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Despite the significant progress made in making robots more intelligent and autonomous, today, teleoperation remains a dominant robot control paradigm for the execution of complex and highly unpredictable tasks. Attempts have been made to make teleoperation systems stable, easy to use, and efficient in terms of physical interactions between the follower remote robot and the environment. In particular, the emergence of torque-controlled robots has permitted to regulate the interaction forces from a distance through direct force or impedance control, enabling them to engage in complex interaction tasks. Exploiting this feature, the concept of teleimpedance control was introduced as an alternative method to bilateral force-reflecting teleoperation. The aim was to create a feed-froward yet contact-efficient teleoperation by enriching the leader commands with desired impedance profiles while executing a task. Since then, the teleimpedance concept has found its way into a wide range of interface and controller designs, as well as application domains. Accordingly, after a decade of research progress, this survey aims to provide: first, a convenient introduction of the concept to new researchers in the field, second, consolidate the existing state-of-the-art for active researchers, third, and discuss the pros and cons of different methods in terms of interface and force feedback to provide guidelines for different applications and future developments.

Tele-impedance augments classic teleoperation by enabling the human operator to actively command remote robot stiffness in real-time, which is an essential ability to successfully interact with the unstructured and unpredictable environment. However, the literature is missing a study on benefits and drawbacks of different types of stiffness command interfaces used in bilateral tele-impedance. In this article, we introduce a term called coupling effect, which pertains to the coupling between human-commanded stiffness going to the remote robot and force feedback coming from the remote robot. We hypothesize that, whenever the operator's commanded stiffness and force feedback are subject to coupling effect (e.g., muscle activity based stiffness command interfaces), force feedback can invoke involuntary changes in the commanded stiffness due to human reflexes. Although the coupling effect takes away some degree of the operator's control over the commanded stiffness, these involuntary changes can be either beneficial (e.g., during position tracking) or detrimental (e.g., during force tracking) to the task performance on the remote robot side. We examined the coupling effect in an experimental study with $\mathbf {16}$ participants, who performed position and force tracking tasks by using both coupled type (muscle activity based) and decoupled type (external device based) of interface. The results demonstrate a benefit of the coupling effect when the remote robot is operating in presence of unexpected force perturbations, where lower absolute error in position tracking task was observed. On the other hand, the decoupled type of interface is beneficial for force tracking tasks on the remote robot side, such as establishing or maintaining a stable contact with objects. However, the coupling effect negatively influences the commanding of reference stiffness to the remote robot in both position and force tracking tasks for the coupled type of interface, compared to the decoupled type of interface, which is not affected.

Humans often demonstrate diverse behaviors due to their personal preferences, for instance, related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating both path and velocity preferences into trajectory planning for robotic manipulators. We first learn reward functions that represent the user path and velocity preferences from kinesthetic demonstration. We then optimize the trajectory in two steps: first the path and then the velocity, to produce trajectories that adhere to both task requirements and user preferences. We design a set of parameterized features that capture the fundamental preferences in a pick-and-place type of object-transportation task, both in shape and timing of the motion. We demonstrate that our method is capable of generalizing such preferences to new scenarios. We implement our algorithm on a Franka Emika 7-DoF robot arm, and validate the functionality and flexibility of our approach in a user study. The results show that non-expert users are able to teach the robot their preferences with just a few iterations of feedback., 14 pages, 12 figures, 2 tables, associated video: https://youtu.be/hhL5-Lpzj4M

Robotic tasks which involve uncertainty--due to variation in goal, environment configuration, or confidence in task model--may require human input to instruct or adapt the robot. In tasks with physical contact, several existing methods for adapting robot trajectory or impedance according to individual uncertainties have been proposed, e.g., realizing intention detection or uncertainty-aware learning from demonstration. However, isolated methods cannot address the wide range of uncertainties jointly present in many tasks. To improve generality, this paper proposes a model predictive control (MPC) framework which plans both trajectory and impedance online, can consider discrete and continuous uncertainties, includes safety constraints, and can be efficiently applied to a new task. This framework can consider uncertainty from: contact constraint variation, uncertainty in human goals, or task disturbances. An uncertainty-aware task model is learned from a few ($\leq3$) demonstrations using Gaussian Processes. This task model is used in a nonlinear MPC problem to optimize robot trajectory and impedance according to belief in discrete human goals, human kinematics, safety constraints, contact stability, and frequency-domain disturbance rejection. This MPC formulation is introduced, analyzed with respect to convexity, and validated in co-manipulation with multiple goals, a collaborative polishing task, and a collaborative assembly task., Comment: Video: https://youtu.be/Of2O3mHfM94 Code: https://gitlab.cc-asp.fraunhofer.de/hanikevi/gp-mpc-impedance-control

Imitation learning techniques have been used as a way to transfer skills to robots. Among them, dynamic movement primitives (DMPs) have been widely exploited as an effective and an efficient technique to learn and reproduce complex discrete and periodic skills. While DMPs have been properly formulated for learning point-to-point movements for both translation and orientation, periodic ones are missing a formulation to learn the orientation. To address this gap, we propose a novel DMP formulation that enables encoding of periodic orientation trajectories. Within this formulation we develop two approaches: Riemannian metric-based projection approach and unit quaternion based periodic DMP. Both formulations exploit unit quaternions to represent the orientation. However, the first exploits the properties of Riemannian manifolds to work in the tangent space of the unit sphere. The second encodes directly the unit quaternion trajectory while guaranteeing the unitary norm of the generated quaternions. We validated the technical aspects of the proposed methods in simulation. Then we performed experiments on a real robot to execute daily tasks that involve periodic orientation changes (i.e., surface polishing/wiping and liquid mixing by shaking)., Comment: 2021 20th International Conference on Advanced Robotics (ICAR)

