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BackgroundObjectiveMethodsResultsConclusionsFalls are a leading cause of severe injury and death in older adults. Remote screening of fall risk may prevent falls and hence, advance health and wellness of older adults. While remote health care is becoming a common practice, we question if remote evaluation of fall risk is as reliable as face-to-face (FTF).To assess the inter-tester reliability of synchronized remote and FTF fall risk assessment.This inter-format, inter-rater reliability study included 48 home dwelling older adults aged 65 and over. Five valid functional and balance tests were conducted: 30 Second Sit-to-Stand (STS), MiniBESTest, Timed up and go (TUG), 4-Meter Walk (4MWT), and Berg Balance Scale (BBS). Instructions were provided via videoconferencing, and two physiotherapists scored performance simultaneously, one remotely, and one in the room. Inter-rater reliability between remote and FTF scores was analyzed using intraclass correlation coefficient (ICC2,1), standard error of measurement (SEM), minimal detectable change (MDC95) and Bland and Altman analysis.Excellent ICCs were found for STS, MiniBESTest, TUG, and BBS (0.90–0.99), and moderate for 4MWT (0.74). SEM and MDC95 values were STS (0.37,1.03 repetitions), MiniBESTest (1.43,3.97 scores), TUG (1.22,3.37 seconds), 4MWT (0.17,0.47 m/second), and BBS (1.79,4.95 scores). The Bland and Altman analysis showed excellent agreement between remote and FTF assessments of the STS. All other tests showed low to moderate agreement. Mean difference ± SD and 95%LOA were as follows: STS (−0.11 ± 0.52), (−1.13,0.91) repetitions, MiniBESTest (0.45 ± 1.98), (−3.43,4.32) scores, TUG (−0.35 ± 1.54), (−3.37,2.67) seconds, 4MWT (−0.08 ± 0.22), (−0.35,0.51) meter/second, and BBS (0.04 ± 2.53), (−4.93,5.01) scores.The findings support the responsible integration of remote fall risk assessment in clinical practice, enabling large-scale screenings and referrals for early intervention to promote healthy aging and fall prevention. [ABSTRACT FROM AUTHOR]

This paper presents the design and initial learning research with the MMM modeling platform, seeking to advance middle school students' learning through constructing computational models of complex physical and chemical systems. A complexity-based structure of an MMM interface is introduced. It suggests that a complex system can be described and modeled by defining entities, their actions, interactions with each other, and interactions with their environment. MMM applies to a wide range of phenomena, targeting learning transfer and generalization. Design principles of MMM are presented and discussed based on a study with seventh-grade students. The study is a quasi-experimental, pretest-intervention-posttest control-comparison-group design. Findings from a quantitative analysis of the questionnaires show that engaging students with the construction of models using MMM significantly promoted students' conceptual learning and enhanced their systems' thinking compared with a comparison group who followed a normative curriculum. Students' responses to the worksheets showed mutual effects between improving the practice of modeling and promoting conceptual understanding and systems thinking. A qualitative analysis of screen-capture movies of one pair of students and their log files revealed that, in a later construction activity, their constructed models grew in sophistication and they articulated their thinking and learning in depth, using more sophisticated relationships between concepts. [ABSTRACT FROM AUTHOR]

RGB and depth cameras are extensively used for the 3D tracking of human pose and motion. Typically, these cameras calculate a set of 3D points representing the human body as a skeletal structure. The tracking capabilities of a single camera are often affected by noise and inaccuracies due to occluded body parts. Multiple-camera setups offer a solution to maximize coverage of the captured human body and to minimize occlusions. According to best practices, fusing information across multiple cameras typically requires spatio-temporal calibration. First, the cameras must synchronize their internal clocks. This is typically performed by physically connecting the cameras to each other using an external device or cable. Second, the pose of each camera relative to the other cameras must be calculated (Extrinsic Calibration). The state-of-the-art methods use specialized calibration session and devices such as a checkerboard to perform calibration. In this paper, we introduce an approach to the spatio-temporal calibration of multiple cameras which is designed to run on-the-fly without specialized devices or equipment requiring only the motion of the human body in the scene. As an example, the system is implemented and evaluated using Microsoft Azure Kinect. The study shows that the accuracy and robustness of this approach is on par with the state-of-the-art practices. [ABSTRACT FROM AUTHOR]

