Data-Driven Motion Detection and Characterization in PET Brain Scans Using List Mode

Head motion during a Positron Emission Tomography (PET) brain scan can considerably degrade image quality. External motion-tracking devices have proven successful in minimizing this effect, but the associated time, maintenance, and workflow changes inhibit their widespread clinical use. List-mode PET acquisition allows for the retroactive analysis of coincidence events on any time scale throughout a scan, and therefore potentially offers a data-driven motion detection and characterization technique. An algorithm was developed to parse list-mode data, divide the full acquisition into short scan intervals, and calculate the line-of-response (LOR) midpoint average for each interval. These LOR midpoint averages, known as “radioactivity centroids,” were presumed to represent the center of the radioactivity distribution in the scanner, and it was thought that changes in this metric over time would correspond to intra-scan motion.

Several scans were taken of the 3D Hoffman brain phantom on a GE Discovery IQ PET/CT scanner to test the ability of the radioactivity to indicate intra-scan motion. Each scan incrementally surveyed motion in a different degree of freedom (2 translational and 2 rotational). The radioactivity centroids calculated from these scans correlated linearly to phantom positions/orientations. Centroid measurements over 1-second intervals performed on scans with ~1mCi of activity in the center of the field of view had standard deviations of 0.026 cm in the x- and y-dimensions and 0.020 cm in the z-dimension, which demonstrates high precision and repeatability in this metric. Radioactivity centroids are thus shown to successfully represent discrete motions on the submillimeter scale. It is also shown that while the radioactivity centroid can precisely indicate the amount of motion during an acquisition, it fails to distinguish what type of motion occurred.

Control of the innate immune response by the mevalonate pathway.

Deficiency in mevalonate kinase (MVK) causes systemic inflammation. However, the molecular mechanisms linking the mevalonate pathway to inflammation remain obscure. Geranylgeranyl pyrophosphate, a non-sterol intermediate of the mevalonate pathway, is the substrate for protein geranylgeranylation, a protein post-translational modification that is catalyzed by protein geranylgeranyl transferase I (GGTase I). Pyrin is an innate immune sensor that forms an active inflammasome in response to bacterial toxins. Mutations in MEFV (encoding human PYRIN) result in autoinflammatory familial Mediterranean fever syndrome. We found that protein geranylgeranylation enabled Toll-like receptor (TLR)-induced activation of phosphatidylinositol-3-OH kinase (PI(3)K) by promoting the interaction between the small GTPase Kras and the PI(3)K catalytic subunit p110δ. Macrophages that were deficient in GGTase I or p110δ exhibited constitutive release of interleukin 1β that was dependent on MEFV but independent of the NLRP3, AIM2 and NLRC4 inflammasomes. In the absence of protein geranylgeranylation, compromised PI(3)K activity allows an unchecked TLR-induced inflammatory responses and constitutive activation of the Pyrin inflammasome.

Improved Accuracy in Optical Motion Capture Measurements Leads to Increased Sensitivity to Kinematic Changes

Clinical optical motion capture allows us to obtain kinematic and kinetic outcome measures that aid clinicians in diagnosing and treating different pathologies affecting healthy gait. The long term aim for gait centres is for subject-specific analyses that can predict, prevent, or reverse the effects of pathologies through gait retraining. To track the body, anatomical segment coordinate systems are commonly created by applying markers to the surface of the skin over specific, bony anatomy that is manually palpated. The location and placement of these markers is subjective and precision errors of up to 25mm have been reported [1]. Additionally, the selection of which anatomical landmarks to use in segment models can result in large angular differences; for example angular differences in the trunk can range up to 53o for the same motion depending on marker placement [2]. These errors can result in erroneous kinematic outcomes that either diminish or increase the apparent effects of a treatment or pathology compared to healthy data. Our goal was to improve the accuracy and precision of optical motion capture outcome measures. This thesis describes two separate studies. In the first study we aimed to establish an approach that would allow us to independently quantify the error among trunk models. Using this approach we determined if there was a best model to accurately track trunk motion. In the second study we designed a device to improve precision for test, re-test protocols that would also reduce the set-up time for motion capture experiments. Our method to compare a kinematically derived centre of mass velocity to one that was derived kinetically was successful in quantifying error among trunk models. Our findings indicate that models that use lateral shoulder markers as well as limit the translational degrees of freedom of the trunk through shared pelvic markers result in the least amount of error for the tasks we studied. We also successfully reduced intra- and inter-operator anatomical marker placement errors using a marker alignment device. The improved accuracy and precision resulting from the methods established in this thesis may lead to increased sensitivity to changes in kinematics, and ultimately result in more consistent treatment outcomes.