The existing state-of-the-art interfaces for commanding a remote robot's endpoint stiffness ellipsoid in tele-impedance lack the ability to independently control its size, shape and orientation or they are not easily to implement due to the use of physiological signals, such as electromyography, to control the endpoint stiffness. We propose a novel method that can command size, shape and orientation independently and simultaneously through a virtual stiffness ellipsoid generated on a touchscreen device. The human operator controls size, shape and orientation of the virtual ellipsoid using his/her index and thumb fingers of one hand. This virtual ellipsoid is then mapped to the Cartesian stiffness ellipsoid of a remote robot endpoint in real-time. The other hand holds the haptic device to control the pose of the remote robotic arm. Compared to the state-of-the-art methods to control the robot stiffness in tele-impedance, the main advantages of the proposed method are its relatively simple implementation and ability of independent control over various aspects of the robot endpoint stiffness ellipsoid. To provide a proof-of-concept and demonstrate the main features of the proposed approach, we performed several experiments on a tele-impedance setup with a Kuka LBR iiwa robotic arm and a Force Dimension Sigma7 haptic device. We examined two principal types of tasks, in which changing stiffness parameters of the remote robot is important for successful task execution: counteracting external perturbations and establishing contact with unknown objects. The results indicate that our proposed approach can successfully deal with these tasks. A human subject study showed that the touchscreen interface is faster in commanding the desired stiffness compared to another state-of-the-art input method, while showing similar workload ratings.

In this paper, we propose a method for selective monitoring and management of human muscle fatigue in human-robot co-manipulation scenarios. The proposed approach uses a machine learning technique to learn the complex relationship between individual human muscle forces, arm configuration and arm endpoint force that are provided by a sophisticated offline musculoskeletal model. The estimated muscle forces are used in the fatigue model to estimate the individual muscle fatigue levels online. Two fatigue management protocols are proposed that enable the robot to handle and reduce the human fatigue by altering the configuration of task execution. The first protocol uses optimisation technique to find the optimal position for task execution, where the fatigue-related endurance time can be maximised. The second protocol divides the arm muscles into groups and then alters the direction of endpoint force so that the fatigued muscle group can relax and the relaxed muscle group becomes active. The proposed method has a potential to enable the robot to facilitate safer and more ergonomic working conditions for the human coworker. The main advantage of this approach is that it can operate online, and that all the measurements can be performed by the robot sensory system, which can significantly increase the applicability in real world scenarios. To validate the proposed method, we performed multiple experiments with two collaborative tasks (polishing and drilling) under different conditions.

The science and technology of wearable robots are steadily advancing, and the use of such robots in our everyday life appears to be within reach. Nevertheless, widespread adoption of wearable robots should not be taken for granted, especially since many recent attempts to bring them to real-life applications resulted in mixed outcomes. The aim of this article is to address the current challenges that are limiting the application and wider adoption of wearable robots that are typically worn over the human body. We categorized the challenges into mechanical layout, actuation, sensing, body interface, control, human–robot interfacing and coadaptation, and benchmarking. For each category, we discuss specific challenges and the rationale for why solving them is important, followed by an overview of relevant recent works. We conclude with an opinion that summarizes possible solutions that could contribute to the wider adoption of wearable robots.

This letter proposes a novel human–robot collaboration (HRC) control approach to alert and reduce the static joint torque overloading of a human partner while executing shared tasks with a robot. Using a preidentified statically equivalent serial chain model, variations of the centre-of-pressure and ground reaction force are calculated, and the overloading joint torques are evaluated in real time to initially alert the human about consequent injuries. An online optimization technique is implemented to adjust the robot trajectories facilitating the human to achieve more ergonomic body poses throughout the HRC task. The optimized human configurations are calculated by taking into account the human stability, the robot, and the human workspaces, and the task constraints, and illustrated to the human in real time. The experimental evaluation of the proposed technique is achieved in a human–robot load sharing task as a representative example of coassembly or transportation scenarios in industrial settings.

In this paper, we propose a novel method for human---robot collaboration, where the robot physical behaviour is adapted online to the human motor fatigue. The robot starts as a follower and imitates the human. As the collaborative task is performed under the human lead, the robot gradually learns the parameters and trajectories related to the task execution. In the meantime, the robot monitors the human fatigue during the task production. When a predefined level of fatigue is indicated, the robot uses the learnt skill to take over physically demanding aspects of the task and lets the human recover some of the strength. The human remains present to perform aspects of collaborative task that the robot cannot fully take over and maintains the overall supervision. The robot adaptation system is based on the Dynamical Movement Primitives, Locally Weighted Regression and Adaptive Frequency Oscillators. The estimation of the human motor fatigue is carried out using a proposed online model, which is based on the human muscle activity measured by the electromyography. We demonstrate the proposed approach with experiments on real-world co-manipulation tasks: material sawing and surface polishing.

We propose a novel human-in-the-loop approach for teaching robots how to solve assembly tasks in unpredictable and unstructured environments. In the proposed method the human sensorimotor system is integrated into the robot control loop though a teleoperation setup. The approach combines a 3-DoF end-effector force feedback with an interface for modulation of the robot end-effector stiffness. When operating in unpredictable and unstructured environments, modulation of limb impedance is essential in terms of successful task execution, stability and safety. We developed a novel hand-held stiffness control interface that is controlled by the motion of the human finger. A teaching approach was then used to achieve autonomous robot operation. In the experiments, we analysed and solved two part-assembly tasks: sliding a bolt fitting inside a groove and driving a self-tapping screw into a material of unknown properties. We experimentally compared the proposed method to complementary robot learning methods and analysed the potential benefits of direct stiffness modulation in the force-feedback teleoperation.

