Publications

Enzymatic nanomotors harvest kinetic energy through the catalysis of chemical fuels. When a drop containing nanomotors is placed in a fuel-rich environment, they assemble into ordered groups and exhibit intriguing collective behaviour akin to the bioconvection of aerobic microorganismal suspensions. This collective behaviour presents numerous advantages compared to individual nanomotors, including expanded coverage and prolonged propulsion duration. However, the physical mechanisms underlying the collective motion have yet to be fully elucidated. Our study investigates the formation of enzymatic swarms using experimental analysis and computational modelling. We show that the directional movement of enzymatic nanomotor swarms is due to their solutal buoyancy. We investigate various factors that impact the movement of nanomotor swarms, such as particle concentration, fuel concentration, fuel viscosity, and vertical confinement. We examine the effects of these factors on swarm self-organization to gain a deeper understanding. In addition, the urease catalysis reaction produces ammonia and carbon dioxide, accelerating the directional movement of active swarms in urea compared with passive ones in the same conditions. The numerical analysis agrees with the experimental findings. Our findings are crucial for the potential biomedical applications of enzymatic nanomotor swarms, ranging from enhanced diffusion in bio-fluids and targeted delivery to cancer therapy.

JTD Keywords: Ammonia, Carbon dioxide, Catalysis, Computer simulation, Kinetics, Motion, Nanostructures, Urease, Viscosity

Over the past decades, the development of nanoparticles (NPs) to increase the efficiency of clinical treatments has been subject of intense research. Yet, most NPs have been reported to possess low efficacy as their actuation is hindered by biological barriers. For instance, synovial fluid (SF) present in the joints is mainly composed of hyaluronic acid (HA). These viscous media pose a challenge for many applications in nanomedicine, as passive NPs tend to become trapped in complex networks, which reduces their ability to reach the target location. This problem can be addressed by using active NPs (nanomotors, NMs) that are self-propelled by enzymatic reactions, although the development of enzyme-powered NMs, capable of navigating these viscous environments, remains a considerable challenge. Here, the synergistic effects of two NMs troops, namely hyaluronidase NMs (HyaNMs, Troop 1) and urease NMs (UrNMs, Troop 2) are demonstrated. Troop 1 interacts with the SF by reducing its viscosity, thus allowing Troop 2 to swim more easily through the SF. Through their collective motion, Troop 2 increases the diffusion of macromolecules. These results pave the way for more widespread use of enzyme-powered NMs, e.g., for treating joint injuries and improving therapeutic effectiveness compared with traditional methods. The conceptual idea of the novel approach using hyaluronidase NMs (HyaNMs) to interact with and reduce the viscosity of the synovial fluid (SF) and urease NMs (UrNMs) for a more efficient transport of therapeutic agents in joints.image

JTD Keywords: Biological barrier, Clinical research, Clinical treatments, Collective motion, Collective motion,nanomotors,nanorobots,swarming,viscous medi, Collective motions, Complex networks, Enzymatic reaction, Enzymes, Hyaluronic acid, Hyaluronic-acid,ph,viscoelasticity,adsorption,barriers,behavior,ureas, Macromolecules, Medical nanotechnology, Nano robots, Nanomotors, Nanorobots, Swarming, Synovial fluid, Target location, Viscous media, Viscous medium

Micro/nanomotors (MNMs) have evolved from single self-propelled entities to versatile systems capable of performing one or multiple biomedical tasks. When single MNMs self-assemble into coordinated swarms, either under external control or triggered by chemical reactions, they offer advantages that individual MNMs cannot achieve. These benefits include intelligent multitasking and adaptability to changes in the surrounding environment. Here, we provide our perspective on the evolution of MNMs, beginning with the development of enzymatic MNMs since the first theoretical model was proposed in 2005. These enzymatic MNMs hold immense promise in biomedicine due to their advantages in biocompatibility and fuel availability. Subsequently, we introduce the design and application of single motors in biomedicine, followed by the control of MNM swarms and their biomedical applications. In the end, we propose viable solutions for advancing the development of MNM swarms and anticipate valuable insights into the creation of more intelligent and controllable MNM swarms for biomedical applications.; Micro/nanomotor swarms propelled by diverse mechanisms.

