observe the
splicing process of these introns in real time at each replication site
by using the new microscopy image modality, called spinning disk
confocal microscopy.
"...The explosive growth in biomedical research using live-cell imaging
techniques has been fueled by a combination of events that include
dramatic advances in confocal microscopy instrumentation coupled with
the introduction of novel ultra-sensitive detectors and continued
improvements in the performance of genetically-encoded fluorescent
proteins. Acquiring images of localized fluorophores in living cells on
the millisecond timescales that reveal intricate biological dynamics
presents a host of new challenges, which are far more complex than the
traditional issues associated with creating a single high-resolution
snapshot of well-stained fixed tissue in a laser scanning confocal
microscope. In order to assure high image acquisition speeds of
fluorescent proteins and synthetic dyes in live cells with reasonable
contrast and minimal photobleaching, microscopes must be able to
quickly scan the field of view and record data using detectors with
high quantum efficiency. Laser scanning confocal microscopes focus a
single beam on the specimen plane to sequentially point-scan a region
of interest with spatial filtration of the emission light through a
single pinhole that rejects light originating from regions that are out
of focus..." (in
Zeiss - Introduction to Spinning Disk Confocal Microscopy)
Objectives: The goal of this work is to design a stochastic model to
describe the transcription and splicing processes from spinning disk
confocal microscopy images. The transcription sites appear in the
images as noisy (Poisson distributed)intensity spots where several
transcriptions and splicing processes are occurring simultaneously. The
final goal is to estimate the number of polymerases and spliceosomes
that are acting at each transcription site along the time to extract
biological relevant parameters that characterize the dynamic of the
process.
Description:
DNA transcription is one of the central mechanisms involved in the
protein synthesis within the cell. This process and in particular the
introns removal step, called RNA maturation or splicing, are not
completely known and are object of a very active field of research. The
improvement and invention of new microscopy image modalities and
techniques made it possible impressive advances on this area of
biological research.
The biologists developed new fluorescent dyes that bind to specific
introns. By this, it is possible to observe the splicing process of
these introns in real time at each replication site by using the new
microscopy image modality, called spinning disk confocal microscopy.
These images, however, present a small SNR and are corrupted by a type
of multiplicative noise with Poisson distribution due to the huge light
amplification need to observe the very weak radiation emitted by the
fluorescent dyes.
The main goal is to study the details of the introns removal and
degradation processes occurring during the maturation process of the
transcribed RNA molecule. The image intensity at each transcription
site reflects the number of polymerases operating simultaneously at
that location as well as the number of spliceossomes that are
maturating the transcribed RNA.
In the scope of this work a stochastic dynamic model should be derived
based on the biological knowledge to describe and characterize the
dynamics of the transcription and splicing processes. The parameters of
the model are estimated from the noisy observation by taking into
account the image formation process, namely, its Poisson statistical
distribution. Additionally, the transcription site is not static and
should be tracked along the 3D field of view along the time at each
acquired volume, where several transcription sites are visible.
The work is composed by three main tasks: i) Pre-processing of the
images to track the several time change intensity and displacement
transcription sites visible in the filed of view, ii) Stochastic model
designing based on biological knowledge about the transcription and
splicing processes, iii) Estimation of parameters of the model and
validation of the method from synthetic data generated with the model,
iv) Application of the method to real data.
Requirements:
Solid mathematical background and programming experience, e.g., MatLab
or C++.
Expected results:
Publications in international conferences and journals and a software
prototype to process this type of images.
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Neurosurgery
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Title: Automatic brain electrical activity registering and
analysis for brain functional mapping in Parkinson deep brain
stimulation surgery.
(In collaboration with the Neurosurgery department from Hospital Santa
Maria, Lisbon)
Advisers: Herculano
Carvalho (HSM) and J. Miguel Sanches (IST)
Deep brain stimulation (DBS) is an effective tool in the minimization
of the severe symptoms of the Parkinson disease. The accurate position
of the electrodes for deep stimulation is a critical procedure with
risks. The trajectories of the electrodes need to be careful and
accurately planed to not cross vascular and vital structures and to not
cause temporary or permanent damages on the brain. Additionally, the
final position of the DBS lead is crucial to obtain the desired result
that is the minimization of the disabling symptoms associated with the
Parkinson disease.
The precise final location of the DBS lead is roughly defined in the
pre-surgical preparation procedures. The exact location is only defined
during the surgery by making a functional map from the electrical
registers obtained along the microelectrodes trajectories. The
functional map allows the selection of the depths to test. The
intra-operative stimulation test will select the best place to implant
DBS lead for symptom suppression without disabling side effects. This
procedure is time consuming, mostly made by hand, prone to errors and
represents a very important percentage of the total time of the surgery.
Objectives:
The main goal of this work is to design and implement the 5 electrode
electrical acquisition system with a wireless interface in order to
reduce the amount of hardware in the surgery scenario. The depth
control of the microelectrodes is made by the surgeon trough a
mechanical device with a screw which is coupled to an encoder that
provides a real-time monitoring of depth. The electrical activity in
the 5 microelectrodes is automatically acquired and stored at a laptop
together with the location (depth) of the microelectrodes.
The software in the laptop generates the electrical activity map along
the microelectrodes course in real-time in an incremental basis, that
is, as soon as the data is acquired it is immediately used to update
the map. In this strategy the neurologist may decide to inspect
locations previously observed if more accuracy is needed.
Description:
Deep brain stimulation (DBS) is a surgical procedure used to treat a
variety of disabling neurological symptoms—most commonly the
debilitating symptoms of Parkinson’s disease (PD), such as tremor,
rigidity, bradykinesia and gait disturbance. The procedure is also used
to treat essential tremor, dystonia and other movement disorders. At
present, the procedure is used only for patients whose symptoms cannot
be adequately controlled with medication.
