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Visual heading estimation is subject to periodic patterns of constant (bias) and variable (noise) error. The nature of the errors, however, appears to differ between studies, showing underestimation in some, but overestimation in others. We investigated whether field of view (FOV), the availability of binocular disparity cues, motion profile, and visual scene layout can account for error characteristics, with a potential mediating effect of vection. Twenty participants (12 females) reported heading and rated vection for visual horizontal motion stimuli with headings ranging the full circle, while we systematically varied the above factors. Overall, the results show constant errors away from the fore-aft axis. Error magnitude was affected by FOV, disparity, and scene layout. Variable errors varied with heading angle, and depended on scene layout. Higher vection ratings were associated with smaller variable errors. Vection ratings depended on FOV, motion profile, and scene layout, with the highest ratings for a large FOV, cosine-bell velocity profile, and a ground plane scene rather than a dot cloud scene. Although the factors did affect error magnitude, differences in its direction were observed only between participants. We show that the observations are consistent with prior beliefs that headings align with the cardinal axes, where the attraction of each axis is an idiosyncratic property.

In environments where orientation is ambiguous, the visual system uses prior knowledge about lighting coming from above to recognize objects, determine which way is up, and reorient the body. Here we investigated the extent with which assumed light from above preferences are affected by body orientation and the orientation of the retina relative to gravity. We tested the ability to extract shape-from-shading with seven human male observers positioned in multiple orientations relative to gravity using a modified KUKA anthropomorphic robot arm. Observers made convex-concave judgments of a central monocularly viewed stimulus with orientations of a shading gradient consistent with being lit from one of 24 simulated illumination directions. By positioning observers in different roll-tilt orientations relative to gravity and when supine, we were able to monitor change in the light-from-above prior (the orientation at which a shaded disk appears maximally convex). The results confirm previous findings that the light-from-above prior changes with body orientation relative to gravity. Interestingly, the results varied also with retinal orientation as well as an additional component that was approximately twice the frequency of retinal orientation. We use a modelling approach to show that the data are well predicted by summing retinal orientation with cross-multiplied utricle and saccule signals of the vestibular system, yielding gravity-dependent biases in the ability to extract shape-from-shading. We conclude that priors such as light coming from above appear to be constantly updated by neural processes that monitor self-orientation to achieve optimal object recognition over moderate deviations from upright posture at the cost of poor recognition when extremely tilted relative to gravity.

Percepts of verticality are thought to be constructed as a weighted average of multisensory inputs, but the observed weights differ considerably between studies. In the present study, we evaluate whether this can be explained by differences in how visual, somatosensory and proprioceptive cues contribute to representations of the Head In Space (HIS) and Body In Space (BIS). Participants (10) were standing on a force plate on top of a motion platform while wearing a visualization device that allowed us to artificially tilt their visual surroundings. They were presented with (in)congruent combinations of visual, platform, and head tilt, and performed Rod & Frame Test (RFT) and Subjective Postural Vertical (SPV) tasks. We also recorded postural responses to evaluate the relation between perception and balance. The perception data shows that body tilt, head tilt, and visual tilt affect the HIS and BIS in both experimental tasks. For the RFT task, visual tilt induced considerable biases (≈ 10° for 36° visual tilt) in the direction of the vertical expressed in the visual scene; for the SPV task, participants also adjusted platform tilt to correct for illusory body tilt induced by the visual stimuli, but effects were much smaller (≈ 0.25°). Likewise, postural data from the SPV task indicate participants slightly shifted their weight to counteract visual tilt (0.3° for 36° visual tilt). The data reveal a striking dissociation of visual effects between the two tasks. We find that the data can be explained well using a model where percepts of the HIS and BIS are constructed from direct signals from head and body sensors, respectively, and indirect signals based on body and head signals but corrected for perceived neck tilt. These findings show that perception of the HIS and BIS derive from the same sensory signals, but see profoundly different weighting factors. We conclude that observations of different weightings between studies likely result from querying of distinct latent constructs referenced to the body or head in space.

Spatial orientation relies on a representation of the position and orientation of the body relative to the surrounding environment. When navigating in the environment, this representation must be constantly updated taking into account the direction, speed, and amplitude of body motion. Visual information plays an important role in this updating process, notably via optical flow. Here, we systematically investigated how the size and the simulated portion of the field of view (FoV) affect perceived visual speed of human observers. We propose a computational model to account for the patterns of human data. This model is composed of hierarchical cells' layers that model the neural processing stages of the dorsal visual pathway. Specifically, we consider that the activity of the MT area is processed by populations of modeled MST cells that are sensitive to the differential components of the optical flow, thus producing selectivity for specific patterns of optical flow. Our results indicate that the proposed computational model is able to describe the experimental evidence and it could be used to predict expected biases of speed perception for conditions in which only some portions of the visual field are visible.

Motion cueing algorithms are used in motion simulation to map the inertial vehicle motion onto the limited simulator motion space. This mapping causes mismatches between the unrestricted visual motion and the constrained inertial motion, which results in perceived motion incongruence (PMI). It is still largely unknown what exactly causes visual and inertial motion in a simulator to be perceived as incongruent. Current methods for measuring motion incongruence during motion simulation result in time-invariant measures of the overall incongruence, which makes it difficult to determine the relevance of the individual and short-duration mismatches between visual and inertial motion cues. In this paper, a novel method is presented to subjectively measure the time-varying PMI continuously throughout a simulation. The method is analyzed for reliability and validity of its measurements, as well as for its applicability in relating physical short-duration cueing errors to PMI. The analysis shows that the method is reliable and that the results can be used to obtain a deeper insight into the formation of motion incongruence during driving simulation.