JTD Keywords: Active particles, Actuation, Behaviors, Biocompatibility, Biomedical applications, Coordination reactions, Design and application, Diffusion, External control, Medical applications, Micromotors, Motion, Nanomotors, Powered nanomotors, Propulsion, Self-assemble, Surrounding environment, Theoretical modeling, Versatile system, Viable solutions

In this work, we report a direct measurement of the forces exerted by a tubulin/kinesin active nematic gel as well as its complete rheological characterization, including the quantification of its shear viscosity, lb and its activity parameter, a. For this, we develop a method that allows us to rapidly photo -polymerize compliant elastic inclusions in the continuously remodeling active system. Moreover, we quantitatively settle longstanding theoretical predictions, such as a postulated relationship encoding the intrinsic time scale of the active nematic in terms of n and a. In parallel, we infer a value for the nematic elasticity constant, K, by combining our measurements with the theorized scaling of the active length scale. On top of the microrheology capabilities, we demonstrate strategies for defect encapsulation, quantification of defect mechanics, and defect interactions, enabled by the versatility of the microfabrication strategy that allows to combine elastic motifs of different shapes and stiffnesses that are fabricated in situ.

JTD Keywords: Dynamics, Hydrogel, Micro fabricatio, Motio, Rheology, Soft active matter, Topological defects

Adherens junctions (AJs) allow cell contact to inhibit epithelial migration yet also permit epithelia to move as coherent sheets. How, then, do cells identify which contacts will inhibit locomotion? Here, we show that in human epithelial cells this arises from the orientation of cortical flows at AJs. When the leader cells from different migrating sheets make head-on contact with one another, they assemble AJs that couple together oppositely directed cortical flows. This applies a tensile signal to the actin-binding domain (ABD) of a-cate-nin, which provides a clutch to promote lateral adhesion growth and inhibit the lamellipodial activity neces-sary for migration. In contrast, AJs found between leader cells in the same migrating sheet have cortical flows aligned in the same direction, and no such mechanical inhibition takes place. Therefore, a-catenin mechano-sensitivity in the clutch between E-cadherin and cortical F-actin allows cells to interpret the direction of motion via cortical flows and signal for contact to inhibit locomotion.

JTD Keywords: Clutch, Contact inhibition of locomotion, Cortical flow, E-cadherin adhesion, Mechanical tension, Α-catenin

Human induced pluripotent stem cell (hiPSC) technologies offer a unique resource for modeling neurological diseases. However, iPSC models are fraught with technical limitations including abnormal aggregation and inefficient maturation of differentiated neurons. These problems are in part due to the absence of synergistic cues of the native extracellular matrix (ECM). We report on the use of three artificial ECMs based on peptide amphiphile (PA) supramolecular nanofibers. All nanofibers display the laminin-derived IKVAV signal on their surface but differ in the nature of their non-bioactive domains. We find that nanofibers with greater intensity of internal supramolecular motion have enhanced bioactivity toward hiPSC-derived motor and cortical neurons. Proteomic, biochemical, and functional assays reveal that highly mobile PA scaffolds caused enhanced β1-integrin pathway activation, reduced aggregation, increased arborization, and matured electrophysiological activity of neurons. Our work highlights the importance of designing biomimetic ECMs to study the development, function, and dysfunction of human neurons.Copyright © 2022 Elsevier Inc. All rights reserved.

JTD Keywords: differentiation, force-field, laminin, migration, nanostructures, peptide amphiphiles, spinal-cord, statistical-model, supramolecular materials, Coarse-grained model, Dynamics, Extracellular matrix, Ikvav, Ipsc-derived neurons, Laminin, Neuronal maturation, Peptide amphiphiles, Supramolecular motion, Supramolecular nanofibers