Modulation in sensory-perceptual processing is a known characteristic of autism, although the underlying mechanism is debated. A prevailing account is formulated in Bayesian terms, where either a reduced prior or reduced noise in the measurement (sensory input) may account for the modulated perception as expressed by the posterior distribution. However, research has shown that individuals with autism use priors in some conditions, and to the same extent as neurotypicals, while other studies fail to show enhanced sensory sensitivity in these individuals. We asked whether the modulated prior effects on perception may arise from non-adaptive relative weighting of priors to sensory reliability. We employed a Two-alternative forced choice (2AFC) width discrimination task, using the width–height illusion, which is based on a long-term acquired bias, where a taller rectangle is typically perceived as thinner than a shorter one. The measurement was manipulated by adding Gaussian blur on the vertical edges of the rectangles. Typically developed individuals displayed the expected increase in bias as a function of noise in the measurement. High-functioning individuals with autism exhibited typical perceptual resolutions and similar susceptibility to the illusion. However, the relative weighting of the perceptual bias and the sensory input differed in their effect on the two groups. Individuals with autism showed a non-adaptive, consistent bias across the different degrees of sensory noise, while typically developed individuals displayed monotonically increasing biases. Cluster analyses showed that this difference in the relative weighting between the groups was preserved regardless of the overall illusion magnitude displayed by individuals in each cluster. Unique perceptual skills and abnormalities in perception have been extensively demonstrated in those with autism for many perceptual domains, accounting, at least in part, for some of the main symptoms. Several new hypotheses suggest that perceptual representations in autism are unrefined, appear less constrained by exposure and regularities of the environment, and rely more on actual concrete input. Consistent with these emerging views, a bottom-up, data-driven fashion of processing has been suggested to account for the atypical perception in autism. It is yet unclear, however, whether reduced effects of prior knowledge and top-down information, or rather reduced noise in the sensory input, account for the often-reported bottom-up mode of processing in autism. We show that neither is sufficiently supported. Instead, we demonstrate clear differences between autistics and neurotypicals in how incoming input is weighted against prior knowledge and experience in determining the final percept. Importantly, the findings tap central differences in perception between those with and without autism that are consistent across identified sub-clusters within each group. [ABSTRACT FROM AUTHOR]

Although camera and sensor noise are often disregarded, assumed negligible or dealt with in the context of denoising, in this paper we show that significant information can actually be deduced from camera noise about the captured scene and the objects within it. Specifically, we deal with depth cameras and their noise patterns. We show that from sensor noise alone, the object's depth and location in the scene can be deduced. Sensor noise can indicate the source camera type, and within a camera type the specific device used to acquire the images. Furthermore, we show that noise distribution on surfaces provides information about the light direction within the scene as well as allows to distinguish between real and masked faces. Finally, we show that the size of depth shadows (missing depth data) is a function of the object's distance from the background, its distance from the camera and the object's size. Hence, can be used to authenticate objects location in the scene. This paper provides tools and insights into what can be learned from depth camera sensor noise. [ABSTRACT FROM AUTHOR]

Just as vocalization proceeds in a continuous stream in speech, so too do movements of the hands, face, and body in sign languages. Here, we use motion-capture technology to distinguish lexical signs in sign language from other common types of expression in the signing stream. One type of expression is constructed action, the enactment of (aspects of) referents and events by (parts of) the body. Another is classifier constructions, the manual representation of analogue and gradient motions and locations simultaneously with specified referent morphemes. The term signing is commonly used for all of these, but we show that not all visual signals in sign languages are of the same type. In this study of Israeli Sign Language, we use motion capture to show that the motion of lexical signs differs significantly along several kinematic parameters from that of the two other modes of expression: constructed action and the classifier forms. In so doing, we show how motion-capture technology can help to define the universal linguistic category "word," and to distinguish it from the expressive gestural elements that are commonly found across sign languages. [ABSTRACT FROM AUTHOR]

The authors introduce a novel marker-less multi-camera setup that allows easy synchronisation between 3D cameras as well as a novel pose estimation method that is calculated on the fly based on the human body being tracked, and thus requires no calibration session nor special calibration equipment. They show high accuracy in both calibration and data merging and is on par with equipment-based calibration. They deduce several insights and practical guidelines for the camera setup and for the preferred data merging methods. Finally, they present a test case that computerises the Fugl-Meyer stroke rehabilitation protocol using the authors' multi-sensor capture system. They conducted a Helsinki-approved research in a hospital in which they collected data on stroke patients and healthy subjects using their multi-camera system. Spatio-temporal features were extracted from the acquired data and machine learning-based evaluations were applied. Results showed that patients and healthy subjects can be correctly classified at a rate of above 90%. Furthermore, they show that the most significant features in the classification are strongly correlated with the Fugl-Meyer guidelines. This demonstrates the feasibility of a low-cost, flexible and non-invasive motion capture system that can potentially be operated in a home setting. [ABSTRACT FROM AUTHOR]