Meniere’s, Migraine & Motion Sickness

CONCLUSION Elevated MSS in MD is likely to be a consequence of the onset of MD and not migraine per se. OBJECTIVES Pathologies of the vestibular system influence motion sickness susceptibility (MSS). Bilateral vestibular deficits lower MSS, vestibular neuritis or benign paroxysmal positional vertigo have little overall effect, whereas vestibular migraine elevates MSS. However, less is known about MSS in Meniere’s disease (MD), a condition in which many patients experience vestibular loss and migraine symptoms. METHODS We conducted an online survey that posed diagnostic and disease questions before addressing frequency of headaches, migraines, visual display dizziness (VDD), syncope, social life and work impact of dizziness (SWID4) and motion sickness susceptibility (MSSQ). The two groups were: diagnosed MD individuals with hearing loss (n=751) and non-MD individuals in the control group (n=400). RESULTS The MD group showed significantly elevated MSS, more headache and migraine, increased VDD, higher SWID4 scores, and increased syncope. MSS was higher in MD than controls only after the development of MD but not before, nor in childhood. Although elevated in MD compared with controls, MSS was lower than migraine patients from past data. Multivariate analysis revealed VDD, SWID4 and MSS in adulthood as the strongest predictors of MD, but not headache nor migraine.

Towards optical polarization control of laser-driven proton acceleration in foils undergoing relativistic transparency

Control of the collective response of plasma particles to intense laser light is intrinsic to relativistic optics, the development of compact laser-driven particle and radiation sources, as well as investigations of some laboratory astrophysics phenomena. We recently demonstrated that a relativistic plasma aperture produced in an ultra-thin foil at the focus of intense laser radiation can induce diffraction, enabling polarization-based control of the collective motion of plasma electrons. Here we show that under these conditions the electron dynamics are mapped into the beam of protons accelerated via strong charge-separation-induced electrostatic fields. It is demonstrated experimentally and numerically via 3D particle-in-cell simulations that the degree of ellipticity of the laser polarization strongly influences the spatial-intensity distribution of the beam of multi-MeV protons. The influence on both sheath-accelerated and radiation pressure-accelerated protons is investigated. This approach opens up a potential new route to control laser-driven ion sources.

Functions of the SLC36 transporter Pathetic in growth control of Drosophila sensory neurons

Thesis (Ph.D.)--University of Washington, 2016-08

Multirobot Tethering for Localization and Control

Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. This becomes more critical if the state estimate is an integral part of system control. We investigate the use of particle filter estimation techniques on a hovercraft vehicle. The marginally stable dynamics of a hovercraft require reliable state estimates for proper stability and control. We use the Monte Carlo localization method, which implements a particle filter in a recursive state estimate algorithm. An H-infinity controller, designed to accommodate the latency inherent in our state estimation, provides stability and controllability to the hovercraft. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. By tracking and controlling the secondary robot, we can position the mobile feature throughout the environment to ensure a high confidence estimate, thus maintaining stability in the system. A laser rangefinder is the sensor the hovercraft uses to track the secondary robot, observe the environment, and facilitate successful localization and stability in motion.

ENABLING HARDWARE TECHNOLOGIES FOR AUTONOMY IN TINY ROBOTS: CONTROL, INTEGRATION, ACTUATION

The last two decades have seen many exciting examples of tiny robots from a few cm3 to less than one cm3. Although individually limited, a large group of these robots has the potential to work cooperatively and accomplish complex tasks. Two examples from nature that exhibit this type of cooperation are ant and bee colonies. They have the potential to assist in applications like search and rescue, military scouting, infrastructure and equipment monitoring, nano-manufacture, and possibly medicine. Most of these applications require the high level of autonomy that has been demonstrated by large robotic platforms, such as the iRobot and Honda ASIMO. However, when robot size shrinks down, current approaches to achieve the necessary functions are no longer valid. This work focused on challenges associated with the electronics and fabrication. We addressed three major technical hurdles inherent to current approaches: 1) difficulty of compact integration; 2) need for real-time and power-efficient computations; 3) unavailability of commercial tiny actuators and motion mechanisms. The aim of this work was to provide enabling hardware technologies to achieve autonomy in tiny robots. We proposed a decentralized application-specific integrated circuit (ASIC) where each component is responsible for its own operation and autonomy to the greatest extent possible. The ASIC consists of electronics modules for the fundamental functions required to fulfill the desired autonomy: actuation, control, power supply, and sensing. The actuators and mechanisms could potentially be post-fabricated on the ASIC directly. This design makes for a modular architecture. The following components were shown to work in physical implementations or simulations: 1) a tunable motion controller for ultralow frequency actuation; 2) a nonvolatile memory and programming circuit to achieve automatic and one-time programming; 3) a high-voltage circuit with the highest reported breakdown voltage in standard 0.5 μm CMOS; 4) thermal actuators fabricated using CMOS compatible process; 5) a low-power mixed-signal computational architecture for robotic dynamics simulator; 6) a frequency-boost technique to achieve low jitter in ring oscillators. These contributions will be generally enabling for other systems with strict size and power constraints such as wireless sensor nodes.