DBS uses a surgically implanted, battery-operated medical device called
a neurostimulator— a dual-channel device capable of bilateral brain
stimulation similar to a heart pacemaker. The device delivers
controlled electrical pulse to stimulate targeted areas in the brain
that control movement, blocking the abnormal activity of deep brain
nuclei that cause the movement disorder.
Before the procedure, a neurosurgeon uses magnetic resonance imaging
(MRI) and stereotatic computed tomography (CT) scan to identify and
locate the exact target and plan a surgical trajectory to reach a
nucleus within the brain. A neuronavigation system is used to do the
surgical plan.
At surgical time, some surgeons may use microelectrode recording—which
involves a small bipolar wire that monitors the activity of nerve cells
in the target area—to more specifically identify the precise brain
target that will be stimulated. Then is performed the intra-operative
stimulation test to verify the symptoms improvement and absence of
significant side effects. Finally is implanted the DBS lead. Generally,
these targets are the thalamus, subthalamic nucleus(STN), or globus
pallidus.
The DBS system consists of three components: the lead, the extension,
and the neurostimulator. The DBS lead (also called a definitive
electrode)—a thin quadripolar, insulated wire—is inserted through a
small opening in the skull (burr hole) and implanted at the selected
nucleus. The tip of the lead is positioned within the targeted brain
area, and can deliver stimulation either by one pole (monopolar) or by
a combination of poles (bipolar).
The extension is an insulated wire that is passed under the skin of the
head, neck, toward torax, connecting the lead to the neurostimulator.
The neurostimulator (the "battery pack") is the third component and is
usually implanted subcutaneously in subclavicular thoracic region. In
some cases it may be implanted under skin at the lower chest or
abdomen.
Once the system is in place, programmed electrical impulses are sent
from the neurostimulator up along the extension wire and the lead and
into the brain. These impulses interfere with and block the electrical
signals that cause the movement disorder."
Adapted from “ NINDS Deep Brain Stimulation for Parkinson's Disease
Information Page
(http://www.ninds.nih.gov/disorders/deep_brain_stimulation/deep_brain_stimulation.htm)
“
This work is composed by two main tasks of hardware and software. The
goal of the first task is to implement the acquisition setup of the
signals collected from the microelectrodes implanted in the brain by
using a wireless system in order to minimize the wires at the surgery
environment that disturb the procedure and more important, improve the
signal to noise ratio of the acquired signals by reducing the artifacts
and interferences that corrupt them. The depth of the microelectrode is
controlled by the surgeon but measured by an encoder. The information
of depth provided by the encoder is sent to the computed together with
the electrical registers from the microelectrodes by the wireless
communication channel, monitoring their position along the planned
trajectory. The second task is the real time analysis of the acquired
signal at the computer in order to compute a functional map along the
microelectrodes course. This signal analysis is done according the
state of the art methods described in the literature and the results
and control of the process is done throught an user interface
application in C++ running on the computer.
Expected results:
The expected results are an experimental prototype, a patent and
publications in international top conferences and journals.
Requirements:
Solid mathematical background and programming experience, e.g., MatLab
or C++.
Sub-topics
Title:
Functional brain
mapping for neurosurgery planning from scalp and intracranial
electroencephalography data
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Title:
CT and/or MRI co-register
with US for computer assisted surgery (CAS) in neuro-surgery guidance
(In collaboration with the Neurosurgery department from Hospital Santa
Maria, Lisbon)
Advisers:
Herculano Carvalho (HSM) and J. Miguel Sanches (IST)
Requirements:
Solid mathematical background and programming experience, e.g., MatLab
or C++.
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Title:
Surface brain shift
deformation tracking with structured light in brain surgery
(In collaboration with the Neurosurgery department from Hospital Santa
Maria, Lisbon)
Advisers:
Herculano Carvalho (HSM) and J. Miguel Sanches (IST)
Brain shift is a common effect observed in open brain surgeries where
the slow leakage of cerebral fluid leads to a deformation of the whole
brain and of the cortex in particular. This deformation leads to a
misalignment with the MRI/CT images acquired during the pre-surgical
phase of the intervention which difficult the work of the surgery team
and will result in inaccuracies in surgical procedures that may cause
severe damages on surrounding regions.
Objectives:
The goal of this work is to design and implement a real
time compensation method of brain shift based on images of the exposed
part of the brain where a structured pattern of light is projected.
This pattern, reflecting the morphological shape of the cortex is
registered with the pre-surgical MRI/CT volumes in order to adapt them
to the slowly evolved deformation associated with brain shift.
Description:
Requirements:
Solid mathematical background and programming
experience, e.g., MatLab or C++.
Bibliography
Tuhin K. Sinha, Benoit M. Dawant, Valerie Duay, David M. Cash, Robert
J. Weil, Reid C. Thompson, Kyle D. Weaver, and Michael I. Miga, A
Method to Track Cortical Surface Deformations Using a Laser Range
Scanner, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 24, NO. 6, JUNE
2005.
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Brain
functional Imaging and Computer Interface
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Title: Scalp EEG
Synchronization and
desynchronization quantification in the analytical signals framework
(10/1/2013 - CoAdviser: Profª Patrícia Figueiredo)
The EEG is one of the most common techniques for brain activity
assessment and it is very well established in the clinical practice for
diagnostic purposes. Recently, it has received additional attention and
developments in the scope of emergent techniques like Brain Computer
Interfaces (BCI) or simultaneous EEG-fMRI. In these modalities,
detection of event-related potentials (ERP) and associated
event-related desynchronization / synchronization (ERD/ERS) are central
goals in several scientific and clinical scopes, e.g., detection of
motor movement or epileptic activity. The most commonly used method for
assessing ERD/ERS consists on the evaluation of EEG power changes upon
the event onset in relation to the baseline, reflecting
increased/decreased synchronization.