In this letter, we propose a novel method that enables the robot to autonomously devise an appropriate control strategy from human demonstrations without a prior knowledge of the demonstrated task. The method is primarily based on observing the patterns and consistency in the observed dataset. This is obtained through a demonstration setting that uses a motion capture system, a force sensor, and muscle activity measurements. The variables (position and force) in the collected dataset are then segmented and analysed for each axis of the observed task frame separately. While checking several conditions based on the consistency, value range, and magnitude of repeated observations, the appropriate controller (i.e., position or force) is delegated to each axis of the task frame. In the final stage, the method also checks for a correlation between variables and muscle activity patterns to determine the desired stiffness behaviour. The robot then uses the derived control strategies in autonomous operation through a hybrid force/impedance controller. To validate the proposed method, we performed experiments on real-life tasks involving physical interaction with the environment, where we considered surface wiping, material sawing, and drilling.

Goal-directed human reaching often involves multi-component strategy with sub-movements. In general, the initial sub-movement is fast and less precise to bring the limb’s endpoint in the vicinity of the target as soon as possible. The final sub-movement then corrects the error accumulated during the previous sub-movement in order to reach the target. We investigate properties of a temporary target of the initial sub-movement. We hypothesise that the peak spatial dispersion of movement trajectories in the axis perpendicular to the movement is in front of the final reaching target, and that it indicates the temporary target of the initial sub-movement. The reasoning is that the dispersion accumulates, due to signal-dependent noise during the initial sub-movement, until the final corrective sub-movement is initiated, which then reduces the dispersion to successfully reach the actual target. We also hypothesise that the reaching movement distance and size of the actual target affect the properties of the temporary target of the initial sub-movement. The increased reaching movement distance increases the magnitude of peak dispersion and moves its location away from the actual target. On the other hand, the increased target size increases the magnitude of peak dispersion and moves its location closer to the actual target.

In this work, we present a novel control approach to human-robot collaboration that takes into account ergonomic aspects of the human co-worker during power tool operations. The method is primarily based on estimating and reducing the overloading torques in the human joints that are induced by the manipulated external load. The human overloading joint torques are estimated and monitored using a whole-body dynamic state model. The appropriate robot motion that brings the human into the suitable ergonomic working configuration is obtained by an optimisation method that minimises the overloading joint torques. The proposed optimisation process includes several constraints, such as the human arm muscular manipulability and safety of the collaborative task, to achieve a task-relevant optimised configuration. We validated the proposed method by a user study that involved a human-robot collaboration task, where the subjects operated a polishing machine on a part that was brought to them by the collaborative robot. A statistical analysis of ten subjects as an experimental evaluation of the proposed control framework is provided to demonstrate the potential of the proposed control framework in enabling ergonomic and task-optimised human-robot collaboration.

Multivariate data analysis (MVDA) and artificial neural networks (ANN) are supporting statistical methodologies required for successful development and manufacturing of drug products. To address this purpose, a complex dataset from 49 industrially produced capsules filled with pellets was first analyzed through the development of a multiple linear regression model focused on determining raw material attributes or process parameters with a significant impact on drug dissolution. Based on the model, the following molecular and micrometrics properties of κ-carrageenan have been identified as critical material attributes with the highest contribution to drug dissolution: molecular weight and polydispersity index, viscosity, content of potassium ions, wettability, particle size, and density. The process parameters identified to control the drug dissolution behavior of pellets were amount of granulation liquid, torque of dry blend, spheronization parameters, and yields after screening. To further scrutinize the dataset, an ANN model was subsequently built, incorporating 29 batches addressing drug particle size and process parameters such as torque during granulation and spheronization time as critical factors. Finally, this study demonstrates the ability of MVDA and ANN to allow prediction of the key performance drivers influencing the drug dissolution of industrially developed capsules filled with pellets and it highlights their complementary relationship.

Stairways, public transport and inclined walkways are often considered as sites with higher likelihood of falls due to a sudden loss of balance. Such sites are usually marked with warning signs, equipped with non-slip surfaces and handles or handrails to avert or decrease this likelihood. Especially, handles are supposed to provide additional support in cases of a sudden loss of balance. However, the mechanisms of using handles for balance at different heights are not yet fully disclosed. We simulated full body perturbations by applying an anterior force to the waist and investigated effectiveness and mechanisms of balance recovery in five different postures: step stance and normal stance with or without holding handles at different heights. Results indicate that both step stance and holding handles at different vertical positions sufficiently assist balance recovery, compared to normal stance. While there was no significant effect of handle in CoM displacement, the shoulder height handle required the lowest handle force, indicating a difference in using the handle.

Industry 4.0 envisions the integration of flexible and quickly reconfigurable robotic systems in assembly lines. This has led to the development of light-weight and adaptive collaborative robots with limited power and payload constraints. Hence, repetitive tasks or those that demand high forces may exceed such limits, resulting in robot damage and lost productivity. To address this problem, we propose a novel framework to prolong the lifetime of collaborative robots while guaranteeing the desired level of productivity. To address this, we propose a method that minimises a function of robot fatigue, an index able to model the robot motor usage at the joint level. This index features the desired external force, task duration, hardware parameters, and fatigue history. Moreover, future tasks are considered through fatigue thresholds imposed on specific joints, computed according to the robot safety requirements. We proved the effectiveness of the approach by comparing its results in terms of fatigue and torque with the well-known minimum effort approach. The results showed that our method ensures that the fatigue thresholds are not exceeded.