Effect of remote ischaemic preconditioning in cardiac dysfunction and end-organ injury following cardiac surgery with cardiopulmonary bypass in children: A translational approach investigating clinical outcome and myocardial molecular biology

Congenital heart disease (CHD) is the most common birth defect, causing an important rate of morbidity and mortality. Treatment of CHD requires surgical correction in a significant percentage of cases which exposes patients to cardiac and end organ injury. Cardiac surgical procedures often require the utilisation of cardiopulmonary bypass (CPB), a system that replaces heart and lungs function by diverting circulation into an external circuit. The use of CPB can initiate potent inflammatory responses, in addition a proportion of procedures require a period of aortic cross clamp during which the heart is rendered ischaemic and is exposed to injury. High O2 concentrations are used during cardiac procedures and when circulation is re-established to the heart which had adjusted metabolically to ischaemia, further injury is caused in a process known as ischaemic reperfusion injury (IRI). Several strategies are in place in order to protect the heart during surgery, however injury is still caused, having detrimental effects in patients at short and long term. Remote ischaemic preconditioning (RIPC) is a technique proposed as a potential cardioprotective measure. It consists of exposing a remote tissue bed to brief episodes of ischaemia prior to surgery in order to activate protective pathways that would act during CPB, ischaemia and reperfusion. This study aimed to assess RIPC in paediatric patients requiring CHD surgical correction with a translational approach, integrating clinical outcome, marker analysis, cardiac function parameters and molecular mechanisms within the cardiac tissue. A prospective, single blinded, randomized, controlled trial was conducted applying a RIPC protocol to randomised patients through episodes of limb ischaemia on the day before surgery which was repeated right before the surgery started, after anaesthesia induction. Blood samples were obtained before surgery and at three post-operative time points from venous lines, additional pre and post-bypass blood samples were obtained from the right atrium. Myocardial tissue was resected during the ischaemic period of surgery. Echocardiographic images were obtained before the surgery started after anaesthetic induction and the day after surgery, images were stored for later off line analysis. PICU surveillance data was collected including ventilation parameters, inotrope use, standard laboratory analysis and six hourly blood gas analysis. Pre and post-operative quantitation of markers in blood specimens included cardiac troponin I (cTnI) and B-type natriuretic peptide (BNP), inflammatory mediators including interleukins IL-6, IL-8, IL-10, tumour necrosis factor (TNF-α), and the adhesion molecules ICAM-1 and VCAM-1; the renal marker Cystatin C and the cardiovascular markers asymmetric dymethylarginine (ADMA) and symmetric dymethylarginine (SDMA). Nitric oxide (NO) metabolites and cyclic guanosine monophosphate (cGMP) were measured before and after bypass. Myocardial tissue was processed at baseline and after incubation at hyperoxic concentration during four hours in order to mimic surgical conditions. Expression of genes involved in IRI and RIPC pathways was analysed including heat shock proteins (HSPs), toll like receptors (TLRs), transcription factors nuclear factor κ-B (NF- κ-B) and hypoxia inducible factor 1 (HIF-1). The participation of hydrogen sulfide enzymatic genes, apelin and its receptor were explored. There was no significant difference according to group allocation in any of the echocardiographic parameters. There was a tendency for higher cTnI values and inotropic score in control patients post-operatively, however this was not statistically significant. BNP presented no significant difference according to group allocation. Inflammatory parameters tended to be higher in the control group, however only TNF- α was significantly higher. There was no difference in levels of Cystatin C, NO metabolites, cGMP, ADMA or SDMA. RIPC patients required shorter PICU stay, all other clinical and laboratory analysis presented no difference related to the intervention. Gene expression analysis revealed interesting patterns before and after incubation. HSP-60 presented a lower expression at baseline in tissue corresponding to RIPC patients, no other differences were found. This study provided with valuable descriptive information on previously known and newly explored parameters in the study population. Demographic characteristics and the presence of cyanosis before surgery influenced patterns of activity in several parameters, numerous indicators were linked to the degree of injury suffered by the myocardium. RIPC did not reduce markers of cardiac injury or improved echocardiographic parameters and it did not have an effect on end organ function; some effects were seen in inflammatory responses and gene expression analysis. Nevertheless, an important clinical outcome indicator, PICU length of stay was reduced suggesting benefit from the intervention. Larger studies with more statistical power could determine if the tendency of lower injury and inflammatory markers linked to RIPC is real. The present results mostly support findings of larger multicentre trials which have reported no cardiac benefit from RIPC in paediatric cardiac surgery.