Background: Smoking is a strong environmental factor leading to adverse outcomes in Crohn's disease, but a more benign course in ulcerative colitis. Several single nucleotide polymorphisms (SNPs) are associated with smoking quantity and behaviour.Aim: To assess whether smoking-associated SNPs interact with smoking to influence the clinical course of inflammatory bowel diseases.Methods: Genetic and prospectively obtained clinical data from 1434 Swiss inflammatory bowel disease cohort patients (821 Crohn's disease and 613 ulcerative colitis) were analysed. Six SNPs associated with smoking quantity and behaviour (rs588765, rs1051730, rs1329650, rs4105144, rs6474412 and rs3733829) were combined to form a risk score (range: 0-12) by adding the number of risk alleles. We calculated multivariate models for smoking, risk of surgery, fistula, Crohn's disease location and ulcerative colitis disease extent.Results: In Crohn's disease patients who smoke, the number of surgeries was associated with the genetic risk score. This translates to a predicted 3.5-fold (95% confidence interval: 2.4- to 5.7-fold, P7 had a significantly shorter time to first intestinal surgery. The genetic risk score did not predict surgery in ulcerative colitis or occurrence of fistulae in Crohn's disease. SNP rs6265 was associated with ileal disease in Crohn's disease (PPConclusions: SNPs associated with smoking quantity is associated with an increased risk for surgery in Crohn's disease patients who smoke. Our data provide an example of genetics interacting with the environment to influence the disease course of inflammatory bowel disease.

Previous behavioral and neurophysiological research has shown better memory for horizontal than for vertical locations. In these studies, participants navigated toward these locations. In the present study we investigated whether the orientation of the spatial plane per se was responsible for this difference. We thus had participants learn locations visually from a single perspective and retrieve them from multiple viewpoints. In three experiments, participants studied colored tags on a horizontally or vertically oriented board within a virtual room and recalled these locations with different layout orientations (Exp. 1) or from different room-based perspectives (Exps. 2 and 3). All experiments revealed evidence for equal recall performance in horizontal and vertical memory. In addition, the patterns for recall from different test orientations were rather similar. Consequently, our results suggest that memory is qualitatively similar for both vertical and horizontal two-dimensional locations, given that these locations are learned from a single viewpoint. Thus, prior differences in spatial memory may have originated from the structure of the space or the fact that participants navigated through it. Additionally, the strong performance advantages for perspective shifts (Exps. 2 and 3) relative to layout rotations (Exp. 1) suggest that configurational judgments are not only based on memory of the relations between target objects, but also encompass the relations between target objects and the surrounding room—for example, in the form of a memorized view. Electronic supplementary material The online version of this article (10.3758/s13421-017-0753-9) contains supplementary material, which is available to authorized users.

Recognizing who is carrying out an action is essential for successful human interaction. The cognitive mechanisms underlying this ability are little understood and have been subject of discussions in embodied approaches to action recognition. Here we examine one solution, that visual action recognition processes are at least partly sensitive to the actor’s identity. We investigated the dependency between identity information and action related processes by testing the sensitivity of neural action recognition processes to clothing and facial identity information with a behavioral adaptation paradigm. Our results show that action adaptation effects are in fact modulated by both clothing information and the actor’s facial identity. The finding demonstrates that neural processes underlying action recognition are sensitive to identity information (including facial identity) and thereby not exclusively tuned to actions. We suggest that such response properties are useful to help humans in knowing who carried out an action.

This brief communication reports on a patient with an exceedingly rare “8p11 (eight-p-eleven) myeloproliferative syndrome” (EMS) with CEP110-FGFR1 rearrangement who responded to treatment with the multi-tyrosine kinase inhibitor (TKI) dasatinib. Dasatinib improved quality of life substantially by increasing blood counts and reducing the need for transfusions. This report demonstrates that the second-generation TKI may provide a therapeutic option for elderly and frail EMS patients who cannot be offered aggressive therapy, including allogeneic hematopoietic cell transplantation.

Recent studies have shown the presence of distortions in proprioceptive hand localization tasks. Those results were interpreted as reflecting specific perceptual distortions bound to a body model. It was especially suggested that hand distortions could be related to distortions of somatotopic cortical maps. In this study, we show that hand distortions measured in localization tasks might be partly driven by a general false belief about hand landmark locations (conceptual biases). We especially demonstrate that hand and object distortions are present in similar magnitude when correcting for the conceptual bias of the knuckles (Experiment 1) or when asking participants to directly locate spatially well-represented landmarks (i.e., without conceptual biases) on their hand (Experiment 2). Altogether our results suggest that localization task distortions are nonspecific to the body and that similar perceptual distortions could underlie localization performance measured on objects and hands. (PsycINFO Database Record

International audience; Creating metrically accurate avatars is important for many applications such as virtual clothing try-on, ergonomics, medicine, immersive social media, telepresence, and gaming. Creating avatars that precisely represent a particular individual is challenging however, due to the need for expensive 3D scanners, privacy issues with photographs or videos, and difficulty in making accurate tailoring measurements. We overcome these challenges by creating “The Virtual Caliper”, which uses VR game controllers to make simple measurements. First, we establish what body measurements users can reliably make on their own body. We find several distance measurements to be good candidates and then verify that these are linearly related to 3D body shape as represented by the SMPL body model. The Virtual Caliper enables novice users to accurately measure themselves and create an avatar with their own body shape. We evaluate the metric accuracy relative to ground truth 3D body scan data, compare the method quantitatively to other avatar creation tools, and perform extensive perceptual studies. We also provide a software application to the community that enables novices to rapidly create avatars in fewer than five minutes. Not only is our approach more rapid than existing methods, it exports a metrically accurate 3D avatar model that is rigged and skinned.

Multicamera tracking of humans and animals in outdoor environments is a relevant and challenging problem. Our approach to it involves a team of cooperating microaerial vehicles (MAVs) with on-board cameras only. Deep neural networks (DNNs) often fail at detecting small-scale objects or those that are far away from the camera, which are typical characteristics of a scenario with aerial robots. Thus, the core problem addressed in this letter is how to achieve on-board, online, continuous, and accurate vision-based detections using DNNs for visual person tracking through MAVs. Our solution leverages cooperation among multiple MAVs and active selection of most informative regions of image. We demonstrate the efficiency of our approach through simulations with up to 16 robots and real-robot experiments involving two aerial robots tracking a person, while maintaining an active perception-driven formation. ROS-based source code is provided for the benefit of the community.