Various locomotion strategies employed by microorganisms are observed in complex biological environments. Spermatozoa assemble into bundles to improve their swimming efficiency compared to individual cells. However, the dynamic mechanisms for the formation of sperm bundles have not been fully characterized. In this study, we numerically and experimentally investigate the locomotion of spermatozoa during the transition from individual cells to bundles of two cells. Three consecutive dynamic behaviors are found across the course of the transition: hydrodynamic attraction/repulsion, alignment, and synchronization. The hydrodynamic attraction/repulsion depends on the relative orientation and distance between spermatozoa as well as their flagellar wave patterns and phase shift. Once the heads are attached, we find a stable equilibrium of the rotational hydrodynamics resulting in the alignment of the heads. The synchronization results from the combined influence of hydrodynamic and mechanical cell-to-cell interactions. Additionally, we find that the flagellar beat is regulated by the interactions during the bundle formation, whereby spermatozoa can synchronize their beats to enhance their swimming velocity.

JTD Keywords: behavior, cilia, collective locomotion, collective motion, competition, flagellar propulsion, hydrodynamics, motility, propulsion, sperm cooperation, tracking, Collective locomotion, Flagellar propulsion, Flagellar synchronization, Spermatozoa bundle

Individual biohybrid microrobots have the potential to perform biomedical in vivo tasks such as remote-controlled drug and cell delivery and minimally invasive surgery. This work demonstrates the formation of biohybrid sperm-templated clusters under the influence of an external magnetic field and essential functionalities for wireless actuation and drug delivery. Ferromagnetic nanoparticles are electrostatically assembled around dead sperm cells, and the resulting nanoparticle-coated cells are magnetically assembled into three-dimensional biohybrid clusters. The aim of this clustering is threefold: First, to enable rolling locomotion on a nearby solid boundary using a rotating magnetic field; second, to allow for noninvasive localization; third, to load the cells inside the cluster with drugs for targeted therapy. A magneto-hydrodynamic model captures the rotational response of the clusters in a viscous fluid, and predicts an upper bound for their step-out frequency, which is independent of their volume or aspect ratio. Below the step-out frequency, the rolling velocity of the clusters increases nonlinearly with their perimeter and actuation frequency. During rolling locomotion, the clusters are localized using ultrasound images at a relatively large distance, which makes these biohybrid clusters promising for deep-tissue applications. Finally, we show that the estimated drug load scales with the number of cells in the cluster and can be retained for more than 10 h. The aggregation of microrobots enables them to collectively roll in a predictable way in response to an external rotating magnetic field, and enhances ultrasound detectability and drug loading capacity compared to the individual microrobots. The favorable features of biohybrid microrobot clusters place emphasis on the importance of the investigation and development of collective microrobots and their potential for in vivo applications.

JTD Keywords: drug delivery, magnetic actuation, microrobot aggregation, sperm, Driven, Drug delivery, Magnetic actuation, Magnetotactic bacteria, Microrobot aggregation, Microrobots, Motion, Movement, Propulsion, Sperm, Sphere, Ultrasound, Wall

Of all the various locomotion strategies in low- (Formula presented.), traveling-wave propulsion methods with an elastic tail are preferred because they can be developed using simple designs and fabrication procedures. The only intrinsic property of the elastic tail that governs the form and rate of wave propagation along its length is the bending stiffness. Such traveling wave motion is performed by spermatozoa, which possess a tail that is characterized by intrinsic variable stiffness along its length. In this paper, the passive bending stiffness of the magnetic nanoparticle-coated flagella of bull sperm cells is measured using a contactless electromagnetic-based excitation method. Numerical elasto-hydrodynamic models are first developed to predict the magnetic excitation and relaxation of nanoparticle-coated nonuniform flagella. Then solutions are provided for various groups of nonuniform flagella with disparate nanoparticle coatings that relate their bending stiffness to their decay rate after the magnetic field is removed and the flagellum restores its original configuration. The numerical models are verified experimentally, and capture the effect of the nanoparticle coating on the bending stiffness. It is also shown that electrostatic self-assembly enables arbitrarily magnetizable cellular segments with variable stiffness along the flagellum. The bending stiffness is found to depend on the number and location of the magnetized cellular segments. © 2022 The Authors. Advanced Theory and Simulations published by Wiley-VCH GmbH.