Analysis and control of transient spectra using time-dependent density functional theory.

215 p.

Brain emotional learning based control of a SDOF structural system with a MR damper

This paper describes the application of a Brain Emotional Learning (BEL) controller to improve the response of a SDOF structural system under an earthquake excitation using a magnetorheological (MR) damper. The main goal is to study the performance of a BEL based semi-active control system to generate the control signal for a MR damper. The proposed approach consists of a two controllers: a primary controller based on a BEL algorithm that determines the desired damping force from the system response and a secondary controller that modifies the input current to the MR damper to generate a reference damping force. A parametric model of the damper is used to predict the damping force based on the piston motion and also the current input. A Simulink model of the structural system is developed to analyze the effectiveness of the semi-active controller. Finally, the numerical results are presented and discussed.

Motion Planning and Controls with Safety and Temporal Constraints

Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.

Head repositioning accuracy in patients with neck pain and asymptomatic subjects: concurrent validity, influence of motion speed, motion direction and target distance

Background: Cervicocephalic kinesthetic deficiencies have been demonstrated in patients with chronic neck pain (NP). On the other hand, authors emphasized the use of different motion speeds for assessing functional impairment of the cervical spine. Purpose: The objectives of this study were (1) to investigate the head repositioning accuracy in NP patients and control subjects and (2) to assess the influence of target distance, motion speed, motion direction and pain. Materials and methods: Seventy-one subjects (36 healthy subjects and 35 NP patients; age 30–55 years) performed the head repositioning test (HRT) at two different speeds for horizontal and vertical movements and at two different distances. For each condition, six consecutive trials were sampled. Results: The study showed the validity and reproducibility of the HRT, confirming a dysfunctional threshold of 4.5°. Normative values of head repositioning error up to 3.6° and 7.1° were identified for healthy and NP subjects, respectively. A distance of 180 cm from the target and a natural motion speed increased HRT accuracy. Repositioning after extension movement showed a significantly larger error in both groups. Intensity, duration of pain as well as pain level did not significantly alter head repositioning error. Conclusions: The assessment of proprioceptive performance in healthy and NP subjects allowed the validation of the HRT. The HRT is a simple, not expensive and fast test, easily implementable in daily practice to assess and monitor treatment and evolution of proprioceptive cervical deficits.

Advanced 4DT flight guidance and control software system

The work presented in this thesis has been part of a Cranfield University research project. This thesis aims to design a flight control law for large cargo aircraft by using predictive control, which can assure flight motion along the flight path exactly and on time. In particular this work involves the modelling of a Boeing C-17 Globemaster III 6DOF model (used as study case), by using DATCOM and Matlab Simulink software. Then a predictive control algorithm has been developed. The majority of the work is done in a Matlab/Simulink environment. Finally the predictive control algorithm has been applied on the aircraft model and its performances, in tracking given trajectory optimized through a 4DT Research Software, have been evaluated.

Improvement of The Driver Simulator Control and Comparison Between Driver-Road-Vehicle Interaction in Real and Simulated Environment

The present doctoral thesis discusses the ways to improve the performance of driving simulator, provide objective measures for the road safety evaluation methodology based on driver’s behavior and response and investigates the drivers' adaptation to the driving assistant systems. The activities are divided into two macro areas; the driving simulation studies and on-road experiments. During the driving simulation experimentation, the classical motion cueing algorithm with logarithmic scale was implemented in the 2DOF motion cueing simulator and the motion cues were found desirable by the participants. In addition, it found out that motion stimuli could change the behaviour of the drivers in terms of depth/distance perception. During the on-road experimentations, The driver gaze behaviour was investigated to find the objective measures on the visibility of the road signs and reaction time of the drivers. The sensor infusion and the vehicle monitoring instruments were found useful for an objective assessment of the pavement condition and the drivers’ performance. In the last chapter of the thesis, the safety assessment during the use of level 1 automated driving “ACC” is discussed with the simulator and on-road experiment. The drivers’ visual behaviour was investigated in both studies with innovative classification method to find the epochs of the distraction of the drivers. The behavioural adaptation to ACC showed that drivers may divert their attention away from the driving task to engage in secondary, non-driving-related tasks.