In this paper we design a nonlinear controller for aggressive maneuvering of a quadrotor. We take a maneuver regulation perspective. Differently from the classical trajectory tracking approach, maneuver regulation does not require following a timed reference state, but a geometric “path” with a velocity (and possibly orientation) profile assigned on it. The proposed controller relies on three main ideas. Given a desired maneuver, i.e., a set of state trajectories equivalent under time translations, the system dynamics is decomposed into dynamics longitudinal and transverse to the maneuver. A space-dependent version of the transverse dynamics is derived, by using the longitudinal state, i.e., the arc-length of the path, as an independent variable. Then the controller is obtained as a function of the arc-length consisting of two terms: a feed forward term, being the nominal input to apply when on the path at the current arc-length, and a feedback term exponentially stabilizing the state-dependent transverse dynamics. Numerical computations are presented to prove the effectiveness of the proposed strategy. The controller performances are tested in presence of uncertainty of the model parameters and input noise and saturations. The controller is also tested in a realistic simulation environment validated against an experimental test-bed.

When in darkness, humans can perceive the direction and magnitude of rotations and of linear translations in the horizontal plane. The current paper addresses the integrated perception of combined translational and rotational motion, as it occurs when moving along a curved trajectory. We questioned whether the perceived motion through the environment follows the predictions of a self-motion perception model (e.g., Merfeld et al. in J Vestib Res 3:141–161, 1993; Newman in A multisensory observer model for human spatial orientation perception, 2009), which assume linear addition of rotational and translational components. For curved motion in darkness, such models predict a non-veridical motion percept, consisting of an underestimation of the perceived rotation, a distortion of the perceived travelled path, and a bias in the perceived heading (i.e., the perceived instantaneous direction of motion with respect to the body). These model predictions were evaluated in two experiments. In Experiment 1, seven participants were moved along a circular trajectory in darkness while facing the motion direction. They indicated perceived yaw rotation using an online tracking task, and perceived travelled path by drawings. In Experiment 2, the heading was systematically varied, and six participants indicated, in a 2-alternative forced-choice task, whether they perceived facing inward or outward of the circular path. Overall, we found no evidence for the heading bias predicted by the model. This suggests that the sum of the perceived rotational and translational components alone cannot adequately explain the overall perceived motion through the environment. Possibly, knowledge about motion dynamics and familiar stimuli combinations may play an important additional role in shaping the percept.

This study examined how navigators of large-scale environmental spaces come up with survey estimates of distant targets. Participants learned a route through a virtual city by walking it multiple times in one direction on an omnidirectional treadmill. After learning, they were teleported to intersections along the route and pointed to multiple other locations. Locations were always queried in chunks of related trials relative to a participant’s current position, either to all locations route forwards or all locations route backwards. For their first pointing, participants took twice as long as for the later pointings and latency correlated with the number of intersections to the target, which was not the case for later pointings. These findings are inconsistent with reading out coordinates from a cognitive map but fit well with constructive theories which suggest that participants integrated locations between their current location and the target along the learned path. Later pointings to adjacent intersections within a chunk of trials continued this process using the previous estimation. Additionally, in first pointings participants’ estimates were quicker and more accurate when targets were located route forwards than route backwards. This route direction effect shows that the long-term memory employed in generating survey estimates must be directed – either in form of a directed graph or a combination of a directed route layer and an undirected survey layer.

Most studies on spatial memory refer to the horizontal plane, leaving an open question as to whether findings generalize to vertical spaces where gravity and the visual upright of our surrounding space are salient orientation cues. In three experiments, we examined which reference frame is used to organize memory for vertical locations: the one based on the body vertical, the visual-room vertical, or the direction of gravity. Participants judged interobject spatial relationships learned from a vertical layout in a virtual room. During learning and testing, we varied the orientation of the participant's body (upright vs. lying sideways) and the visually presented room relative to gravity (e.g., rotated by 90° along the frontal plane). Across all experiments, participants made quicker or more accurate judgments when the room was oriented in the same way as during learning with respect to their body, irrespective of their orientations relative to gravity. This suggests that participants employed an egocentric body-based reference frame for representing vertical object locations. Our study also revealed an effect of body-gravity alignment during testing. Participants recalled spatial relations more accurately when upright, regardless of the body and visual-room orientation during learning. This finding is consistent with a hypothesis of selection conflict between different reference frames. Overall, our results suggest that a body-based reference frame is preferred over salient allocentric reference frames in memory for vertical locations perceived from a single view. Further, memory of vertical space seems to be tuned to work best in the default upright body orientation. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

In this study, we demonstrate the effects of anxiety and cognitive load on eye movement planning in an instrument flight task adhering to a single-sensor-single-indicator data visualisation design philosophy. The task was performed in neutral and anxiety conditions, while a low or high cognitive load, auditory n-back task was also performed. Cognitive load led to a reduction in the number of transitions between instruments, and impaired task performance. Changes in self-reported anxiety between the neutral and anxiety conditions positively correlated with changes in the randomness of eye movements between instruments, but only when cognitive load was high. Taken together, the results suggest that both cognitive load and anxiety impact gaze behavior, and that these effects should be explored when designing data visualization displays.

While some unmanned aerial vehicles (UAVs) have the capacity to carry mechanically stabilized camera equipment, weight limits or other problems may make mechanical stabilization impractical. As a result many UAVs rely on fixed cameras to provide a video stream to an operator or observer. With a fixed camera, the video stream is often unsteady due to the multirotor's movement from wind and acceleration. These video streams are often analyzed by both humans and machines, and the unwanted camera movement can cause problems for both. For a human observer, unwanted movement may simply make it harder to follow the video, while for computer algorithms, it may severely impair the algorithm's intended function. There has been significant research on how to stabilize videos using feature tracking to determine camera movement, which in turn is used to manipulate frames and stabilize the camera stream. We believe, however, that this process could be greatly simplified by using data from a UAV's on-board inertial measurement unit (IMU) to stabilize the camera feed. In this paper we present an algorithm for video stabilization based only on IMU data from a UAV platform. Our results show that our algorithm successfully stabilizes the camera stream with the added benefit of requiring less computational power.