Objectives
The goal of this project is the designing of a new method for ERD/ERS
estimation based on measuring spatial variations of the EEG phase. A
continuous phase map is estimated from the discrete set of EEG traces
by using the Hilbert transform in the analytical signals framework. The
synchronization at each arbitrary continuous location in the scalp
space is then computed as the magnitude of the phase gradient at that
location. The interpolation/fitting algorithm is a central issue of the
project due the highly time and space variability of the interpolated
signals.
Description
The electroencephalogram (EEG) is one of the commonest techniques used
in the study of neuronal activity and to assist the diagnosis of brain
disorders. Event-related potentials (ERPs) are defined as the changes
of the activity of neuronal populations elicited by sensory stimuli
[1,2]. The usual way to detect ERP is by averaging the responses over
the several trials. This approach admits that ERPs consist of a pattern
time and phase-locked in relation to the stimuli [2]. Moreover, changes
in the ongoing EEG activity elicited by specific cognitive or
pathological events often occur in specific frequencies bands, hence a
time-frequency analysis of the signals is desirable.
During a motor task, like voluntary movement, desynchronization
phenomena occur in the upper alpha and low beta frequency bands across
the motor cortex. Such desynchronization is observed predominantly in
the hemisphere contralateral to the movement close to the scalp
projection of the hand area (electrode C3 or C4, for right or left hand
movements, respectively) prior to movement onset. But immediately after
movement onset, the desynchronization is bilateral and nearly
symmetrical. It means that the neuronal groups oscillate in a frequency
range during the movement and after that they enter into phase-locking
over a period of time. There is evidence that these phase
desynchronizations and synchronizations between neural signals are
reflected in the EEG in terms of the so-called event-related
desynchronization/synchronization (ERD/ERS).
This phenomenon is usually quantified as the relative change in
spectral power elicited by the event in relation to the baseline
period, assuming that an increase / decrease of the EEG power in a
certain frequency band corresponds to the synchronization /
desynchronization of the underlying neuronal population’s activity,
respectively. Alternatively, ERS/ERD could also be assessed based on
the phase differences across EEG channels, which are thought to reflect
different degrees of synchronization between the underlying neuronal
populations. The Phase-Locking Factor (PLF), which measures the phase
difference between two channel’s signals, has previously been used as a
measure of synchronization between the two signals. A PLF close to 1
means that the two signals are synchronized (with the same phase),
while a PLF close to 0 means that the signals are desynchronized (with
different phases).
In this project, a novel method to assess ERD/ERS based on the
continuous variation of the phase across EEG channels will be designed.
The topographical distribution of the EEG channels on the scalp is
represented in a 2D matrix and the Hilbert transform is used to obtain
the phase of the EEG signal recorded from each channel at each time
point. The ERD/ERS is then computed as the modulus of the phase
gradient along both directions. The proposed methodology was applied to
the EEG data recorded from a healthy volunteer performing an index
finger movement. The results were compared with the conventional
even-related spectral power ERD/ERS measure.
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|
Biofeedback
|
Biofeedback is a recent and general framework where physiological
measurements are used do provide the patient with objective indicators
about his own state. The goal is to help the subjects to learn and
train procedures to self-control some of their brain and physiological
states, such as muscle relaxation.
Biofeedback systems based on electromyography (muscle activity) are the
most traditional ones and the first used in clinical practice to help
patients in muscle relaxation.
Recently, biofeedback systems based on Heart Rate Variability (HRV)
have received a lot of attention because they allow a direct monitoring
of the autonomic nervous system (ANS) that depends, among other
factors, on the central nervous system (CNS).
By this, biofeedback systems seem particularly suitable to help
patients with several psychological and psychiatric disorders such as
anxiety and panic, sleep disorders, Depression, Stress, Fatigue and
Attention deficit / hyperactivity disorder ADHD
(http://www.centerforadd-az.com/)
The huge increasing on the computational power of the smart-phones
allows, today, the implementation of highly portable, complex and
sophisticated medical applications impossible some years ago.
Title:
A biofeedback system for
insomnia
João Sanches and Teresa Paiva
Objectives
The goal of this work is to study and implement a biofeedback system
and training program for insomnia based on MAPSA (Mobile Acquisition
Platform for Sleep Assessment), a mobile platform based on smart-phone
under development in our group.
Description
MAPSA is being developed for long term physiological data monitoring to
be used in the diagnosis of sleep disorders. This platform, highly
portable based on smart-phone, is suitable for a wide range of
applications, such as biofeedback ones.
The objective of this work is to develop a biofeedback application in
MAPSA based on HRV and other physiological and environment data to help
patients with insomina. Besides the engineering component, the work
contains a clinical component where patients from the Centro de
Elecroencefalografia e Neurofisilogia Cl_nica (CENC) will collaborate
for validation and testing purposes.
Requirements:
Solid mathematical background and programming experience, e.g., MatLab,
Java or C++.
Expected results:
Publications in international conferences and journals and a software
prototype to process this type of images.
|
Title:
A biofeedback system for
panic and anxiety
João Sanches
Objectives
The goal of this work is to study and implement a biofeedback system
and training program for help subjects with Anxiety and Panic Attacks
based on MAPSA (Mobile Acquisition Platform for Sleep Assessment), a
mobile platform based on smart-phone under development in our group.
Description
MAPSA is being developed for long term physiological data monitoring.
This platform, highly portable based on smart-phone, is suitable for a
wide range of applications, such as biofeedback ones.