JTD Keywords: cilia, flagella, flagellar propulsion, low reynolds numbers, magnetic, microswimmers, passive, sperm cell, Bending stiffness, Cells, Cellulars, Coatings, Decay (organic), Electric excitation, Excited states, Flagellar propulsion, Locomotion strategies, Low reynolds numbers, Magnetic, Magnetic excitations, Nanoparticle coatings, Passive, Propulsion methods, Self assembly, Simple++, Sperm cell, Sperm cells, Stiffness, Travelling waves, Variable stiffness, Wave propagation, Younǵs modulus

Introduction: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. Methods: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. Results: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of R-2: 0.38 with an error (sigma: 12.8). Next, we evaluate its reliability (r = 0.89 for test-retest), longitudinal external validity (95% true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements (R-2: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory (R-2: 0.40) and Barthel Index (R-2: 0.35). Conclusions: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

JTD Keywords: interactive feedback, motion classification, motion sensing, multivariate regression, posture monitoring, rehabilitation, stroke, Adult, Aged, Analytic method, Arm movement, Article, Barthel index, Brain hemorrhage, Cerebrovascular accident, Chedoke arm and hand activity inventory, Clinical protocol, Cognitive defect, Computer analysis, Controlled study, Convergent validity, Correlation coefficient, Disease severity, External validity, Female, Fugl meyer assessment for the upper extremity, Functional assessment, Functional status assessment, General health status assessment, Hemiparesis, Human, Interactive feedback, Ischemic stroke, Kinematics, Major clinical study, Male, Mini mental state examination, Motion classification, Motion sensing, Motor analog scale, Movement, Multivariate regression, Muscle function, Posture monitoring, Probability, Recovery, Rehabilitation, Reliability, Retrospective study, Stroke, Stroke patient, Test retest reliability, Therapy, Total goal directed movement, Upper extremities, Upper limb, Upper-limb, Wolf motor function test

Chemically active Janus particles sustain non-equilibrium spatial variations in the chemical composition of the suspending solution; these induce hydrodynamic flow and (self-)motility of the particles. Direct mapping of these fields has so far proven to be too challenging. Therefore, indirect methods are needed, e.g., deconvolving the response of “tracer” particles to the activity-induced fields. Here, we study experimentally the response of silica particles, sedimented at a wall, to active Pt/silica Janus particles. The latter are either immobilized at the wall, with the symmetry axis perpendicular or parallel to the wall, or motile. The experiments reveal complex effective interactions that are dependent on the configuration and on the state of motion of the active particle. Within the framework of a coarse-grained model, the behavior of tracers near an immobilized Janus particle can be captured qualitatively once activity-induced osmotic flows on the wall are considered.

JTD Keywords: sphere, Motion

Enzyme-powered nanomotors are an exciting technology for biomedical applications due to their ability to navigate within biological environments using endogenous fuels. However, limited studies into their collective behavior and demonstrations of tracking enzyme nanomotors in vivo have hindered progress toward their clinical translation. Here, we report the swarming behavior of urease-powered nanomotors and its tracking using positron emission tomography (PET), both in vitro and in vivo. For that, mesoporous silica nanoparticles containing urease enzymes and gold nanoparticles were used as nanomotors. To image them, nanomotors were radiolabeled with either I on gold nanoparticles or F-labeled prosthetic group to urease. In vitro experiments showed enhanced fluid mixing and collective migration of nanomotors, demonstrating higher capability to swim across complex paths inside microfabricated phantoms, compared with inactive nanomotors. In vivo intravenous administration in mice confirmed their biocompatibility at the administered dose and the suitability of PET to quantitatively track nanomotors in vivo. Furthermore, nanomotors were administered directly into the bladder of mice by intravesical injection. When injected with the fuel, urea, a homogeneous distribution was observed even after the entrance of fresh urine. By contrast, control experiments using nonmotile nanomotors (i.e., without fuel or without urease) resulted in sustained phase separation, indicating that the nanomotors’ self-propulsion promotes convection and mixing in living reservoirs. Active collective dynamics, together with the medical imaging tracking, constitute a key milestone and a step forward in the field of biomedical nanorobotics, paving the way toward their use in theranostic applications. 124 18