Objective Cervical cancer precursor screening by HPV testing has a low positive predictive value for advanced lesion. HPV16 RNA patterns characteristic for HPV16-transformed cells but based on laborious, cost-intensive singleplex NASBA reactions promised high value in triaging HPV16 DNA-positive women. Methods We developed two high-throughput reverse transcriptase quantitative (RT-q) PCR assays for the HPV16 transcripts E6*I, E1^E4 and E1C and the cellular transcript ubiquitin C and analysed RNA of 158 singly HPV16 DNA-positive cervical cell samples archived in PreservCyt buffer for the presence of transformation-associated HPV16 RNA patterns, i.e., upregulation of E6*I relative to E1^E4 and/or presence of E1C. Results HPV16 RNA pattern analyses classified 85% of 58 samples diagnosed ≤CIN1 (no cytologically and histologically detectable cervical lesion or CIN grade 1) as negative and 90% of 59 samples diagnosed as ≥CIN3 (CIN grade 3 or invasive cancer) as positive. Among 41 CIN grade 2 samples representing an intermediate lesion group, 49% were HPV16 RNA patterns-positive. Interestingly, 3 of 4 HPV16 RNA patterns-positive lesions initially diagnosed as ≤CIN1 at follow-up 5–24months later had progressed to ≥CIN2. Conclusions We successfully developed and validated a second generation of HPV16 RNA patterns assay by rapid RT-qPCR as triage marker for HPV16 DNA-positive women offering clinical utility to distinguish between the need for immediate colposcopy and continued observation. Limited follow-up data suggests that HPV16 RNA patterns-positivity in ≤CIN1 lesions can predict disease progression.

While moving through the environment, humans use vision to discriminate different self-motion intensities and to control their actions (e.g. maintaining balance or controlling a vehicle). How the intensity of visual stimuli affects self-motion perception is an open, yet important, question. In this study, we investigate the human ability to discriminate perceived velocities of visually induced illusory self-motion (vection) around the vertical (yaw) axis. Stimuli, generated using a projection screen (70 × 90 deg field of view), consist of a natural virtual environment (360 deg panoramic colour picture of a forest) rotating at constant velocity. Participants control stimulus duration to allow for a complete vection illusion to occur in every single trial. In a two-interval forced-choice task, participants discriminate a reference motion from a comparison motion, adjusted after every presentation, by indicating which rotation feels stronger. Motion sensitivity is measured as the smallest perceivable change in stimulus intensity (differential threshold) for eight participants at five rotation velocities (5, 15, 30, 45 and 60 deg/s). Differential thresholds for circular vection increase with stimulus velocity, following a trend well described by a power law with an exponent of 0.64. The time necessary for complete vection to arise is slightly but significantly longer for the first stimulus presentation (average 11.56 s) than for the second (9.13 s) and does not depend on stimulus velocity. Results suggest that lower differential thresholds (higher sensitivity) are associated with smaller rotations, because they occur more frequently during everyday experience. Moreover, results also suggest that vection is facilitated by a recent exposure, possibly related to visual motion after-effect.

The perceptual upright is thought to be constructed by the central nervous system (CNS) as a vector sum; by combining estimates on the upright provided by the visual system and the body’s inertial sensors with prior knowledge that the upright is usually above the head. Results from a number of recent studies furthermore show that the weighting of the respective sensory signals is proportional to their reliability, consistent with a Bayesian interpretation of the idea of a vector sum (Forced Fusion, FF). However, findings from a study conducted in partial gravity suggest that the CNS may rely on a single sensory system (Cue Capture, CC), or choose to process sensory signals differently based on inferred signal causality (Causal Inference, CI). We developed a novel Alternative-Reality system to manipulate visual and physical tilt independently, and tasked participants (n=28) to indicate the perceived upright for various (in-)congruent combinations of visual-inertial stimuli. Overall, the data appear best explained by the FF model. However, an evaluation of individual data reveals considerable variability, favoring different models in about equal proportions of participants (FF, n=12; CI, n=7, CC, n=9). Given the observed variability, we conclude that the notion of a vector sum does not provide a comprehensive explanation of the perception of the upright.

In this paper we study if approximated linear models are accurate enough to predict the vibrations of a cable of a Cable-Driven Parallel Robot (CDPR) for different pretension levels. In two experiments we investigated the damping of a thick steel cable from the Cablerobot simulator [1] and measured the motion of the cable when a sinusoidal force is applied at one end of the cable. Using this setup and power spectral density analysis we measured the natural frequencies of the cable and compared these results to the frequencies predicted by two linear models: i) the linearization of partial differential equations of motion for a distributed cable, and ii) the discretization of the cable using a finite elements model. This comparison provides remarkable insights into the limits of approximated linear models as well as important properties of vibrating cables used in CDPR.

Eye-movements are typically measured with video cameras and image recognition algorithms. Unfortunately, these systems are susceptible to changes in illumination during measurements. Electrooculography (EOG) is another approach for measuring eye-movements that does not suffer from the same weakness. Here, we introduce and compare two methods that allow us to extract the dwells of our participants from EOG signals under presentation conditions that are too difficult for optical eye tracking. The first method is unsupervised and utilizes density-based clustering. The second method combines the optical eye-tracker’s methods to determine fixations and saccades with unsupervised clustering. Our results show that EOG can serve as a sufficiently precise and robust substitute for optical eye tracking, especially in studies with changing lighting conditions. Moreover, EOG can be recorded alongside electroencephalography (EEG) without additional effort.