Collaborative robots are often designed with limited power and force capacity, with the aim to provide affordable solutions and ensure human safety in case of accidental collisions and impacts. If a task requires a power beyond this capacity, or is performed repeatedly over long periods, such limits may be exceeded, which can cause inevitable robot damage and contribute to the lost productivity. In such cases, where hardware solutions and improvements are not applicable, effective software frameworks can prolong robot productivity and lifetime. To this end, in this paper we propose a novel technique for the monitoring and management of robot fatigue in repetitive or high-effort task execution scenarios. The robot fatigue is estimated by the measured temperature of motors in the joints. The proposed fatigue management system is composed of two-stage reaction process that is triggered by different levels of the estimated fatigue. The first stage exploits the kinematic redundancy of robot structure in attempt to minimise the load in the specific joints that under fatigue by reconfiguration in the joint space through the null space of the Cartesian task production. If the first stage is not successful in reducing the fatigue, the second stage is activated that gradually reduces the forces of hybrid controller. At that point, the human co-worker can temporarily take over the task execution until the robot will be recovered from the excessive fatigue. To validate the proposed approach we conducted experiments on KUKA Lightweight Robot performing two interaction tasks: autonomous surface wiping and collaborative human-robot surface polishing.

In this paper, we propose a novel method for selective management of muscle fatigue in human-robot co-manipulation. The proposed framework enables the detection of excessive fatigue levels of an individual muscle group while executing a certain task, and provides anticipatory robotic responses to distribute the effort among less-fatigued muscles of human arm. Our approach uses a machine learning technique to enable online predictions of muscle forces in different arm configurations and endpoint interaction forces. The estimated muscle forces are then used for the model-based estimation of muscle fatigue levels. Through optimisation, the fatigue management system can alter the task execution in a way that specific fatigued muscles are offloaded, while at the same time enables the production of task force using muscles with lower levels of fatigue. The main advantage of the proposed method is that it can operate online, and that all the measurements are performed by the robot sensory system, which can significantly increase the applicability in real-world scenarios. To validate the proposed method, we performed proof-of-concept experiments where the task of the human operator was to use a tool to polish an object that was manipulated by the robot.

The aim of the present study was to demonstrate the application of an automated high-throughput (HT) dissolution method as a useful screening tool for characterization of controlled release pellets in the formulation development phase. Five controlled release pellet formulations with drug substances exhibiting high or low solubility were chosen to investigate the correlation of the automated HT dissolution method with the conventional dissolution testing. Overall, excellent correlations (R(2 )>( )0.96) between the HT and the conventional dissolution method were obtained. In one case the initial unsatisfactory correlation (R(2 )=( )0.84) and poor method agreement (SD = 12.5) was improved by optimizing the HT dissolution method with design of experiment approach. Here in comparison to initial experimental HT dissolution settings, increased amount of pellets (25% of the capsule filling mass), lower temperature (22 °C) and no shaking resulted in significantly better correlation (R(2 )=( )0.97) and method agreement (SD = 5.3). These results show that such optimization is valuable for the development of HT dissolution methods. In conclusion, the high correlation of dissolution profiles obtained from the conventional and the automated HT dissolution method combined with low within-sample and measurement system variability, justifies the utilization of the automated HT dissolution method during development phase of controlled release pellets.

In this study we have investigated the effects of different cell culture conditions on the Calu-3 epithelial cell model. Calu-3 cells were cultured in media A-MEM at the air–liquid (A–L) or liquid–liquid (L–L) interface for one or three wks (weeks). Different cryomethods were tested and the cell line was characterized using histochemistry, immunofluorescence, transmission and scanning electron microscopy, transepithelial resistance (TEER) measurements, permeability studies, and gene profiling of 84 drug transporters. Cell culture was successful in A-MEM with only 2.5% FBS. Cell proliferation and viability depended on the cryopreservation method. All Calu-3 models expressed CK7, occludin, and E-cadherin. The A–L interface resulted in a more biomimetic native bronchial epithelium displaying pseudostratified columnar epithelium with more microvilli and secretory vesicles than at the L–L interface, where the epithelium was cuboidal, but exhibited higher TEER values and lower dextran permeabilities. Longer time in culture significantly decreased dextran permeability and increased the expression of specific drug transporters. Drug transporter expression was also notably influenced by the culture interface, where the A–L interface yielded a higher expression of drug transporter genes than the L–L interface. Since cell culture interface and time in culture affect Calu-3 cell differentiation, barrier integrity, permeability properties, and drug transporter expression, culture conditions need to be considered and standardized when using the Calu-3 cell line as an in vitro model for aerosol drug delivery and screening of bronchial drug candidates.

In this paper, we propose a novel method for the control of human-robot eo-manipulation that takes into aeeount the ergonomie requirements for the human eo-worker. The robot uses a whole-body dynamic model of the human to optimise for the position of the eo-manipulation task in the workspace. In this configuration, the overloading joint torques, i.e. the effects of an external load in human body joints, are minimised. In addition, the optimisation process ineludes several constraints, sueh as human arm manipulability properties, to ensure that the human has a good manipulation eapaeity in the given eonfiguration. The main advantage of this approaeh is that the robot ean potentially help to reduee the work-related strain and increase the productivity of the human eo-worker. In addition, the on-line estimation of the overloading joint torques does not require an external foree plate or sensor insoles. We validated the proposed method with experiments in two eo-manipulation tasks: human using a device to polish an object that is delivered by the robot and a human-robot object handover. The results show that the proposed method is successful in achieving the ergonomie conditions for the human during the eollaboration.