The objective of this work is to develop a biofeedback application in
MAPSA based on HRV and other physiological and environment data to help
subjects suffering from Anxiety and Panic Attacks.
Requirements:
Background on mathematics and physiology.
Outputs:
Patent and publications on international journal and conference.
Location:
ISR/IST and Institute of physiology at the IMM/FMUL
|
Title: Biofeedback
in MAPSA
Individuals exhibit voluntary yet unwittingly control over brain
activation in a daily basis. Nevertheless, the extent to which an
individual can learn to directly and consciously control the activation
of specific brain regions is not yet known. Biofeedback is a procedure
supported by machinery that translates physiological processes into
audio or visual real-time signals, with the goal of controlling the
nervous system activity.
The development of portable devices and systems for biofeedback
purposes is an active field of research with unquestionable importance
in a medical perspective, e.g., in psychiatry, psicology or sleep
diagnosis and treatment, the main focus of our research.
Objectives
The inclusion of a EEG acquisition system, with at least two channels,
in the Mobile Acquisition Platform for Sleep Assessment (MAPSA) and the
implementation in the platform of a Biofeedback application to
illustrate the concept and show the usefulness and feasibility of the
platform for these type of medical applications.
Description
The goal of this work is to incorporate an EEG signal acquisition
functionality in the Mobile Acquisition Platform for Sleep Assessment
(MAPSA). This platform, based on a mobile phone, has been developed in
the last four years in the scope of several MSc thesis for the
acquisition of physiological, clinical and patient data aiming at
the monitoring and diagnosis of sleep disorders.
By including the EEG functionality in the platform it is expected to
improve its power form a diagnosis point of view but also the
increasing of its application range, namely, for Biofeedback
purposes.
Therefore, its is expected, as an output of this work, besides the EEG
acquisition functionality, the implementation of a Biofeedback
application on the platform, using the acquired EEG and ECG data, to be
used in the scope of sleep disorders therapy.
The results of this work should be submitted for publication in an
international journal and conference. It is also expected the
submission of a patent proposal.
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|
Emotional
and Cognitive quantification
|
Title: Real time stress quantification from
physiological and behavioral data
Stress
assessment from physiological and behavioral data is very important in
several practical applications, such as vehicle driving. In most of the
cases the existing methods and systems are cumbersome and non-portable,
which prevents its use in real life conditions.
Stress and attention manifest on the autonomic nervous system activity
that can be indirectly "observed" trough some physiological variables
that can be easily acquired, such as the ECG and Galvanic Skin Response
(GSR).
Description
This
thesis is about stress and attention quantification and detection from
heart rate variability (HRV) and GSR data. As shown in [1],
physiological and behavioral data have the ability of sleep staging and
hypnogram estimation. In the scope of this work a prototype,
based on an arduino, will be designed and constructed to acquire in
real time, ECG, actigraphy and GSR data from the left wrist and
shoulder of the subject.
The data, acquired with this bracelet-type system, highly portable and
non-cumbersome, is transmitted to a smartphone to be stored and
processed in real time. The software application, running in the
smartphone, detects stress, attention deficit or drowsiness and takes
countermeasures to prevent catastrophic events, e.g. car crashing.
Objectives
This
work is composed by two main tasks: 1) Hardware design and assembling
and 2) algorithm design and implementation. In the first step an
Arduino microprocessor/microcontroller based system is used to acquire
ECG, Actigraphy and GSR data at the non-dominant wrist and shoulder of
the subject and sent that data to a smartphone. In the second step,
algorithms running at the smartphone analyze the data to quantify the
levels of stress, attention and sleep. The software should
generate countermeasures, such as visual or audio stimulus, to induce
appropriated levels of attention, decrease stress and prevent
drowsiness.
Requirements:
Mathematical background and programming experience in MatLab.
Results:
Papers in international journals and conferences and a prototype.
Location:
ISR/IST and CENC
References
[1] Domingues, A.; Paiva, T.; Sanches, J., "Hypnogram and Sleep
Parameter Computation from Activity and Cardiovascular data,"
Biomedical Engineering, IEEE Transactions on , vol.PP, no.99, pp.1,1,
doi: 10.1109/TBME.2014.2301462, 2014
|
Title: Dreams, Emotional contents and Brain
computer interfaces
Dreaming
is a highly complex process not yet completely understood. One of its
known functions is the consolidation of lived experiences during the
awakening state. Some of these consolidation tasks contain motor
components that can be detected and processed under the classical
framework of motor imagery in brain computer interface (BCI)
systems.
Description
In
this work, EEG data collected during sleep, in the scope of
polysomnographic exams, are analyzed and processed with
well-established techniques of brain motor imagery, in order to detect
types of dreamed movements and actions. A brain computer interface
system is trained during the awake state with well established motor
paradigms aiming at detecting broad classes of movements, such as, left
or right limb movements during sleep.
Objectives
The
objectives of this work is to design a brain computer interface system,
typically used during the awakening state in several interaction tasks,
such as with handicapped subjects, in the scope of sleep and dreaming
studies. The physiological foundations of the problem need to be
studied and experimentally validated in order to prove the hypothesis
that motor imagery is able to detect imagined movements during sleep
and dreaming.
Requirements:
Mathematical background and programming experience in MatLab.
Results:
Papers in international journals and conferences and a prototype of the
detection system.
Location:
ISR/IST and CENC
|
Title: Dream contents estimation from
polysomnographic data
Dreams are by far one of the most unknown phenomena
in terms of standard physiological data.
Dreams, mostly those occurring in REM sleep, have important emotional
components. Emotions in dreams can vary between negative and positive
modalities, being the negative ones more frequent.