A fast pattern matching scheme termed matching by tone mapping (MTM) is introduced which allows matching under nonlinear tone mappings. We show that, when tone mapping is approximated by a piecewise constant/linear function, a fast computational scheme is possible requiring computational time similar to the fast implementation of normalized cross correlation (NCC). In fact, the MTM measure can be viewed as a generalization of the NCC for nonlinear mappings and actually reduces to NCC when mappings are restricted to be linear. We empirically show that the MTM is highly discriminative and robust to noise with comparable performance capability to that of the well performing mutual information, but on par with NCC in terms of computation time. [ABSTRACT FROM PUBLISHER]

new approach to detecting forgery in digital photographs is suggested. The method does not necessitate adding data to the image (such as a Digital Watermark) nor require other images for comparison or training. The fundamental assumption in the presented approach is the notion that image features arising from the image acquisition process itself or due to the physical structure and characteristics of digital cameras, are inherent proof of authenticity and they are sensitive to image manipulation as well as being difficult to forge synthetically. Typically, such features do not affect image content nor quality and are often invisible to the inexperienced eye. The approach presented in this work is based on the effects introduced in the acquired image by the optical and sensing systems of the camera. Specifically, it exploits image artifacts that are due to chromatic aberrations as indicators for evaluating image authenticity. [ABSTRACT FROM AUTHOR]

Abstract--Motion in modern video coders is estimated using a block matching algorithm that calculates the distance and direction of motion on a block-by-block basis. In this paper, a novel fast block-based motion estimation algorithm is proposed. This algorithm uses an efficient projection framework that bounds the distance between a template block and candidate blocks. Fast projection is performed using a family of highly efficient filter kernels-the gray-code kernels--requiring only 2 operations per pixel per kernel. The projection framework is combined with a rejection scheme which allows rapid rejection of candidate blocks that are distant from the template block. The tradeoff between computational complexity and quality of results can be easily controlled in the proposed algorithm; thus, it enables adaptivity to image content to further improve the results. Experiments show that the proposed adaptive algorithm outperforms other popular fast motion estimation algorithms. [ABSTRACT FROM AUTHOR]

A novel approach to pattern matching is presented in which time complexity is reduced by two orders of magnitude compared to traditional approaches. The suggested approach uses an efficient projection scheme which bounds the distance between a pattern and an image window using very few operations on average. The projection framework is combined with a rejection scheme which allows rapid rejection of image windows that are distant from the pattern. Experiments show that the approach is effective even under very noisy conditions. The approach described here can also be used in classification schemes where the projection values serve as input features that are informative and fast to extract. [ABSTRACT FROM AUTHOR]

Phonetic reduction arises in the course of typical language production, when language users produce a less clearly articulated form of a word. An important factor that affects phonetic reduction is the predictability of the information conveyed: predictable information is reduced. This can be observed in everyday use of reference in spoken language. Specifically, first mention of a referent is more carefully articulated than subsequent mentions of the same referents, which are often phonetically reduced. Here we ask whether phonetic reduction for predictable information exists in a young sign language, and, in particular, how phonetic reduction is realized in visual languages that exploit various articulators of the body: the hands, the head, and the torso. The only natural languages that we can observe as they emerge in real time are young sign languages, and we focus on one of these in the current study: Israeli Sign Language (ISL). We use 3D motion-capture technology to measure phonetic reduction in signers of ISL by comparing the production of referring expressions synchronically, at different points during a narrative (e.g., Introduction, Reintroduction, Maintenance). Our findings show: (a) that phonetic reduction is present in a young sign language; and specifically (b) that the actions of different articulators involved in discourse are reduced, based on predictability. We consider the importance of these findings in understanding predictability in language more generally. [ABSTRACT FROM AUTHOR]