Auditory warnings are often used to direct a user’s attention from a primary task to critical peripheral events. In the context of traffic, in-vehicle collision avoidance systems could, for example, employ spatially relevant sounds to alert the driver to the possible presence of a crossing pedestrian. This raises the question: What is an effective auditory alert in a steering environment? Ideally, such warning signals should not only arouse the driver but also result in deeper processing of the event that the driver is being alerted to. Warning signals can be designed to convey the time to contact with an approaching object (Gray, 2011). That is, sounds can rise in intensity in accordance with the physical velocity of an approaching threat. The current experiment was a manual steering task in which participants were occasionally required to recognized peripheral visual targets. These visual targets were sometimes preceded by a spatially congruent auditory warning signal. This was either a sound with constant intensity, linearly rising intensity, or non-linearly rising intensity that conveyed time-to-contact. To study the influence of warning cues on the arousal state, different features of electroencephalography (EEG) were measured. Alpha frequency, which ranges from 7.5 to 12.5 Hz, is believed to represent different cognitive processes, in particular arousal (Klimesch, 1999). That is, greater desynchronization in the alpha frequency reflects higher levels of attention as well as alertness. Our results showed a significant decrease in alpha power for sounds with rising intensity profiles, indicating increased alertness and expectancy for an event to occur. To analyze whether the increased arousal for rising sounds resulted in deeper processing of the visual target, we analyzed the event related potential P3. It is a positive component that occurs approximately 300 ms after an event and is known to be associated with recognition performance of a stimulus (Parasuraman & Beatty, 1980). In other words, smaller P3 amplitudes indicate worse identification than larger amplitudes. Our results show that sounds with time-to-contact properties induced larger P3 responses to the targets that they cued compared to targets cued by constant or linearly rising sounds. This suggests that rising sounds with time-to-contact intensity profiles evoke deeper processing of the visual target and therefore result in better identification than events cued by sounds with linearly rising or constant intensity.

Reliable and accurate car driver head pose estimation is an important function for the next generation of Advanced Driver Assistance Systems that need to consider the driver state in their analysis. For optimal performance, head pose estimation needs to be non-invasive, calibration-free and accurate for varying driving and illumination conditions. In this pilot study we investigate a 3D head pose estimation system that automatically fits a statistical 3D face model to measurements of a driver's face, acquired with a low-cost depth sensor on challenging real-world data. We evaluate the results of our sensor-independent, driver-adaptive approach to those of a state-of-the-art camera-based 2D face tracking system as well as a non-adaptive 3D model relative to own ground-truth data, and compare to other 3D benchmarks. We find large accuracy benefits of the adaptive 3D approach. Our system shows a median error of 5.99 mm for position and 2.12° for rotation while delivering a full 6-DOF pose with very little degradation from strong illumination changes or out-of-plane rotations of more than 50°. In terms of accuracy, 95% of all our results have a position error of less than 9.50 mm, and a rotation error of less than 4.41°. Compared to the 2D method, this represents a 59.7% reduction of the 95% rotation accuracy threshold, and a 56.1% reduction of the median rotation error.

Unrestricted gaze tracking that allows for head and body movements can enable us to understand interactive gaze behavior with large-scale visualizations. Approaches that support this, by simultaneously recording eye- and user-movements, can either be based on geometric or data-driven regression models. A data-driven approach can be implemented more flexibly but its performance can suffer with poor quality training data. In this paper, we introduce a pre-processing procedure to remove training data for periods when the gaze is not fixating the presented target stimuli. Our procedure is based on a velocity-based filter for rapid eye-movements (i.e., saccades). Our results show that this additional procedure improved the accuracy of our unrestricted gaze-tracking model by as much as 56 %. Future improvements to data-driven approaches for unrestricted gaze-tracking are proposed, in order to allow for more complex dynamic visualizations.

This paper introduces the CableRobot simulator, which was developed at the Max Planck Institute for Biological Cybernetics in cooperation with the Fraunhofer Institute for Manufacturing Engineering and Automation IPA. The simulator is a completely novel approach to the design of motion simulation platforms in so far as it uses cables and winches for actuation instead of rigid links known from hexapod simulators. This approach allows to reduce the actuated mass, scale up the workspace significantly, and provides great flexibility to switch between system configurations in which the robot can be operated. The simulator will be used for studies in the field of human perception research and virtual reality applications. The paper dicusses some of the issues arising from the usage of cables and provides a system overview regarding kinematics and system dynamics as well as giving a brief introduction into possible application use cases.

Categorization of seen objects is often determined by the shapes of objects. However, shape is not exclusive to the visual modality: The haptic system also is expert at identifying shapes. Hence, an important question for understanding shape processing is whether humans store separate modality-dependent shape representations, or whether information is integrated into one multisensory representation. To answer this question, we created a metric space of computer-generated novel objects varying in shape. These objects were then printed using a 3-D printer, to generate tangible stimuli. In a categorization experiment, participants first explored the objects visually and haptically. We found that both modalities led to highly similar categorization behavior. Next, participants were trained either visually or haptically on shape categories within the metric space. As expected, visual training increased visual performance, and haptic training increased haptic performance. Importantly, however, we found that visual training also improved haptic performance, and vice versa. Two additional experiments showed that the location of the categorical boundary in the metric space also transferred across modalities, as did heightened discriminability of objects adjacent to the boundary. This observed transfer of metric category knowledge across modalities indicates that visual and haptic forms of shape information are integrated into a shared multisensory representation.