In awake states emotions can be detected by changes in ECG namely due
to tachycardia measured from the ECG waveform. The autonomic control is
different in awake and REM sleep. Furthermore, REM sleep is associated
with frequency changes in HR. However, it is not known whether
these changes are associated with specific emotional states or other
dream components.
Description
In
this work, dreams collected during REM sleep are characterized in a
psychological basis from dream reports collected in normal subjects in
the sleep laboratory during REM awakenings.
Additionally, since the most important component of the HRV is related
with the autonomic nervous system, other measures of its activity are
also acquired such as galvanic skin response (GSR). The time constant
differences on these two responses need to be taken into account.
The dream reports are stored together with neurophysiological data that
include ECG and GSR information, for offline processing and analysis
with statistical signal processing techniques and machine learning
tools.
Objectives
The
main goals of this work are: 1) Correlate the psychological emotional
reports with the physiological/autonomic data and 2) find specificities
of this correlation.
A set of labels, representing broad classes of emotional states during
dreaming are defined and correlated with physiological data using data
mining and machine learning tools, in order to infer the emotional
contents during sleep without having to awake the patients.
Requirements:
Mathematical background and programming experience in MatLab.
Results:
Papers in international journals and conferences.
Location:
ISR/IST and CENC |
Title: Dream emotional states, Time event
detection and Autonomic activity by HRV/ECG waveform analysis and GSR
data
Up
to the moment it is not known how to identify dream states from
physiological data or even if a subject is dreaming or not. In spite of
this it is known that dreams contents are correlated with some changes
in EEG frequencies. However the specific correlation is not known.
Description
In
this work, dreams collected during REM sleep are characterized in a
psychological basis from dream reports collected from normal subjects
in the sleep laboratory during REM awakenings.
Additionally, since the most important component of the heart rate
variability (HRV) is related with the autonomic nervous system, other
measures of its activity are also acquired such as galvanic skin
response (GSR).
The dream reports are stored together with neurophysiological data,
which include ECG information, for offline processing and analysis with
statistical signal processing techniques and machine learning tools.
Objectives
The
main goal of this work is to identify the exact moments of dream events
and the classification of the corresponding contents. This implies: 1)
using variables describing the observations, e.g., EEG, EOG, EMG and
ECG and 2) apply classification techniques of temporal series to
identify dream states. 3) The ground truth is in this case the
existence or not of dream reported during the forced awakening from REM
sleep.
The ultimate goal is detecting the presence of dreaming states
and the corresponding onset time events to automatically annotate long
duration polysomnographic data.
Requirements:
Mathematical background and programming experience in MatLab.
Results:
Papers in international journals and conferences.
Location:
ISR/IST and CENC
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Epilepsy
|
Title: Characterization and detection of
epileptic seizures from physiological and behavioural data
Advisors: João Sanches (ISR/IST) Carla Bentes (Neurologia, HSM/FMUL)
and Rita Peralta (Neurologia, HSM/FMUL)
Description:
Detection and characterization of epileptic seizures is a very
important goal for an accurate knowledge of the disease, in order to
adopt the appropriated therapeutic measures and strategies. Moreover,
the automatic detection of epileptic seizures is also very important
for sake of patient safety. Epileptic seizures, especially if
consciousness impairment or generalization occurs, may be associated
with severe traumatic injuries. Furthermore, epilepsy-related causes of
death account for 40% of mortality in these patients and include
accidents during the epileptic attack but also sudden unexpected death
episodes (SUDEP).
Detection of seizures is accurate in laboratorial and hospitalar
conditions where several data modalities, e.g. EEG, ECG and video, are
acquired with highly complex and sophisticated equipment and analyzed
by experts.
These exams, however, are expensive, time consuming, highly cumbersome
and intrusive for the patients, preventing its use in ambulatory
conditions during normal day life conditions. Additionally, the
difficulty of monitoring the patient for long periods during his
quotidian life also prevents the characterization of uncommon or
patients unrecognized seizures.
Objectives:
The objective of this work is to design, implement
and validate a portable system to monitor and detect epileptic
seizures, especially with motor phenomenology, during wakefulness
and sleep, based on physiological and behavioral data.
The main sources of data to achieve the proposed goal are the ECG and
Actigraphy.
The ECG will be used to perform Heart Rate Variability (HRV) analysis
to estimate the autonomic activity. A seizure can present with
autonomic symptoms and autonomic dysfunction due to epilepsy can
contribute to sudden unexpected death episodes.
Actigraphy data, acquired from the non dominant wrist of the patient,
in ambulatory conditions and from the four limbs at the Hospital,
contain useful information about the motor activity of the patient.
In this work, a set of discriminative features are extracted from the
HRV and Actigraphy data aiming at detecting seizures and generate
alarms and automatic annotations that will help the medical staff in
the detection and characterization of the disease. Special attention
will be paid to seizures during sleep, frequently unrecognized by the
patient in his daily life. Part of the work will investigate the
discriminative power of actigraphy data acquired from an actigraph
sensor located in the patient bed especially tuned to detect
generalizes seizures, only from movement patterns.
Requirements:
Solid mathematical background and programming experience in MatLab.
Results:
Papers in international journals and conferences and
a prototype of the
detection system.
Location:
ISR/IST |
Title: Epileptic seizure
detection
in children during sleep
Objectives:
The objective of this project is to create and test algorithms for
detecting seizures related to the movement of actigraphy data starting
symptoms.
The objective of this project is twofold: to study and characterize
typical movement patterns during seizures in children, from a
fundamental
research perspective, and to design and implementing of a prototype
system to alert parents or medical team of epileptic seizures onset.