Psychiatric evaluation of anxiety and depression is currently based on self-reported symptoms and their classification into discrete disorders. Yet the substantial overlap between these disorders as well as their within-disorder heterogeneity may contribute to the mediocre success rates of treatments. The proposed research examines a new framework for diagnosis that is based on alterations in underlying cognitive mechanisms. In line with the Research Domain Criteria (RDoC) approach, the current study directly compares disorder-specific and transdiagnostic cognitive patterns in predicting the severity of anxiety and depression symptoms. The sample included 237 individuals exhibiting differing levels of anxiety and depression symptoms, as measured by the STAI-T and BDI-II. Random Forest regressors were used to analyze their performance on a battery of six computerized cognitive-behavioral tests targeting selective and spatial attention, expectancy, interpretation, memory, and cognitive control biases. Unique anxiety-specific biases were found, as well as shared anxious-depressed bias patterns. These cognitive biases exhibited relatively high fitting rates when predicting symptom severity (questionnaire scores common range 0–60, MAE = 6.03, RMSE = 7.53). Interpretation and expectancy biases exhibited the highest association with symptoms, above all other individual biases. Although internal validation methods were applied, models may suffer from potential overfitting due to sample size limitations. In the context of the ongoing dispute regarding symptom-centered versus transdiagnostic approaches, the current study provides a unique comparison of these two views, yielding a novel intermediate approach. The results support the use of mechanism-based dimensional diagnosis for adding precision and objectivity to future psychiatric evaluations. • New framework for diagnosis, based on underlying cognitive mechanisms • Test battery measured six different cognitive biases for 237 participants. • Machine-learning algorithm predicted symptoms severity based on performance. • High fitting rates for prediction of transdiagnostic and disorder-specific symptoms • Endorsing intermediate approach bridging symptom-centred and transdiagnostic methods [ABSTRACT FROM AUTHOR]

AbstractObjective: Aspects of our emotional state are constantly being broadcast via our facial expressions. Psychotherapeutic theories highlight the importance of emotional dynamics between patients and therapists for an effective therapeutic relationship. Two emotional dynamics suggested by the literature are emotional reactivity (i.e., when one person is reacting to the other) and emotional stability (i.e., when a person has a tendency to remain in a given emotional state). Yet, little is known empirically about the association between these dynamics and the therapeutic alliance. This study investigates the association between the therapeutic alliance and the emotional dynamics of reactivity and stability, as manifested in the facial expressions of patients and therapists within the session. Methods: Ninety-four patients with major depressive disorder underwent short-term treatment for depression (N = 1256 sessions). Results: Both therapist reactivity and stability were associated with the alliance, across all time spans. Patient reactivity was associated with the alliance only in a short time span (1 s). Conclusions: These findings may potentially guide therapists in the field to attenuate not only their emotional reaction to their patients, but also their own unique presence in the therapy room. [ABSTRACT FROM AUTHOR]

Removal of shadows from a single image is a challenging problem. Producing a high-quality shadow-free image which is indistinguishable from a reproduction of a true shadow-free scene is even more difficult. Shadows in images are typically affected by several phenomena in the scene, including physical phenomena such as lighting conditions, type and behavior of shadowed surfaces, occluding objects, etc. Additionally, shadow regions may undergo postacquisition image processing transformations, e.g., contrast enhancement, which may introduce noticeable artifacts in the shadow-free images. We argue that the assumptions introduced in most studies arise from the complexity of the problem of shadow removal from a single image and limit the class of shadow images which can be handled by these methods. The purpose of this paper is twofold: First, it provides a comprehensive survey of the problems and challenges which may occur when removing shadows from a single image. In the second part of the paper, we present our framework for shadow removal, in which we attempt to overcome some of the fundamental problems described in the first part of the paper. Experimental results demonstrating the capabilities of our algorithm are presented. [ABSTRACT FROM PUBLISHER]

Is fluctuating asymmetry a reliable indicator of a population's state of adaptation? Does it respond in a predictable way to stress? How is it best employed by evolutionary biologists? To answer these questions, we studied leaf asymmetry of twelve species of vascular plants growing under contrasting microclimates on the opposing slopes of 'Evolution Canyon,' Nahal Oren, Mount Carmel, Israel. We applied similar sampling and measurement techniques to all 12 species, and used power transformations to correct for size scaling. Leaves of the trees Quercus calliprinos and Pistacia palaestina were significantly more asymmetrical on the microclimatically more fluctuating, drier, and savannah-like south-facing 'African' slope. Leaves of the shrub Calicotome villosa were significantly more asymmetrical on the microclimatically less variable, shadier, and maquis-like north-facing 'European' slope. Differences in fluctuating asymmetry were negatively correlated with differences in local abundance; species displayed higher fluctuating asymmetry on the slope where they were less abundant. The results obtained in the present study additionally suggest that the 'African' slope of 'Evolution Canyon' is only severely stressful for species on the margins of their adaptive zone. Similarly, the 'European' slope is only severely stressful for species on the margins of their, different, adaptive zone. Many plant species can adapt to both slopes. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2011, , 786-797. [ABSTRACT FROM AUTHOR]