In this paper we study the concept of robots learning from collaboration with skilled robots. The advantage of this concept is that the human involvement is reduced, while the skill can be propagated faster among the robots performing similar collaborative tasks or the ones being executed in hostile environments. The expert robot initially obtains the skill through the observation of, and physical collaboration with the human. We present a novel approach to how a novice robot can learn the specifics of the co-manipulation task from the physical interaction with an expert robot. The method consists of a multi-stage learning process that can gradually learn the appropriate motion and impedance behaviour under given task conditions. The trajectories are encoded with Dynamical Movement Primitives and learnt by Locally Weighted Regression, while their phase is estimated by adaptive oscillators. The learnt trajectories are replicated by a hybrid force/impedance controller. To validate the proposed approach we performed experiments on two robots learning and executing a challenging co-manipulation task.

The paper presents a novel control method for the arm exoskeletons that takes into account the muscular force manipulability of the human arm. In contrast to classical controllers that provide assistance without considering the biomechanical properties of the human arm, we propose a control method that takes into account the configuration of the arm and the direction of the motion to effectively compensate the anisotropic property of the muscular manipulability of the human arm. Consequently, the proposed control method effectively maintains a spherical endpoint manipulability in the entire workspace of the arm. As a result, the proposed method allows the human using the exoskeleton to efficiently perform tasks in arm configurations that are normally unsuitable due to the low manipulability. We evaluated the proposed approach by a preliminary experimental study where a subject wearing a 2 DOF arm-exoskeleton had to move a 4 kg weight between several locations. The results of our study demonstrate that the proposed approach effectively augments the ability of human motor control to perform tasks equally well in the whole arm workspace that include configurations with low intrinsic manipulability.

The further characterization of the cell line RPMI 2650 and the evaluation of different culture conditions for an in vitro model for nasal mucosa. Cells were cultured in media MEM or A-MEM at air-liquid (A-L) or liquid-liquid (L-L) interfaces for 1 or 3 weeks. Different cryopreservation methods and cell culture techniques were evaluated with immunolabelling of junctional proteins, ultrastructural analysis using electron microscopy, transepithelial electrical resistance (TEER) measurements, permeation studies with dextran and jacalin, and gene expression profiling of 84 drug transporters. Cell proliferation and differentiation depended on the used medium. The established epithelia expressed occludin, claudin-1, and E-cadherin under all conditions. Cells grown at the A-L interface formed more layers and exhibited a higher TEER and lower dextran and jacalin permeability than at the L-L interface, where cells morphologically exhibited a more differentiated phenotype. The expression of ABC and SLC transporters depended on culture duration and interface. The RPMI 2650 cells form a polarized epithelium resembling nasal mucosa. However, different culture conditions have a significant effect on cell ultrastructure, barrier integrity, and gene expression, and should be considered when using this cell line as an in vitro model for drug permeability studies and screening of nasal drug candidates.

There are many everyday situations in which a supportive hand contact is required for an individual to counteract various postural perturbations. By emulating situations when balance of an individual is challenged, we examined functional role of supportive hand contact at different locations where balance of an individual was perturbed by translational perturbations of the support surface. We examined the effects of handle location, perturbation direction and perturbation intensity on the postural control and the forces generated in the handle. There were significantly larger centre-of-pressure (CoP) displacements for perturbations in posterior direction than for perturbations in anterior direction. Besides, the perturbation intensity significantly affected the peak CoP displacement in both perturbation directions. However, the position of the handle had no effects on the peak CoP displacement. On the contrary, there were significant effects of perturbation direction, perturbation intensity and handle position on the maximal force in the handle. The effect of the handle position was significant for the perturbations in posterior direction where the lowest maximal forces were recorded in the handle located at the shoulder height. They were comparable to the forces in the handle at eye height and significantly lower than the forces in the handle located either lower or further away from the shoulder. In summary, our results indicate that although the location of a supportive hand contact has no effect on the peak CoP displacement of healthy individuals, it affects the forces that an individual needs to exert on the handle in order to counteract support perturbations.

We present a novel approach where a human demonstrator can intuitively teach robot full-body skills. The aim of this approach is to exploit human sensorimotor ability to learn how to operate a huma...

The aim of this study was to develop a sirolimus (BCS class II drug substance) solid oral dosage form containing a precipitation inhibitor, which would result in an improved sirolimus absorption in humans compared to the formulation containing nanosized sirolimus without a precipitation inhibitor, i.e., Rapamune. The selection of the precipitation inhibitor was based on the results of a screening campaign that identified two "hit" excipients: HPMC 603 (i.e., Pharmacoat 603) and Poloxamer 407. However, in a confirmatory precipitation inhibitor study using biorelevant media (Fa/FeSSIF) HPMC 603 more effectively inhibited sirolimus precipitation than Poloxamer 407. In the PAMPA assay, HPMC 603, but not Poloxamer 407, significantly increased the flux of the sirolimus across the membrane lipid layer. Additionally, a differential scanning calorimetry (DSC) and an infrared (IR) spectroscopy study revealed that interactions between the sirolimus and HPMC 603 were developed that could lead to the observed precipitation inhibition effect. Based on the above data, two formulations with HPMC 603-coated sirolimus particles were developed, namely, formulation A (d (0.5) = 0.21 μm) and formulation B (d (0.5) = 1.7 μm). A human pharmacokinetic study outlined that significantly higher AUC and Cmax were obtained for formulations A and B in comparison to Rapamune. This result could be attributed to the HPMC 603 (Pharmacoat 603) mediated sirolimus precipitation inhibition resulting in improved sirolimus absorption from the gastrointestinal tract in humans.