JTD Keywords: cell, reversal, silica nanoparticles, size, step, transport, Administration, intravesical, Animals, Equipment design, Female, Gold, Metal nanoparticles, Mice, Mice, inbred c57bl, Motion, Phantoms, imaging, Positron emission tomography computed tomography, Precision medicine, Propelled micromotors, Robotics, Translational research, biomedical, Urease, Urinary bladder

We examine a mechanism of locomotion of active particles whose surface is uniformly coated with mobile enzymes. The enzymes catalyze a reaction that drives phoretic flows but their homogeneous distribution forbids locomotion by symmetry. We find that the ability of the enzymes to migrate over the surface combined with self-phoresis can lead to a spontaneous symmetry-breaking instability whereby the homogeneous distribution of enzymes polarizes and the particle propels. The instability is driven by the advection of enzymes by the phoretic flows and occurs above a critical Péclet number. The transition to polarized motile states occurs via a supercritical or subcritical pitchfork bifurcations, the latter of which enables hysteresis and coexistence of uniform and polarized states.

JTD Keywords: Biomimetic & bio-inspired materials, Locomotion, Surface-driven phase separation

This book constitutes the proceedings of the )th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020, held in Freiburg, Germany, in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 32 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial intelligence, Soft robotics, Biomimetics, Insect navigation, Synthetic nervous system, Computer vision, Bio-inspired materials, Visual homing, Locomotion+, Image processing, Intelligent robots, Human-robot interaction, Machine learning, Snake robot, Mobile robots, Robotic systems, Drosophila, Robots, Sensors, Signal processing

Background: Many experimental studies have evaluated Linehan’s biological emotional vulnerability in Borderline Personality Disorder (BPD). However, some inconsistencies were observed in operationalizing and supporting its components. This study aims at clarifying which aspects of Linehan’s model are altered in BPD, considering a multimodal evaluation of processes concerned with emotional responsiveness (self-report, psychophysiology and eye-tracking). Methods: Forty-eight socio-emotional pictures were administered to 28 participants (14 BPD, 14 Healthy Controls, HCs), gender- and age-matched, by employing two different lengths of stimuli exposure (5 s and 15 s). Results: Our results supported the hypersensitivity hypothesis in terms of faster physiological responses and altered visual processing. Furthermore, hypersensitivity was associated with detailed socio-emotional contents. Hyperreactivity assumption was not experimentally sustained by physiological and self-report data. Ultimately, the slow return to emotional baseline was demonstrated as an impaired emotional modulation. Conclusions: Our data alternatively supported the hypersensitivity and the slow return to emotional baseline hypotheses, postulated by Linehan’s Biosocial model, rather than the hyperreactivity assumption. Results have been discussed in light of other BPD core psychopathological processes.

JTD Keywords: Borderline personality disorder, Emotional vulnerability, Linehan’s model, Hypersensitivity, Slow return to emotional baseline

Facial expressions are salient social features that crucial in communication, and humans are capable of reading the messages faces convey and the emotions they display. Robots that interact with humans will need to employ similar communication channels for successful interactions. Here, we focus on the readability of the facial expressions of a humanoid robot. We conducted an online survey where participants evaluated emotional stimuli and assessed the robot’s expressions. Results suggest that the robot’s facial expressions are correctly recognised and the appraisal of the robots expressive elements are consistent with the literature.

JTD Keywords: Emotion recognition, Facial expressions, Human-robot interaction

The motion of nanomotors triggered by light sources will provide new alternative routes to power nanoarchitectures without the need of chemical fuels. However, most light-driven nanomotors are triggered by UV-light, near infrared reflection, or laser sources. It is demonstrated that nanocap shaped Au/TiO2 nanomotors (175 nm in diameter) display increased Brownian motion in the presence of broad spectrum visible light. The motion results from the surface plasmon resonance effect leading to self-electrophoresis between the Au and TiO2 layers, a mechanism called plasmonic photocatalytic effect in the field of photocatalysis. This mechanism is experimentally characterized by electron energy loss spectroscopy, energy-filtered transmission electron microscopy, and optical video tracking. This mechanism is also studied in a more theoretical manner using numerical finite-difference time-domain simulations. The ability to power nanomaterials with visible light may result in entirely new applications for externally powered micro/nanomotors.