Fluctuating asymmetry consists of random deviations from perfect symmetry in populations of organisms. It is a measure of developmental noise, which reflects a population's average state of adaptation and coadaptation. Moreover, it increases under both environmental and genetic stress, though responses are often inconsistent. Researchers base studies of fluctuating asymmetry upon deviations from bilateral, radial, rotational, dihedral, translational, helical, and fractal symmetries. Here, we review old and new methods of measuring fluctuating asymmetry, including measures of dispersion, landmark methods for shape asymmetry, and continuous symmetry measures. We also review the theory, developmental origins, and applications of fluctuating asymmetry, and attempt to explain conflicting results. In the process, we present examples from the literature, and from our own research at "Evolution Canyon" and elsewhere. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a new measure of symmetry for bifurcating structures, which relies not only on topology and ordering, but also on quantitative properties (e.g. length of branches). This measure is based on a specific biological mechanism and on the concept of minimum energy. The effectiveness of the approach is demonstrated in a classification test where leaves taken from plants growing under different stress conditions are classified. Results show that the proposed measure improves classification performance compared to classification based on other leading measures. [Copyright &y& Elsevier]

Unlike landmark methods for estimating object asymmetry, continuous symmetry measures (CSM) can be used to measure the symmetry distance (ds) of inconsistent objects, such as plant leaves. Inconsistent objects have no homologous landmarks, no consistent topology, no quantitative consistency, and sometimes no matching points. When CSM is used in conjugation with LAMINA Leaf Shape Determination software, one can quickly and efficiently process a large number of scanned leaves. LAMINA automatically generates equally-spaced points around the perimeter of each leaf and the resulting x-y coordinates are normalized to average centroid size prior to estimating ds using a fold, average, unfold algorithm. We estimated shape asymmetry of leaves of three species of flowering plants: Ligustrum sinense (Chinese Privet), Rubus cuneifolius (blackberry), and Perilla frutescens (Perilla), as well as individual leaves from a few species of oaks (Quercus) and maples (Acer). We found that 100 to 200 equally-spaced points worked well for all three of the main species. Measurement error accounted for a small proportion of the asymmetry variation. Nevertheless, measurement error was great enough to generate some negative size scaling after normalization to average centroid size. [ABSTRACT FROM AUTHOR]

Automating fall risk assessment, in an efficient, non-invasive manner, specifically in the elderly population, serves as an efficient means for implementing wide screening of individuals for fall risk and determining their need for participation in fall prevention programs. We present an automated and efficient system for fall risk assessment based on a multi-depth camera human motion tracking system, which captures patients performing the well-known and validated Berg Balance Scale (BBS). Trained machine learning classifiers predict the patient's 14 scores of the BBS by extracting spatio-temporal features from the captured human motion records. Additionally, we used machine learning tools to develop fall risk predictors that enable reducing the number of BBS tasks required to assess fall risk, from 14 to 4–6 tasks, without compromising the quality and accuracy of the BBS assessment. The reduced battery, termed Efficient-BBS (E-BBS), can be performed by physiotherapists in a traditional setting or deployed using our automated system, allowing an efficient and effective BBS evaluation. We report on a pilot study, run in a major hospital, including accuracy and statistical evaluations. We show the accuracy and confidence levels of the E-BBS, as well as the average number of BBS tasks required to reach the accuracy thresholds. The trained E-BBS system was shown to reduce the number of tasks in the BBS test by approximately 50% while maintaining 97% accuracy. The presented approach enables a wide screening of individuals for fall risk in a manner that does not require significant time or resources from the medical community. Furthermore, the technology and machine learning algorithms can be implemented on other batteries of medical tests and evaluations. [ABSTRACT FROM AUTHOR]

Most of the studies comparing facial expressions of born blind and sighted persons that have been carried out up until now have involved children as subjects. Various studies claimed that the quantity and quality of facial expressions of congenitally blind persons deteriorate with increasing age. Here, we compared facial expressions of born blind and sighted individuals using adults predominantly. Facial expressions were documented in an individual interview inducing such emotions as think-concentrate, sadness, anger, disgust, joy, and surprise.Common characteristics found amongst studied individuals were: similar repertoires* of movements over the entire interview, high-frequency and high-repertoire proportion of facial movements in concentration, sadness, and anger relative to those in disgust, joy, and surprise, similar distributions of a cumulative repertoire proportion of facial movements, and also common behavioral profiles of frequencies of facial movements in the emotional states discussed. Similar displays of eyebrow movements were found as well in concentration, sadness, and anger.Our study indicates that most tested characteristics of facial movements are common to born blind and sighted subjects, except for different cumulative mean frequencies in different emotional states, which is possibly related to the lack of visual feedback in born blind persons.Our study substantiates the hypothesis that facial expressions are innate and have important cues in the evolution of social communication. [ABSTRACT FROM AUTHOR]