Simultaneous registration of ECG and cardiac motion by a single esophageal probe

Long-term surface ECG is routinely used to diagnose paroxysmal arrhythmias. However, this method only provides information about the heart's electrical activity. To this end, we investigated a novel esophageal catheter that features synchronous esophageal ECG and acceleration measurements, the latter being a record of the heart's mechanical activity. The acceleration data were quantified in a small study and successfully linked to the activity sequences of the heart in all subjects. The acceleration signals were additionally transformed into motion. The extracted cardiac motion was proved to be a valid reference input for an adaptive filter capable of removing relevant baseline wandering in the recorded esophageal ECGs. Taking both capabilities into account, the proposed recorder might be a promising tool for future long-term heart monitoring.

Food Volume Computation for Self Dietary Assessment Applications

There is great demand for easily-accessible, user-friendly dietary self-management applications. Yet accurate, fully-automatic estimation of nutritional intake using computer vision methods remains an open research problem. One key element of this problem is the volume estimation, which can be computed from 3D models obtained using multi-view geometry. The paper presents a computational system for volume estimation based on the processing of two meal images. A 3D model of the served meal is reconstructed using the acquired images and the volume is computed from the shape. The algorithm was tested on food models (dummy foods) with known volume and on real served food. Volume accuracy was in the order of 90 %, while the total execution time was below 15 seconds per image pair. The proposed system combines simple and computational affordable methods for 3D reconstruction, remained stable throughout the experiments, operates in near real time, and places minimum constraints on users.

Being Moved by the Self and Others: Influence of Empathy on Self-Motion Perception

BACKGROUND: The observation of conspecifics influences our bodily perceptions and actions: Contagious yawning, contagious itching, or empathy for pain, are all examples of mechanisms based on resonance between our own body and others. While there is evidence for the involvement of the mirror neuron system in the processing of motor, auditory and tactile information, it has not yet been associated with the perception of self-motion. METHODOLOGY/PRINCIPAL FINDINGS: We investigated whether viewing our own body, the body of another, and an object in motion influences self-motion perception. We found a visual-vestibular congruency effect for self-motion perception when observing self and object motion, and a reduction in this effect when observing someone else's body motion. The congruency effect was correlated with empathy scores, revealing the importance of empathy in mirroring mechanisms. CONCLUSIONS/SIGNIFICANCE: The data show that vestibular perception is modulated by agent-specific mirroring mechanisms. The observation of conspecifics in motion is an essential component of social life, and self-motion perception is crucial for the distinction between the self and the other. Finally, our results hint at the presence of a "vestibular mirror neuron system".

Perceptual learning of motion discrimination by mental imagery.

Perceptual learning can occur when stimuli are only imagined, i.e., without proper stimulus presentation. For example, perceptual learning improved bisection discrimination when only the two outer lines of the bisection stimulus were presented and the central line had to be imagined. Performance improved also with other static stimuli. In non-learning imagery experiments, imagining static stimuli is different from imagining motion stimuli. We hypothesized that those differences also affect imagery perceptual learning. Here, we show that imagery training also improves motion direction discrimination. Learning occurs when no stimulus at all is presented during training, whereas no learning occurs when only noise is presented. The interference between noise and mental imagery possibly hinders learning. For static bisection stimuli, the pattern is just the opposite. Learning occurs when presented with the two outer lines of the bisection stimulus, i.e., with only a part of the visual stimulus, while no learning occurs when no stimulus at all is presented.

Part two: Against the motion. External diameter for AAA size

Aneurysm diameter measurement is quick and easy, but suffers from the pitfalls of being "too rough and ready". When semi-automated segmentation took 7-10 minutes to estimate volume, it was not a practical tool for busy, routine clinical practice. Today, the availability of automatic segmentation in seconds is bound to make volume measurement, along with 3D ultrasonography, the tools of the future. There can be no debate.

Modulation of orientation-selective neurons by motion: when additive, when multiplicative?

The recurrent interaction among orientation-selective neurons in the primary visual cortex (V1) is suited to enhance contours in a noisy visual scene. Motion is known to have a strong pop-up effect in perceiving contours, but how motion-sensitive neurons in V1 support contour detection remains vastly elusive. Here we suggest how the various types of motion-sensitive neurons observed in V1 should be wired together in a micro-circuitry to optimally extract contours in the visual scene. Motion-sensitive neurons can be selective about the direction of motion occurring at some spot or respond equally to all directions (pandirectional). We show that, in the light of figure-ground segregation, direction-selective motion neurons should additively modulate the corresponding orientation-selective neurons with preferred orientation orthogonal to the motion direction. In turn, to maximally enhance contours, pandirectional motion neurons should multiplicatively modulate all orientation-selective neurons with co-localized receptive fields. This multiplicative modulation amplifies the local V1-circuitry among co-aligned orientation-selective neurons for detecting elongated contours. We suggest that the additive modulation by direction-specific motion neurons is achieved through synaptic projections to the somatic region, and the multiplicative modulation by pandirectional motion neurons through projections to the apical region of orientation-specific pyramidal neurons. For the purpose of contour detection, the V1-intrinsic integration of motion information is advantageous over a downstream integration as it exploits the recurrent V1-circuitry designed for that task.

Sparse computation for large-scale binary classification

Well-known data mining algorithms rely on inputs in the form of pairwise similarities between objects. For large datasets it is computationally impossible to perform all pairwise comparisons. We therefore propose a novel approach that uses approximate Principal Component Analysis to efficiently identify groups of similar objects. The effectiveness of the approach is demonstrated in the context of binary classification using the supervised normalized cut as a classifier. For large datasets from the UCI repository, the approach significantly improves run times with minimal loss in accuracy.

Psychological Data from an Exploration of the Rapport / Synchrony Interplay Using Motion Energy Analysis

These data result from an investigation examining the interplay between dyadic rapport and consequential behavior-mirroring. Participants responded to a variety of interpersonally-focused pretest measures prior to their engagement in videotaped interdependent tasks (coded for interactional synchrony using Motion Energy Analysis [17,18]). A post-task evaluation of rapport and other related constructs followed each exchange. Four studies shared these same dependent measures, but asked distinct questions: Study 1 (Ndyad = 38) explored the influence of perceived responsibility and gender-specificity of the task; Study 2 (Ndyad = 51) focused on dyad sex-makeup; Studies 3 (Ndyad = 41) and 4 (Ndyad = 63) examined cognitive load impacts on the interactions. Versions of the data are structured with both individual and dyad as the unit of analysis. Our data possess strong reuse potential for theorists interested in dyadic processes and are especially pertinent to questions about dyad agreement and interpersonal perception / behavior association relationships.

SLR-GNSS analysis in the framework of the ITRF2013 computation

Pre-combined SLR-GNSS solutions are studied and the impact of different types of datum definition on the estimated parameters is assessed. It is found that the origin is realized best by using only the SLR core network for defining the geodetic datum and the inclusion of the GNSS core sites degrades the origin. The orientation, however, requires a dense and continuous network, thus, the inclusion of the GNSS core network is absolutely needed.