Description:
Epileptic seizures with movement disorders are potentially dangerous in
children during sleep because they can cause injuries as a result of
uncontrolled movements during the crises.
However, movements during sleep are normal and a simple movement
detector to detect seizures is useless.
Actigraphy is the natural choice to this project. Actigraphy signals,
obtained from 3D accelerometers usually placed at the non-dominant
wrist of the subject, are able to discriminate normal from disturbed
movements where global movement features, not associated with
specific tasks, can be captured. Additionaly, actigraph sensors are
noninvasive and do not involve any experimental apparatus that can
interfere with the normal sleep process of children.
So the goal of this project is to use actigraph data obtained from
childrens during normal sleep and during epileptic seizures and apply
statistical signal processing tecniques to compute relevant features
and use machine learning algorithms to detect epileptic sizure events.
Requirements:
Solid mathematical background and programming experience in MatLab.
Results:
Papers in international journals and conferences and a prototype of the
detection system.
Location:
ISR/IST
|
Physiology
|
Title: Quantificação da actividade
do SNA a partir do ritmo cardíaco e dilatação das pupilas em ambiente
de condução automóvel
João Sanches (ISR/IST), 2013
Objectives
O objectivo deste projecto é o de estudar, desenvolver e implementar
métodos para quantificar a actividade do Sistema Nervoso Autónomo e da
atenção a apartir da variabilidade cardíaca, da dilatação das pupilas e
de um canal de EEG, usando métodos de processamento de imagens e
processamento de sinais fisiológicos para efeitos de monitorização em
tempo real do estado de atenção e concentração em ambiente de codução
automóvel.
Description
A actividade do sistema nervoso autónomo depende fortemente do
sistema nervoso central e portanto é influenciado por estados
cerebrais, tais como atenção, sono e relaxamento, e emocionais, tais
como ansiedade e pânico, A avaliação em tempo real da actividade do SNA
é impotante em diversas aplicações relacionadas com o sono, disfunções
psiquiátricas ou em aplicações específicas como sejam a avaliação
emocional de condutores em tempo real para detectar sonolência ou falta
de atenção durante a condução.
O objectivo deste projecto é essencialmente o de desenvolver os
algoritmos e montar o aparato experimental que permita criar um
protótipo para esta última aplicação, isto é: através da aquisição do
ECG, de um canal de EEG e da análise das pupilas do condutor, detectar
estados cerebrais não apropriados para a condução e gerar os alarmes
apropriados para evitar acidentes.
|
Title: Desenho, teste e
validação de um modelo do sistema cardio-vascular e a sua interacção
com o sistema nervoso autónomo: baro and chemo reflexes
João Sanches (ISR/IST) e Isabel Rocha (IF/FMUL), 2012
Objectives
Desenvolvimento de um modelo, já parcialmente implementado
emMatLab/Simulink, que reproduz o comportamento da pressão arterial e
seus determinantes ( frequência cardíaca, débito cardíaco, resistência
vascular periférica, volume sistólico, amplitude e frequência dos
movimentos respiratórios) num teste de stress respiratório (
respiração profunda)
O objectivo deste modelo é compreender a contribuição individual e
integrada destes componentes no controlo integrado cardio-respiratório.
Pretende-se também que este modelo possa ser utilizado durante as aulas
de fisiologia como simulador da regulação integrada cardiorrespiratória.
Description
O sistema nervoso autónomo, em conjunto com os sistema endócrino e
imunitário, contribui para a manutenção da homeodinamia
controlando as funções viscerais instante a instante. Neste sentido,
torna-se fundamental a sua avaliação fidedigna com o objectivo de
melhor entender os mecanismos fisiológicos e, também, os
fisiopatologicos subjacentes a patologias cardiovasculares que cursem
com alterações respiratórias.
Existem conjuntos de manobras provocativas do sistema nervoso autónomo
que permitem uma avaliação da regulação do SNA, de uma forma não
invasiva e reproductivel. Conceptualmente, o teste da respiração
profunda permite avaliar o comportamento do reflexo quimioreceptor e a
sua intervenção na regulação integrada cardiorrespiratória em
Indivíduos normais e em doentes.
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Title: Desenho, teste e
validação de um modelo do sistema cardio-vascular e a sua interacção
com o sistema nervoso autónomo: reflexos cardíacos
João Sanches (ISR/IST) e Isabel Rocha (IF/FMUL), 2012
Objectives
Desenvolvimento de um modelo, já parcialmente implementado
emMatLab/Simulink, que reproduz o comportamento da pressão arterial e
seus determinantes ( frequência cardíaca, débito cardíaco, resistência
vascular periférica, inotropismo, volume sistolico) num teste de
stress ortostático ( teste de ortostatismo passivo/teste de tilt)
O objectivo deste modelo é compreender a contribuição individual e
integrada destes componentes no controlo da pressão arterial.
Pretende-se também que este modelo possa ser utilizado durante as aulas
de fisiologia como simulador da regulação do sistema cardio-vascular
pelo sistema nervoso autónomo.
Description
O sistema nervoso autónomo, em conjunto com os sistema endócrino e
imunitário, contribui para a manutenção da homeodinamia
controlando as funções viscerais instante a instante. Neste sentido,
torna-se fundamental a sua avaliação fidedigna com o objectivo de
melhor entender os mecanismos fisiológicos e, também, os
fisiopatologicos subjacentes a patologias cardiovasculares.
Existem conjuntos de manobras provocativas do sistema nervoso autónomo
que permitem uma avaliação da regulação do SNA, de uma forma não
invasiva e reproductivel. Conceptualmente, o teste de ortostatismo
passivo permite avaliar o comportamento do reflexo baroreceptor e a sua
intervenção na regulação da pressão arterial em Indivíduos normais e em
doentes.