We propose a novel method that arbitrates the control between the human and the robot actors in a teaching-by-demonstration setting to form synergy between the two and facilitate effective skill synthesis on the robot. We employed the human-in-the-loop teaching paradigm to teleoperate and demonstrate a complex task execution to the robot in real-time. As the human guides the robot to perform the task, the robot obtains the skill online during the demonstration. To encode the robotic skill we employed Locally Weighted Regression that fits local models to specific state region of the task based on the human demonstration. If the robot is in the state region where no local models exist, the control over the robotic mechanism is given to the human to perform the teaching. When local models are gradually obtained in that region, the control is given to the robot so that the human can examine its performance already during the demonstration stage, and take actions accordingly. This enables a co-adaptation between the agents and contributes to a faster and more efficient teaching. As a proof-of-concept, we realised the proposed robot teaching system on a haptic robot with the task of generation of a desired vertical force on a horizontal plane with unknown stiffness properties. European Commission

The toxicity of amiodarone Lek formulation (test formulation) was investigated after a single intravenous (i.v.) administration to mice and rats. When compared to the reference item, Cordarone (Cordarone(®); Wyeth Pharmaceuticals Inc., Collegeville, Pennsylvania, USA), median lethal dose (LD(50)) after i.v. administration in female mice was 294.0 mg/kg body weight (b.w.) for the test formulation and 227.5 mg/kg b.w. for Cordarone. In female rats after i.v. administration, the LD(50) value was 269.9 mg/kg b.w. for the test formulation and 192.4 mg/kg b.w. for Cordarone. By altering the particle size of amiodarone in the Lek formulation, we were able to improve the solubility of amiodarone, thereby decreasing the number and quantity of excipients needed for preparation of the i.v. formulation and, consequently, reduced the acute toxic effects observed in the present study.

Cytotoxicity screening of new chemical entities in antibacterial drug discovery discerns between cytotoxic and antimicrobial activity, thus providing predictive evidence for selective toxicity. The objective of this study was to evaluate 3 cytotoxicity assays in identifying novel antibacterial hits with desired safety margins. The endpoints in assays comprised adenylate kinase (AK) release rate as an indicator of membrane rupture (Toxilight), intracellular adenosine triphosphate (CellTiter-Glo), and reduction of resazurin (CellTiter-Blue) both as indicators of cell metabolic activity. In the CellTiter-Glo and the CellTiter-Blue assays, 7 of 8 selected compounds showed cytotoxicity, whereas in the Toxilight assay, 3 of 8 compounds significantly reduced cell viability in the ChoK1 and the JurkatE6.1 cell line. The CellTiter-Glo assay proved to be the most sensitive among the evaluated assays, and excellent Z' values were obtained in the 96-well plate (Z' > 0.83). The CellTiter-Glo assay was clearly superior to the CellTiter-Blue and the Toxilight assay for the initial cytotoxicity screening. Moreover, the application of the CellTiter-Glo assay to determine mammalian cell toxicity versus the antibacterial effect ratio contributed to early identification of antibacterial hits with desired safety margins. The chemical structures of these novel antibacterial hits are disclosed herein.

This paper presents a novel approach for human-robot cooperation in tasks with dynamic uncertainties. The essential element of the proposed method is a multi-modal interface that provides the robot with the feedback about the human motor behaviour in real-time. The human muscle activity measurements and the arm force manipulability properties encode the information about the motion and impedance, and the intended configuration of the task frame, respectively. Through this human-in-the-loop framework, the developed hybrid controller of the robot can adapt its actions to provide the desired motion and impedance regulation in different phases of the cooperative task. We experimentally evaluate the proposed approach in a two-person sawing task that requires an appropriate complementary behaviour from the two agents.

The drawbacks and limitations of existing anticoagulant therapy which may result in serious adverse effects and a high mortality rate, have given rise to many anticoagulant development programmes in the last decade, focusing mainly at development of thrombin and FXa low-molecular weight inhibitors. A detailed understanding of blood coagulation pathways, functioning of the serine proteases thrombin, FXa, FVIIa and FIXa and elucidation of their crystal structures resulted in many potent compounds, among which some have entered the clinical phase or have been approved for use in clinical practice. Recently, the focus of anticoagulant research turned to inhibition of the TF:FVIIa complex, with some promising clinical candidates on the horizon. This article provides an overview of the current development status of serine protease inhibitors as anticoagulants, including new trends such as dual coagulation factor inhibitors.

Due to copyright restrictions, the access to the full text of this article is only available via subscription. In this paper, we present an analysis regarding the pneumatic air muscle modelling, with a particular emphasis on the exoskeleton robot control. We propose two calibration approaches for obtaining the model identification data. We used the measurement data acquired from the proposed approaches to identify different mathematical models of pneumatic muscles. These models specified the necessary muscle control pressure for the desired muscle force at a given muscle length value. We compared the performance between the different types of models identified by either of the calibration method. The identified model with the lowest validation error was implemented in pneumatic muscle control for an elbow exoskeleton system. As a result, the system exhibited satisfactory torque and position control tasks, adequately validating the proposed approach. Japanese MEXT SRPBS ; European Commission ; Japanese MIC ; MEXT KAKENHI ; JST-SICP ; MIC-SCOPE ; JSPS-MIZS Japan-Slovenia Research Cooperative Program ; ImPACT Program of Council for Science, Technology and Innovation ; NEDO ; Slovene Human Resources Development and Scholarship Fund.