People use “route knowledge” to navigate to targets along familiar routes and “survey knowledge” to determine (by pointing, for example) a target’s metric location. We show that both root in separate memories of the same environment: participants navigating through their home city relied on representations and reference frames different from those they used when doing a matched survey task. Tubingen residents recalled their way along a familiar route to a distant target while located in a photorealistic virtual 3D model of Tubingen, indicating their route decisions on a keyboard. Participants had previously done a survey task (pointing) using the same start points and targets. Errors and response latencies observed in route recall were completely unrelated to errors and latencies in pointing. This suggests participants employed different and independent representations for each task. Further, participants made fewer routing errors when asked to respond from a horizontal walking perspective rather than a constant aerial perspective. This suggests that instead of the single reference, north-up frame (similar to a conventional map) they used in the survey task, participants employed different, and most probably multiple, reference frames learned from “on the ground” navigating experience. The implication is that, within their everyday environment, people use map or navigation-based knowledge according to which best suits the task.

In this paper, we show that differences in reaction times (RT) to self-motion depend not only on the duration of the profile, but also on the actual time course of the acceleration. We previously proposed models that described direction discrimination thresholds for rotational and translational motions based on the dynamics of the vestibular sensory organs (otoliths and semi-circular canals). As these models have the potential to describe RT for different motion profiles (e.g., trapezoidal versus triangular acceleration profiles or varying profile durations), we validated these models by measuring RTs in human observers for a direction discrimination task using both translational and rotational motions varying in amplitude, duration and acceleration profile shape in a within-subjects design. In agreement with previous studies, amplitude and duration were found to affect RT, and importantly, we found an influence of the profile shape on RT. The models are able to fit the measured RTs with an accuracy of around 5 ms, and the best-fitting parameters are similar to those found from identifying the models based on threshold measurements. This confirms the validity of the modeling approach and links perceptual thresholds to RT. By establishing a link between vestibular thresholds for self-motion and RT, we show for the first time that RTs to purely inertial motion stimuli can be used as an alternative to threshold measurements for identifying self-motion perception models. This is advantageous, since RT tasks are less challenging for participants and make assessment of vestibular function less fatiguing. Further, our results provide strong evidence that the perceived timing of self-motion stimulation is largely influenced by the response dynamics of the vestibular sensory organs.

Low-cost motion systems have been proposed for certain training tasks that would otherwise be performed on highperformance full-flight simulators. These systems usually have lower bandwidth and lower smoothness. The influence of these characteristics on pilot perception and control behavior is unknown and needs to be investigated. In this paper, this is done by simulating a model of a simulator with limited capabilities on a high-end simulator. The platform limitations, which consist of a platform filter, time delay, and noise characteristics, can then be removed one by one, and their effect on control behavior is studied in isolation. An experiment was conducted to identify pilot perception and control behavior in a closed-loop control task. The time delay and noise characteristics of the simulators did not have an effect. However, it was found that the bandwidth of the motion system had a significant effect on performance and control behavior. Results indicate that the motion cues were barely used at all in conditions with a low bandwidth, and that participants relied on the visual cues to generate lead to perform the control task.

International audience; In this paper, we investigate the effect of haptic cueing on human operator's performance in the field of bilateral teleoperation of multiple mobile robots, in particular multiple unmanned aerial vehicles (UAVs). Two aspects of human perfor- mance are deemed important in this area, namely the maneuver- ability of mobile robots and perceptual sensitivity of the remote environment. We introduce metrics that allow us to address these aspects in two psychophysical studies, which are reported here. Three fundamental haptic cue types were evaluated. The Force cue conveys information on the proximity of the commanded trajectory to obstacles in the remote environment. The Velocity cue represents the mismatch between the commanded and actual velocity of the UAVs and can implicitly provide a rich amount of information regarding the actual behavior of the UAVs. Finally, the Velocity+Force cue is a linear combination of the two. Our experimental results show that while maneuverability is best supported by the Force cue feedback, perceptual sensitivity is best served by the Velocity cue feedback. In addition, we show that large gains in the haptic feedbacks do not always guarantee an enhancement in teleoperator's performance.

In this paper we present the design of a platform for autonomous navigation of a quadrotor UAV based on RGB-D technology. The proposed platform can safely navigate in an unknown environment while self-stabilization is done relying only on its own sensor perception. We developed an estimation system based on the integration of IMU and RGB-D measurements in order to estimate the velocity of the quadrotor in its body frame. Experimental tests conducted as teleoperation experiments show the effectiveness of our approach in an unstructured environment.

Biodynamic feedthrough (BDFT) occurs when vehicle accelerations feed through the pilot’s body and cause involuntary motions of limbs, resulting in involuntary control inputs. BDFT can severely reduce ride comfort, control accuracy and, above all, safety during the operation of rotorcraft. Furthermore, BDFT can cause and sustain rotorcraft-pilot couplings. Despite many different studies conducted in past decades—both within and outside of the rotorcraft community—BDFT is still a poorly understood phenomenon. The complexities involved in BDFT have kept researchers and manufacturers in the rotorcraft domain from developing robust ways of dealing with its effects. A practical BDFT pilot model, describing the amount of involuntary control inputs as a function of accelerations, could pave the way to account for adverse BDFT effects. In the current paper, such a model is proposed. Its structure is based on the model proposed by Mayo (15th European Rotorcraft Forum, Amsterdam, pp. 81-001–81-012 1989), and its accuracy and usability are improved by incorporating insights from recently obtained experimental data. An evaluation of the model performance shows that the model describes the measured data well and that it provides a considerable improvement to the original Mayo model. Furthermore, the results indicate that the neuromuscular dynamics have an important influence on the BDFT model parameters.

The introduction of drug-eluting stents (DES) to interventional cardiology has been a breakthrough in the treatment of in-stent restenosis. However, the downside of reduced restenosis is a significantly prolonged and practically incalculable time to reendothelialization of thrombogenic stent-surfaces with an increased risk for coronary thrombosis. As the use of DES in non-coronary arteries (e.g. carotid, renal, infrainguinal and even cerebral arteries) is increasing, new vascular beds might be put at risk of ischemia. The practice of stopping antiplatelet drugs in a perioperative setting is highly problematic and contemporary guidelines released by scientific societies from different medical specialties have recently addressed this problem. While many case reports have reported alarming incidents of stent thrombosis, prospective clinical data are scarcely available to guide anticoagulation during the perioperative phase. This review summarizes information on the vascular biology of DES and associated adverse events based on a systematic search of the available literature in public data bases. An emphasis is put on the growing use of DES in non-coronary vessels and the associated danger of putting new vascular beds at risk of thrombotic complications.