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Title: Desenho, teste e
validação de um modelo do sistema cardio-vascular e a sua interacção
com o sistema nervoso autónomo: reflexo baroreceptor
João Sanches (ISR/IST) e Isabel Rocha (IF/FMUL), 2012
Objectives
Desenvolvimento de um modelo, já parcialmente implementado
emMatLab/Simulink, que reproduz o comportamento da pressão arterial e
seus determinantes ( frequência cardíaca, débito cardíaco, resistência
vascular periférica, volume sistólico, inotropismo) num teste de
stress ortostático ( teste de ortostatismo passivo/teste de tilt)
O objectivo deste modelo é compreender a contribuição individual e
integrada destes componentes no controlo da pressão arterial.
Pretende-se também que este modelo possa ser utilizado durante as aulas
de fisiologia como simulador da regulação do sistema cardio-vascular
pelo sistema nervoso autónomo.
Description
O sistema nervoso autónomo, em conjunto com os sistema endócrino e
imunitário, contribui para a manutenção da homeodinamia
controlando as funções viscerais instante a instante. Neste sentido,
torna-se fundamental a sua avaliação fidedigna com o objectivo de
melhor entender os mecanismos fisiológicos e, também, os
fisiopatologicos subjacentes a patologias cardiovasculares.
Existem conjuntos de manobras provocativas do sistema nervoso autónomo
que permitem uma avaliação da regulação do SNA, de uma forma não
invasiva e reproductivel. Conceptualmente, o teste de ortostatismo
passivo permite avaliar o comportamento do reflexo baroreceptor e a sua
intervenção na regulação da pressão arterial em Indivíduos normais e em
doentes.
|
Title: A
Mathematical model of the Cardiovascular System in the scope of heart
coherence
The cardio vascular system (CVS) promotes the blood flow across the
body in order to properly deliver oxygen and nutrients to the
cells at every organ and tissue. This feedback system operates in a
close-loop basis in order to adapt the blood flow and pressure in the
large and small vessels according the external and internal specific
conditions that are mainly related with the interaction of the subject
with the surrounding environment.
These physiological parameters, flow and pressure, are controlled by
the autonomic nervous system (ANS) by acting in the heart and vessels.
The rate and contractility of the heart and the section of the small
and medium vessels are the main parameters controlled by the ANS in
order to keep the constancy of the blood pressure (BP), called
Homeostasis.
The control of this system, performed by the ANS, is mainly performed
in great extend at involuntary and unconscious level. However it
is known that the central nervous system (CNS) is able to influence
several parameters of the CVS. Additionally, there are several
techniques reported in the literature that are able to change some
parameters of the CVS, most of them based on voluntary procedures
related with respiration.
Heart Coherence seems to be a resonant condition of the CVS where
regularity patterns and magnitude of the Heart Rate Variability (HRV)
are maximized. The specific set point is associated with health
conditions and positive brain states. More important, accurate and
realistic mathematical models to describe the CVS can be of great help
to understand and diagnosis some dysautonomia disorders, such as
Vasovagal Syncope (VS) and Postural Orthostatic Position Syndrome
(POTS) or other very common disease, some times with unknown etiology,
like hypertension.
Objectives
The goal of this work is to derive a physiological based mathematical
model to describe the CVS and simulate the respiration effects on it.
The model, with parameters tuned with information obtained from
physiology literature, should be able to reproduce the
physiological measures of heart rate and mean arterial pressure (MAP)
recorded during the Hewing protocol with the tilt table usually used to
assess the performance of the ANS and detect dysautonomia diseases,
such as, VS and POTS. The model should also be able to reproduce Heart
Coherence with a proper respiration excitation.
Figure - Tilt table used in the Hewing protocol for ANS assessment
Description
Heart, vessels and receptors (baro and chemio) are the main efferent
components of the CVS controlled by the ANS, located at the brain stem.
This system can be modeled under the Control Theory framework as a
canonical feedback architecture. The control pathway is composed by the
two branches of the ANS, parasympathetic (vagus) and sympathetic fibers
that code the control signal by mean of the firing rate intensity.
The model, based on physiological information, will be simulated with
the graphical programming language Simulink from MalLab and it is
expected to improve the previous Master thesis [1].
Figure - Baroreflex simulink model
The main goal of this work is to improve the model derived in [1]
(displayed in Figure above) by including the effect of respiration in
order to simulate and reproduce the heart coherence, a pocessess
involved in relaxation and emotions self-regulation.
Requirements:
Background on mathematics and physiology.
Outputs: Patent and
publications on international journal and conference.
Location: ISR/IST
and Institute of physiology at the IMM/FMUL
References:
[1] José Santos, A Baroreflex Control Model Using Head-Up Tilt Test,
Master Thesis at IST and Inst. Fisiologia IMM/FMUL 2008.
|
Title: Modeling of the
Haemodynamic
Response Function based on Physiological Principles
The metabolic activity of brain cells may be indirectly measured by
several means, namely, by the BOLD signal obtained by using functional
MRI (Magnetic Resonance Imaging) or directly by using invasive methods.
The metabolic activity of these cells is related with the brain
activity as response of external or internal stimulus and induces
changes on several physiologic variables such as blood flow and
oxygenated / non oxygenated hemoglobin ratio.
The relation of the blood flow and oxygenated hemoglobin concentration
with brain activity is a complex process depending on several
physiologic mechanisms, which are not completely understood. On the
other hand, this knowledge is crucial for several purposes, such as,
robust indirect detection of activated region in the functional MRI
scope.
Objectives
The goal of this work is to deeply study the physiologic mechanisms
involved in the hemodynamic response of the tissues (namely in the
brain) to design realistic theoretical sound and physiologic based
mathematically models for this response. Validate the model indirectly
with fMRI and directly by invasive methods in mouse.