In this paper we propose a human-in-the-loop approach for teaching robots how to solve part assembly tasks. In the proposed setup the human tutor controls the robot through a haptic interface and a hand-held impedance control interface. The impedance control interface is based on a linear spring-return potentiometer that maps the button position to the robot arm stiffness. This setup allows the tutor to modulate the robot compliance based on the given task requirements. The demonstrated motion and stiffness trajectories are encoded using Dynamical Movement Primitives and learnt using Locally Weight Regression. To validate the proposed approach we performed experiments using Kuka Light Weight Robot and HapticMaster robot. The task of the experiment was to teach the robot how to perform an assembly task involving sliding a bolt fitting inside a groove in order to mount two parts together. Different stiffness was required in different stages of the task execution to accommodate the interaction of the robot with the environment and possible human-robot cooperation.

The common structural feature of LK direct thrombin inhibitors is a strong basic group attached to the azaphenylalanine scaffold, which is important for the appropriate interaction at the thrombin active site. Our previous results have shown that this basic group could be responsible for a reduction of tracheal air flow and a fall of mean arterial pressure in anaesthetized rats, an undesired effect of direct thrombin inhibitors which correlated with their ability to release histamine from mast cells. In the present study, we investigated the mechanism of LK direct thrombin inhibitors-induced histamine release from rat peritoneal mast cells. We demonstrated that thrombin inhibitors with basic character (LK-732, LK-639 and LK-6063) provoked release of histamine from mast cells, while less basic analogs (LK-658, LK-633 and LK-6062) had no effect. Histamine released by LK-732 and LK-639 was suppressed by removal of sialic acid residues by neuraminidase and by pertussis toxin, an inhibitor of G i protein activity. Additional demonstration that G proteins are the targets of LK-732 and LK-639 was provided by the increase of GTPγS binding rate to G proteins in rat brain cortical membranes. Our results indicate that basic direct thrombin inhibitors LK-732 and LK-639 provoke release of histamine from mast cells by direct activation of G i proteins through the similar biochemical pathway as basic secretagogues.

SummaryThe main structural feature of direct thrombin inhibitor LK-732 responsible for the appropriate interaction at the thrombin active site is a strong basic group. A possibility that a strong basic group of LK-732 might contribute to the mast cell degranulation effect and consequent reduction of tracheal air flow (TAF) and fall of mean arterial blood pressure (MAP) in rats was investigated in the present study. At doses up to5 mg/kg (i. v.), LK-732 did not cause significant changes of TAF and MAP. At 7 mg/kg (i. v.),a sudden reduction of TAF and a fall of MAP was observed within 5 min after LK-732 administration (75% mortality, p=0. 007). A less basic direct thrombin inhibitor LK-658 (21 mg/ kg, i. v.) did not significantly disturb TAF and MAP. A reduction of TAF and a fall of MAP caused by LK-732 (7 mg/kg, i. v.) was almost completely abolished in rats with degranulated mast cells (0% mortality, p=0. 008). LK-732 concentration-dependently degranulated rat peritoneal mast cells in vitro (pEC50=1. 92±0. 05 µM). A structure-activity relationship (SAR) study revealed that the terminal basic groups attached to the aromatic ring are responsible for the mast cell degranulation effect. A good correlation was observed between mast cell degranulation and pKb of analogues of LK-732 (R2=0. 49), but not between mast cell degranulation and thrombin Ki (R2=0. 23). LK-732-induced reduction of TAF, the fall of MAP and high mortality originate from LK732-induced mast cell degranulation. As judged by the SAR study, this effect could be overcome by reducing the basicity of LK-732.

SummaryThe antithrombotic potential of new direct thrombin inhibitors built on the azaphenylalanine scaffold (LK-732, LK-639 and LK-731) and their amidoxime prodrugs (LK-658, LK-633 and LK-730) was studied in comparison to argatroban and nadroparin in two rat models of venous thrombosis, induced either by complete stasis combined with hypercoagulability (model 1) or by partial stasis combined with vessel injury (model 2). In initial experiments LK-732 was established as the most promising antithrombotic of the LK inhibitors and as such was further tested. In model 1, intravenous bolus administration of LK-732 produced a dose-dependent inhibition of thrombus formation with an ID50 value of 1.3 mg/kg. This ID50 value was approximately four times higher than the ID50 value of argatroban (0.3 mg/kg; p=0.011). However, in model 2, LK-732 and argatroban decreased thrombus weight by 50% at similar ID50 values (3.8 mg/kg vs 3.0 mg/kg, respectively; p=0.726). The ex vivo anticoagulant effect of LK-732 was substantially weaker compared to argatroban at doses that produced comparable antithrombotic effects. After subcutaneous administration, in vivo thrombus weight reduction of LK inhibitors (10 mg/kg) ranged between 22 to 48%. However, their oral antithrombotic effect at a dose of 30 mg/kg was rather low. LK amidoxime prodrugs failed to produce a substantial antithrombotic effect after subcutaneous (10 mg/ kg) as well as after oral administration (30 mg/kg). In conclusion, thrombin inhibitors built on the azaphenylalanine scaffold represent a new group of intravenously effective antithrombotics. However, optimisation of the oral antithrombotic effect of amid-oxime prodrug LK-658 of the lead inhibitor LK-732 is required for justifying further development of these inhibitors.