In this paper, a novel decentralized control strategy for bilaterally teleoperating heterogeneous groups of mobile robots from different domains (aerial, ground, marine, and underwater) is proposed. By using a decentralized control architecture, the group of robots, which is treated as the slave side, is made able to navigate in a cluttered environment while avoiding obstacles, interrobot collisions, and following the human motion commands. Simultaneously, the human operator acting on the master side is provided with a suitable force feedback informative of the group response and of the interaction with the surrounding environment. Using passivity-based techniques, we allow the behavior of the group to be as flexible as possible with arbitrary split and join events (e.g., due to interrobot visibility/packet losses or specific task requirements) while guaranteeing the stability of the system. We provide a rigorous analysis of the system stability and steady-state characteristics and validate performance through human/hardware-in-the-loop simulations by considering a heterogeneous fleet of unmanned aerial vehicles (UAVs) and unmanned ground vehicles as a case study. Finally, we also provide an experimental validation with four quadrotor UAVs.

In the manual control of a dynamic system, the human controller (HC) is often required to follow a visible and predictable reference path. Using the predictable aspect of a reference signal, through applying feedforward control, the HC can significantly improve performance as compared to a purely feedback control strategy. A proper definition of a signal’s predictability, however, is never given in literature. This paper investigates the predictability of a sum-of-sinusoids target signal, as a function of the number of sinusoid components and the fact whether the sinusoid frequencies are harmonic, or not. A human-in-the-loop experiment was done, with target signals varying for these two signal characteristics. A combined feedback-feedforward HC model was identified and parameters were estimated. It was found that for all experimental conditions, subjects used a feedforward strategy. Results further showed that subjects were able to perform better for harmonic signals as compared to non-harmonic signals, for signals with roughly the same frequency content.

Shared control is becoming widely used in many manual control tasks as a mean for improving performance and safety. Designing an effective shared control system requires extensive testing and knowledge of how operators react to the haptic sensations provided by the control device shared with the support system. Commercial general purpose haptic devices may be unfit to reproduce the operational situation typical of the control task under study, like car driving or airplane flying. Thus specific devices are needed for research on specific task; this market niche exists but is characterized by expensive products. This paper presents the development of a complete low cost haptic stick, of its initial characterization and inner loop and impedance control systems design, and finally proposes an evaluation with two test cases: pilot admittance identification with the classical tasks, and an entire haptic experiment. In particular this latter experiment tries to study what happens when a system failure happens in a pilot support system built using a classical embedded controller, compared to a system built following the haptic shared control paradigm.

Equipped with four actuators, quadrotor Unmanned Aerial Vehicles belong to the family of underactuated systems. The lateral motion of such platforms is strongly coupled with their orientation and consequently it is not possible to track an arbitrary 6D trajectory in space. In this paper, we propose a novel quadrotor design in which the tilt angles of the propellers with respect to the quadrotor body are being simultaneously controlled with two additional actuators by employing the parallelogram principle. Since the velocity of the controlled tilt angles of the propellers does not appear directly in the derived dynamic model, the system cannot be static feedback linearized. Nevertheless, the system is linearizable at a higher differential order, leading to a dynamic feedback linearization controller. Simulations confirm the theoretical findings, highlighting the improved motion capabilities with respect to standard quadrotors.

In this paper, we present a collision-free indoor navigation algorithm for teleoperated multirotor Unmanned Aerial Vehicles (UAVs). Assuming an obstacle rich environment, the algorithm keeps track of detected obstacles in the local surroundings of the robot. The detection part of the algorithm is based on measurements from an RGB-D camera and a Bin-Occupancy filter capable of tracking an unspecified number of targets. We use the estimate of the robot's velocity to update the obstacles state when they leave the direct field of view of the sensor. The avoidance part of the algorithm is based on the Model Predictive Control approach. By predicting the possible future obstacles states, it filters the operator commands to prevent collisions. The method is validated on a platform equipped with its own computational unit, which makes it self-sufficient in terms of external CPUs.

In this paper we present a robust quadrotor controller for tracking a reference trajectory in presence of uncertainties and disturbances. A Super Twisting controller is implemented using the recently proposed gain adaptation law [1], [2], which has the advantage of not requiring the knowledge of the upper bound of the lumped uncertainties. The controller design is based on the regular form of the quadrotor dynamics, without separation in two nested control loops for position and attitude. The controller is further extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. The higher order quadrotor dynamic model and proposed controller are validated using a SimMechanics physical simulation with initial error, parameter uncertainties, noisy measurements and external perturbations.

Methods for identifying pilot's responses commonly assume time-invariant dynamics. However, humans are likely to vary their responses during realistic control scenarios. In this work an identification method is developed for estimating time-varying responses to visual and force feedback during a compensatory tracking task. The method describes pilot's responses with finite impulse response filters and use a Regularized Recursive Least Squares (RegRLS) algorithm to simultaneously estimate filter coefficients. The method was validated in a Monte-Carlo simulation study with different levels of remnant noise. With low levels of remnant noise, estimates were accurate and tracked the time-varying behaviour of the simulated responses. On the other hand, estimates showed high variability in case of large remnant noise. However, parameters of the RegRLS could be further optimized to improve robustness to large remnant noise. Taken together, these findings suggest that the novel RegRLS algorithm could be used to estimate time-varying pilot's responses in real human-in-the-loop experiments.