Description
This work is the continuation of the Master Thesis [Rita Gafaniz,
2010] aiming to derive a mathematical model to describe the
relation between electrical neuronal activity and metabolism. This is a
basic and central issue in several scopes such as functional MRI.
However, it is also related with the basic processes involved in sleep.
Requirements:
Solid mathematical background and programming experience, e.g., MatLab
or C++.
References
[1] COUPLING OF NITRIC OXIDE TRANSPORT AND BLOOD FLOW: A COMPUTATIONAL
MODELING APPROACH, A Thesis Submitted to the Faculty of Drexel
University by Xuewen Chen in partial fulfillment of the requirements
for the degree of Doctor of Philosophy, March 2007.
[2] Timing of potential and metabolic brain energy, Jakob Korf and Jan
Bert Gramsbergen, Journal of Neurochemistry, 2007, 103, 1697–1708.
[3] Dynamic Modeling for Modulation of ATP Concentration at the
Endothelial Surface by Viscous Shear Flow, Kairong Qin, Zhe Xu, Hui
Zhang, Cheng Xiang, Shuzhi Sam Ge and Zonglai Jiang, Proceedings of the
2006 IEEE International Symposium on Intelligent Control Munich,
Germany, October 4-6, 2006.
[4] Vasoconstrictor and Vasodilator Effects of Adenosine in the Mouse
Kidney due to Preferential Activation of A1 or A2 Adenosine Receptors,
P. B. Hansen, S. Hashimoto, M. Oppermann, Y. Huang, J. P. Briggs, and
J. Schnermann, THE JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL
THERAPEUTICS Vol. 315, No. 3, JPET 315:1150–1157, 2005.
[5] Discovery of Some of the Biological Effects of Nitric Oxide and its
Role in Cell Signaling, Ferid Murad, Bioscience Reports, Vol. 24, Nos.
4/5, August/October 2004 ( (c) 2005).
[6] Nitric Oxide: Involvement in the Nervous Control of Cardiovascular
Function, L. N. Shapoval, Neurophysiology, Vol. 36, Nos. 5/6, 2004.
[7] Sameer A. Sheth, Masahito Nemoto, Michael Guiou, Melissa Walker,
Nader Pouratian, and Arthur W. Toga, Linear and Nonlinear Relationships
between Neuronal Activity, Oxygen Metabolism, and Hemodynamic
Responses, Neuron, Vol. 42, 347–355, April 22, 2004.
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Title: Muscle activation
and
strength: a dynamic model
João Sanches(IST) and Mamede de Carvalho(FMUL)
Objectives
The goal of this work is the derivation of a theorectical dynamic model
for motor unit recruitment on mild muscular contraction, imvolving
frequency and regularity of the motor unit firing . The validation of
the model will be done with synthetic and real data. The aim is to
investigate the hypothesis that single motor unit recruitment variation
is dependent on the normal function of the cortico-spinal tract. This
work involves laboratorial work at the Physiology Institute in the FMUL
to acquire real data and measure neuronal activity, needed to validate
the model.
Description
The strength of the muscle depends on the number and frequency of the
recruited motor unit. On slight contraction the different motor units
are easily recognized. Mild contration activates a limited number of
motor units which fired at a frequency of about 7 Hz. The
inter-discharge interval of single motor units activation shows some
variation. Based on previous exploratory investigation, this variation
is decreased in patients with corticospinal tract lesion. We plan to
establish a recording set up to register motor units recruitment on
mild contraction in controls and patients. The goal of this work is
derive a mathematical model to describe this process where the motor
units are modeled in a stochastic framework. This model can be used to
explain and help in the diagnosis of certain neurological disorders
where motor function is disturbed. In the scope of this work,
laboratorial experiments should be designed to acquired data at the
Institute of Physiology – FMUL, used to tune and validate the model.
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Title: Estimation of the
haemodynamic response to epileptic activity in EEG-fMRI data
Advisers:
João Sanches and Patrícia Figueiredo (IST)
The recent technical advances in the simultaneous acquisition of the
electron-encephalogram (EEG) with functional magnetic resonance imaging
(fMRI) have made it possible to localize epileptogenic brain networks
with good spatial resolution, through the identification of the
haemodynamic correlates of (inter-) ictal electrical discharges. One of
the major limitations of this technique has been the uncertainty
regarding the exact shape of the haemodynamic response function (HRF),
which may hinder its detection sensitivity. In fact, the commonly used
canonical HRF is most likely altered in epileptogenic brain regions and
it would therefore be desirable to employ data analysis methods that
allow HRF estimation simultaneously with activity detection.
Objectives
Estimation of the HRF to inter-ictal and ictal discharges from EEG-fMRI
data in focal epilepsy.Estimation of the HRF to inter-ictal and ictal
discharges from EEG-fMRI data in focal epilepsy.
Description
The work will consist on the implementation of appropriate algorithms
for the analysis of simultaneous EEG-fMRI data, collected from
epileptic patients during both inter-ictal and ictal discharges. In
particular, a new method will be tested for the estimation of the HRF,
simultaneously with activity detection, based on a Bayesian approach.
The results will be compared with alternative methods used in the
literature.
References
- LeVan P, Tyvaert L, Moeller F, Gotman J. (2010)
Independent component analysis reveals dynamic ictal BOLD responses in
EEG-fMRI data from focal epilepsy patients. Neuroimage. 49(1):366-78.
- David Afonso, Jo_o Sanches and Martin H. Lauterbach
(2008), Joint Bayesian detection of brain activated regions and local
HRF estimation in functional MRI, ICASSP.
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