We propose an approach that combines human demonstrated posture-control skill defined by the motion in the lower limb joints with an inverse kinematics solution of an arbitrary hand motion. The posture-control skill for humanoid robot was obtained through the human-in-the-loop teaching approach. The collected data during the teaching phase was used to approximate functional relation between the state of the robot's centre-of-pressure and the appropriate motion in the joints of the leg. The motion of the robot's hand was prescribed using the inverse kinematic solution. The posture-control skill and the motion of the hand were combined together using the task priority resolution strategy. We tested our approach with an experiment where the humanoid robot had to spin a spindle device with the hand and simultaneously maintain balance in the presence of external perturbations. In addition, we propose an upgrade that allows switching of control over the leg joints between arm task and posture-control task.

Literature and experimental data relevant for the decision to allow a waiver of in vivo bioequivalence (BE) testing for the approval of immediate release (IR) solid oral dosage forms containing levetiracetam are reviewed. Data on solubility and permeability suggest that levetiracetam belongs to class I of the biopharmaceutical classification system (BCS). Levetiracetam's therapeutic use, its wide therapeutic index, and its favorable pharmacokinetic properties make levetiracetam a valid candidate for the BCS-based biowaiver approach. Further, no BE studies with levetiracetam IR formulations in which the test formulation failed to show BE with the comparator have been reported in the open literature. On the basis of the overall evidence, it appears unlikely that a BCS-based biowaiver approach for levetiracetam IR solid oral dosage forms formulated with established excipients would expose patients to undue risks. Thus, the BCS-based biowaiver approach procedure is recommended for IR solid oral dosage form containing levetiracetam, provided the excipients in the formulation are also present in products that have been approved in countries belonging to or associated with the International Committee on Harmonization and are used in their usual quantities, and provided the dissolution profiles of the test and reference product comply with the current requirements for BCS-based biowaivers.

In this paper we propose a system capable of teaching humanoid robots new skills in real-time. The system aims to simplify the robot control and to provide a natural and intuitive interaction between the human and the robot. The key element of the system is exploitation of the human sensorimotor learning ability where a human demonstrator learns how to operate a robot in the same fashion as humans adapt to various everyday tasks. Another key aspect of the proposed system is that the robot learns the task simultaneously while the human is operating the robot. This enables the control of the robot to be gradually transferred from the human to the robot during the demonstration. The control is transferred based on the accuracy of the imitated task. We demonstrated our approach using an experiment where a human demonstrator taught a humanoid robot how to maintain the postural stability in the presence of the perturbations. To provide the appropriate feedback information of the robot's postural stability to the human sensorimotor system, we utilized a custom-built haptic interface. To absorb the demonstrated skill by the robot, we used Locally Weighted Projection Regression machine learning method. A novel approach was implemented to gradually transfer the control responsibility from the human to the incrementally built autonomous robot controller.

The excipient-mediated precipitation inhibition is classically determined by the quantification of the dissolved compound in the solution. In this study, two alternative approaches were evaluated, one is the light scattering (nephelometer) and other is the turbidity (plate reader) microtiter plate-based methods which are based on the quantification of the compound precipitate. Following the optimization of the nephelometer settings (beam focus, laser gain) and the experimental conditions, the screening of 23 excipients on the precipitation inhibition of poorly soluble fenofibrate and dipyridamole was performed. The light scattering method resulted in excellent correlation (r>0.91) between the calculated precipitation inhibitor parameters (PIPs) and the precipitation inhibition index (PI(classical)) obtained by the classical approach for fenofibrate and dipyridamole. Among the evaluated PIPs AUC100 (nephelometer) resulted in only four false positives and lack of false negatives. In the case of the turbidity-based method a good correlation of the PI(classical) was obtained for the PIP maximal optical density (OD(max), r=0.91), however, only for fenofibrate. In the case of the OD(max) (plate reader) five false positives and two false negatives were identified. In conclusion, the light scattering-based method outperformed the turbidity-based one and could be reliably used for identification of novel precipitation inhibitors.

The objective of this study was to evaluate the suitability and acceptance criteria of isolated rat jejunum model for Biopharmaceutics Classification System (BCS)—permeability classification. The evaluation followed recommended procedures including investigation of tissue integrity by applying damage triggers (nitrogen gassing, elevated temperature, azide addition), characterization of transporter functionality, and expression and development of correlation between rats' apparent permeability coefficient ( P app ) versus humans' and versus oral fraction absorbed ( f a ) in humans. Firstly, damage triggers caused a decrease in transepithelial resistance and potential difference and increase in lucifer yellow (LY) and fluorescein isothiocyanate (FITC)–dextran P app . However, only FITC–dextran P app 's increase was considered significant in all treatment groups, making FITC–dextran a better indicator of jejunum integrity than LY. Secondly, the expression level of selected intestinal transporters highly correlated between rat and human and functionality of P-glycoprotein was confirmed. P app of investigated drugs correlated with human f a ( R 2 = 0.85, n = 20) and with human permeability coefficients ( R 2 = 0.86, n = 13). Utility of described model for BCS classification was shown on levetiracetam, where significantly higher permeability of levetiracetam as compared with internal standard metoprolol was determined ( t -test, p = 0.005). In conclusion, isolated rat jejunum model is a useful tool not only for mechanistic investigation, but also for permeability classification according to BCS and consequently for BCS-based biowaiver procedures.