JTD Keywords: Enhanced Brownian motion, Fuel-free nanomotors, Nanomachines, Self-electrophoresis, Visible light

This chapter takes the view that emotions of living machines can be seen from the perspective of self-regulation and appraisal. We will first look at the pragmatic needs to endow machines with emotions and subsequently describe some of the historical background of the science of emotions and its different interpretations and links to affective neuroscience. Subsequently, we argue that emotions can be cast in terms of self-regulation where they provide for a descriptor of the state of the homeostatic processes that maintain the relationship between the agent and its internal and external environment. We augment the notion of homeostasis with that of allostasis which signifies a change from stability through a fixed equilibrium to stability through continuous change. The chapter shows how this view can be used to create complex living machines where emotions are anchored in the need fulfillment of the agent, in this case considering both utilitarian and epistemic needs.

JTD Keywords: Emotion, Motivation, Needs, Appraisal, Self-regulation, Homeostasis, Allostasis, Human–robot interaction, James–Lange theory

This chapter introduces the “Capabilities” section of the Handbook of Living Machines. Where the previous section considered building blocks, we recognize that components or modules do not automatically make systems. Hence, in the remainder of this handbook, the emphasis is toward the capabilities of living systems and their emulation in artifacts. Capabilities often arise from the integration of multiple components and thus sensitize us to the need to develop a system-level perspective on living machines. Here we summarize and consider the 14 contributions in this section which cover perception, action, cognition, communication, and emotion, and the integration of these through cognitive architectures into systems that can emulate the full gamut of integrated behaviors seen in animals including, potentially, our own capacity for consciousness.

JTD Keywords: Action, Cognition, Cognitive architecture, Communication, Consciousness, Emotion, Perception

This book constitutes the proceedings of the 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2018, held in Paris, France, in July 2018. The 40 full and 18 short papers presented in this volume were carefully reviewed and selected from 60 submissions. The theme of the conference targeted at the intersection of research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

JTD Keywords: Artificial neural network, Bio-actuators, Bio-robotics, Biohybrid systems, Biomimetics, Bipedal robots, Earthoworm-like robots, Robotics, Decision-making, Tactile sensing, Soft robots, Locomotion, Insects, Sensors, Actuators, Robots, Artificial intelligence, Neural networks, Motion planning, Learning algorithms

Cardiac motion estimation is an important diagnostic tool for detecting heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate cardiac motion using ultrafast ultrasound data. Our solution is based on a variational formulation characterized by the L 2-regularized class. Displacement is represented by a lattice of b-splines and we ensure robustness, in the sense of eliminating outliers, by applying a maximum likelihood type estimator. While this is an important part of our solution, the main object of this work is to combine low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows one to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. The low-rank constraint speeds up the convergence of the optimization problem while topology preservation ensures a more accurate displacement. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that exhibit motion.

JTD Keywords: Cardiac analysis, Low-rank representation, Motion estimation, Topology preservation, Ultrafast ultrasound

Purpose: To assess, with finite element (FE) calculations, whether immediate weight bearing would be possible after surgical stabilization either with cannulated screws or with a locking plate in a split fracture of the lateral tibial plateau (LTP). Methods: A split fracture of the LTP was recreated in a FE model of a human tibia. A three-dimensional FE model geometry of a human femur-tibia system was obtained from the VAKHUM project database, and was built from CT images from a subject with normal bone morphologies and normal alignment. The mesh of the tibia was reconverted into a geometry of NURBS surfaces. A split fracture of the lateral tibial plateau was reproduced by using geometrical data from patient radiographs. A locking screw plate (LP) and a cannulated screw (CS) systems were modelled to virtually reduce the fracture and 80 kg static body-weight was simulated. Results: While the simulated body-weight led to clinically acceptable interfragmentary motion, possible traumatic bone shear stresses were predicted nearby the cannulated screws. With a maximum estimation of about 1.7 MPa maximum bone shear stresses, the Polyax system might ensure more reasonable safety margins. Conclusions: Split fractures of the LTP fixed either with locking screw plate or cannulated screws showed no clinically relevant IFM in a FE model. The locking screw plate showed higher mechanical stability than cannulated screw fixation. The locking screw plate might also allow full or at least partial weight bearing under static posture at time zero.