A long standing debate revolves around the question whether visual action recognition primarily relies on visual or motor action information. Previous studies mainly examined the contribution of either visual or motor information to action recognition. Yet, the interaction of visual and motor action information is particularly important for understanding action recognition in social interactions, where humans often observe and execute actions at the same time. Here, we behaviourally examined the interaction of visual and motor action recognition processes when participants simultaneously observe and execute actions. We took advantage of behavioural action adaptation effects to investigate behavioural correlates of neural action recognition mechanisms. In line with previous results, we find that prolonged visual exposure (visual adaptation) and prolonged execution of the same action with closed eyes (non-visual motor adaptation) influence action recognition. However, when participants simultaneously adapted visually and motorically – akin to simultaneous execution and observation of actions in social interactions - adaptation effects were only modulated by visual but not motor adaptation. Action recognition, therefore, relies primarily on vision-based action recognition mechanisms in situations that require simultaneous action observation and execution, such as social interactions. The results suggest caution when associating social behaviour in social interactions with motor based information.

Holistic processing—the tendency to perceive objects as indecomposable wholes—has long been viewed as a process specific to faces or objects of expertise. Although current theories differ in what causes holistic processing, they share a fundamental constraint for its generalization: Nonface objects cannot elicit facelike holistic processing in the absence of expertise. Contrary to this prevailing view, here we show that line patterns with salient Gestalt information (i.e., connectedness, closure, and continuity between parts) can be processed as holistically as faces without any training. Moreover, weakening the saliency of Gestalt information in these patterns reduced holistic processing of them, which indicates that Gestalt information plays a crucial role in holistic processing. Therefore, holistic processing can be achieved not only via a top-down route based on expertise, but also via a bottom-up route relying merely on object-based information. The finding that facelike holistic processing can extend beyond the domains of faces and objects of expertise poses a challenge to current dominant theories.

Faces are processed holistically, so selective attention to 1 face part without any influence of the others often fails. In this study, 3 experiments investigated what type of facial information (shape or surface) underlies holistic face processing and whether generalization of holistic processing to nonexperienced faces requires extensive discrimination experience. Results show that facial shape information alone is sufficient to elicit the composite face effect (CFE), 1 of the most convincing demonstrations of holistic processing, whereas facial surface information is unnecessary (Experiment 1). The CFE is eliminated when faces differ only in surface but not shape information, suggesting that variation of facial shape information is necessary to observe holistic face processing (Experiment 2). Removing 3-dimensional (3D) facial shape information also eliminates the CFE, indicating the necessity of 3D shape information for holistic face processing (Experiment 3). Moreover, participants show similar holistic processing for faces with and without extensive discrimination experience (i.e., own- and other-race faces), suggesting that generalization of holistic processing to nonexperienced faces requires facial shape information, but does not necessarily require further individuation experience. These results provide compelling evidence that facial shape information underlies holistic face processing. This shape-based account not only offers a consistent explanation for previous studies of holistic face processing, but also suggests a new ground-in addition to expertise-for the generalization of holistic processing to different types of faces and to nonface objects.

This paper addresses the problem of cooperative aerial transportation of an object using a team of quadrotors. The approach presented to solve this problem accounts for the full dynamics of the system and it is inspired by the literature on reconfigurable cable-driven parallel robots (RCDPR). Using the modelling convention of RCDPR it is derived a direct relation between the motion of the quadrotors and the motion of the payload. This relation makes explicit the available internal motion of the system, which can be used to automatically achieve additional tasks. The proposed method does not require to specify a priory the forces in the cables and uses a tension distribution algorithm to optimally distribute them among the robots. The presented framework is also suitable for online teleoperation. Physical simulations with a human-in-the-loop validate the proposed approach.

Robustness and flexibility constitute the main advantages of multiple-robot systems with respect to single-robot ones as per the recent literature. The use of multiple unmanned aerial vehicles (UAVs) combines these benefits with the agility and pervasiveness of aerial platforms [1], [2]. The degree of autonomy of the multi-UAV system should be tuned according to the specificities of the situation under consideration. For regular missions, fully autonomous UAV systems are often appropriate, but, in general, the use of semiautonomous groups of UAVs, supervised or partially controlled by one or more human operators, is the only viable solution to deal with the complexity and unpredictability of real-world scenarios as in, e.g., the case of search and rescue missions or exploration of large/cluttered environments [3]. In addition, the human presence is also mandatory for taking the responsibility of critical decisions in high-risk situations [4].

OBJECTIVES: The optimal surgical treatment of patients with bicuspid aortic valve (BAV) disease and ascending aortic aneurysm is controversial. The aim of this study was to evaluate the risk of late aortic events after an isolated aortic valve replacement (AVR) for BAV stenosis with concomitant mild-to-moderate proximal aortic dilation. METHODS: A review of our institutional BAV database identified a subgroup of 153 consecutive BAV patients (mean age 54.2 ± 10.5 years, 73% men) with BAV stenosis and concomitant ascending aortic dilation of 40–50 mm who underwent an isolated AVR from 1995 to 2000. All cases of simultaneous aortic surgery (i.e. ascending aorta with a diameter of >50 mm) were excluded. The follow-up (1759 patient-years) was 100% complete. The mean follow-up was 11.5 ± 3.2 years. Adverse aortic events were defined as the need for proximal aortic surgery, the occurrence of aortic dissection/rupture or sudden death during the follow-up. RESULTS: Actuarial survival rates of our study population were 86 and 78% at 10 and 15 years, respectively. Ascending aortic surgery was required in five patients (3%) for progressive ascending aortic aneurysm. Freedom from aortic interventions at 10 and 15 years was 97 and 94%, respectively. No documented aortic dissection or rupture occurred. Freedom from adverse aortic events was 95% at 10 years and 93% at 15 years postoperatively. In a separate group of patients presenting with aortic insufficiency (i.e. root phenotype), freedom from adverse aortic events was significantly lower (88 and 70% at 10 and 15 years, P = 0.009). CONCLUSIONS: BAV patients with aortic valve stenosis and concomitant mild-to-moderate ascending aortic dilation are at a considerably low risk of adverse aortic events at 15 years after an isolated AVR. The BAV phenotype should be considered when determining the risk of subsequent adverse aortic events and the need for concomitant aortic replacement.