JTD Keywords: Bone fixation, Finite element, Fracture fixation, Interfragmentary motion, Tibial plateau fractures, Weight bearing

An automatic gait initialization strategy based on user intention sensing in the context of rehabilitation with a lower-limb wearable robot is proposed and evaluated. The proposed strategy involves monitoring the human-orthosis interaction torques and initial position deviation to determine the gait initiation instant and to modify orthosis operation for gait assistance, when needed. During gait, the compliant control algorithm relies on the adaptation of the joints' stiffness in function of their interaction torques and their deviation from the desired trajectories, while maintaining the dynamic stability. As a reference input, the average of a set of recorded gaits obtained from healthy subjects is used. The algorithm has been tested with five healthy subjects showing its efficient behavior in initiating the gait and maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from incomplete Spinal cord injury and Stroke.

JTD Keywords: Biomedical monitoring, Exoskeletons, Joints, Knee, Legged locomotion, Trajectory, Exoskeleton, adaptive control, gait assistance, gait initiation, rehabilitation, wearable robot

The lack of physiological motion compensation is a major problem in robotic-assisted cardiac surgery. Since the heart is beating while the surgeon carried out the procedure, dexterity of the surgeon’s and precision are compromised. Due to the operative space and the visibility of the surgical field are reduced, the most practical solution is the use of computer vision techniques. The lack of efficiency and robustness of the existing proposals make physiological motion compensation to be considered an open problem. In this work a novel solution to solve this problem based on the minimization of an energy functional is presented. It is described in the three-dimensional space using the l1−regularized optimization class in which cubic b-splines are used to represent the changes produced on the heart surface. Moreover, the logarithmic barrier function is applied to create an approximation of the total energy in order to avoid its non-differentiability. According to the results, this proposal is able to deal with complex deformations, requires a short computational time and gives a small error.

JTD Keywords: Beating heart surgery, Image analysis, Motion compensation

Xenopus tadpoles are an emerging model for developmental, genetic and behavioral studies. A small size, optical accessibility of most of their organs, together with a close genetic and structural relationship to humans make them a convenient experimental model. However, there is only a limited toolset available to measure behavior and organ function of these animals at medium or high-throughput. Herein, we describe an imaging-based platform to quantify body and autonomic movements of Xenopus tropicalis tadpoles of advanced developmental stages. Animals alternate periods of quiescence and locomotor movements and display buccal pumping for oxygen uptake from water and rhythmic cardiac movements. We imaged up to 24 animals in parallel and automatically tracked and quantified their movements by using image analysis software. Animal trajectories, moved distances, activity time, buccal pumping rates and heart beat rates were calculated and used to characterize the effects of test compounds. We evaluated the effects of propranolol and atropine, observing a dose-dependent bradycardia and tachycardia, respectively. This imaging and analysis platform is a simple, cost-effective high-throughput in vivo assay system for genetic, toxicological or pharmacological characterizations.

JTD Keywords: Xenopus tropicalis, Animal behavior, Cardiac imaging, Motion analysis, Animal tracking, Hhigh-throughput in vivo assay

Compensating physiological motion in the context of minimally invasive cardiac surgery has become an attractive issue since it outperforms traditional cardiac procedures offering remarkable benefits. Owing to space restrictions, computer vision techniques have proven to be the most practical and suitable solution. However, the lack of robustness and efficiency of existing methods make physiological motion compensation an open and challenging problem. This work focusses on increasing robustness and efficiency via exploration of the classes of l1- and l2-regularized optimization, emphasizing the use of explicit regularization. Both approaches are based on natural features of the heart using intensity information. Results pointed out the l1-regularized optimization class as the best since it offered the shortest computational cost, the smallest average error and it proved to work even under complex deformations.

JTD Keywords: Motion Compensation, Optimization, Regularization, Beating Heart Surgery, Ill-posed problem