Hip strategy for balance control in quiet standing is reduced in people with low back pain

Study Design. Quiet stance on supporting bases with different lengths and with different visual inputs were tested in 24 study participants with chronic low back pain (LBP) and 24 matched control subjects. Objectives. To evaluate postural adjustment strategies and visual dependence associated with LBP. Summary of Background Data. Various studies have identified balance impairments in patients with chronic LBP, with many possible causes suggested. Recent evidence indicates that study participants with LBP have impaired trunk muscle control, which may compromise the control of trunk and hip movement during postural adjustments ( e. g., hip strategy). As balance on a short base emphasizes the utilization of the hip strategy for balance control, we hypothesized that patients with LBP might have difficulties standing on short bases. Methods. Subjects stood on either flat surface or short base with different visual inputs. A task was counted as successful if balance was maintained for 70 seconds during bilateral stance and 30 seconds during unilateral stance. The number of successful tasks, horizontal shear force, and center-of-pressure motion were evaluated. Results. The hip strategy was reduced with increased visual dependence in study participants with LBP. The failure rate was more than 4 times that of the controls in the bilateral standing task on short base with eyes closed. Analysis of center-of-pressure motion also showed that they have inability to initiate and control a hip strategy. Conclusions. The inability to control a hip strategy indicates a deficit of postural control and is hypothesized to result from altered muscle control and proprioceptive impairment.

The relative contributions of colour and luminance signals towards the visuomotor localisation of targets in human peripheral vision

We sought to determine the extent to which colour (and luminance) signals contribute towards the visuomotor localization of targets. To do so we exploited the movement-related illusory displacement a small stationary window undergoes when it has a continuously moving carrier grating behind it. We used drifting (1.0-4.2 Hz) red/green-modulated isoluminant gratings or yellow/black luminance-modulated gratings as carriers, each curtailed in space by a stationary, two-dimensional window. After each trial, the perceived location of the window was recorded with reference to an on-screen ruler (perceptual task) or the on-screen touch of a ballistic pointing movement made without visual feedback (visuomotor task). Our results showed that the perceptual displacement measures were similar for each stimulus type and weakly dependent on stimulus drift rate. However, while the visuomotor displacement measures were similar for each stimulus type at low drift rates (<4 Hz), they were significantly larger for luminance than colour stimuli at high drift rates (>4 Hz). We show that the latter cannot be attributed to differences in perceived speed between stimulus types. We assume, therefore, that our visuomotor localization judgements were more susceptible to the (carrier) motion of luminance patterns than colour patterns. We suggest that, far from being detrimental, this susceptibility may indicate the operation of mechanisms designed to counter the temporal asynchrony between perceptual experiences and the physical changes in the environment that give rise to them. We propose that perceptual localisation is equally supported by both colour and luminance signals but that visuomotor localisation is predominantly supported by luminance signals. We discuss the neural pathways that may be involved with visuomotor localization. © 2007 Springer-Verlag.

Benefits of electronic vision enhancement systems (EVES) for the visually impaired

PURPOSE: To examine whether objective performance of near tasks is improved with various electronic vision enhancement systems (EVES) compared with the subject's own optical magnifier. DESIGN: Experimental study, randomized, within-patient design. METHODS: This was a prospective study, conducted in a hospital ophthalmology low-vision clinic. The patient population comprised 70 sequential visually impaired subjects. The magnifying devices examined were: patient's optimum optical magnifier; magnification and field-of-view matched mouse EVES with monitor or head-mounted display (HMD) viewing; and stand EVES with monitor viewing. The tasks performed were: reading speed and acuity; time taken to track from one column of print to the next; follow a route map, and locate a specific feature; and identification of specific information from a medicine label. RESULTS: Mouse EVES with HMD viewing caused lower reading speeds than stand EVES with monitor viewing (F = 38.7, P < .001). Reading with the optical magnifier was slower than with the mouse or stand EVES with monitor viewing at smaller print sizes (P < .05). The column location task was faster with the optical magnifier than with any of the EVES (F = 10.3, P < .001). The map tracking and medicine label identification task was slower with the mouse EVES with HMD viewing than with the other magnifiers (P < .01). Previous EVES experience had no effect on task performance (P > .05), but subjects with previous optical magnifier experience were significantly slower at performing the medicine label identification task with all of the EVES (P < .05). CONCLUSIONS: Although EVES provide objective benefits to the visually impaired in reading speed and acuity, together with some specific near tasks, some can be performed just as fast using optical magnification. © 2003 by Elsevier Inc. All rights reserved.

Memory conformity: Actors and bystanders

This dissertation explored memory conformity effects on people who interacted with a confederate and of bystanders to that interaction. Two studies were carried out. Study 1 was conducted in the field. A male confederate approached a group of people at the beach and had a brief interaction. About a minute later a research assistant approached the group and administered a target-absent lineup to each person in the group. Analyses revealed that memory conformity occurred during the lineup task. Bystanders were twice as likely to conform as those who interacted with the confederate. Study 2 was carried out in a laboratory under controlled conditions. Participants were exposed to two events during their time in the laboratory. In one event, participants were shown a brief video with no determinate roles assigned. In the other event participants were randomly assigned to interact with a confederate (actor condition) or to witness that interaction (bystander condition). Participants were given memory tests on both events to understand the effects of participant role (actor vs. bystander) on memory conformity. Participants answered second to all questions, following a confederate acting as a participant, who disseminated misinformation on critical questions. Analyses revealed no significant differences in memory conformity between actors and bystanders during the movie memory task. However, differences were found for the interaction memory task such that bystanders conformed more than actors on two of four critical questions. Bystanders also conformed more than actors during a lineup identification task. The results of these studies suggest that the role a person plays in an interaction affects how susceptible they are to information from a co-witness. Theoretical and applied implications are discussed. First, the results are explained through the use of two models of memory. Second, recommendations are made for forensic investigators.

Fragilariopsis kerguelensis images from sediment core PS1768-8

Background: Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and / or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists. Results: The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of object outlines, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results. Special attention was given to ease of use, applicability to a broad range of data and problems, and supporting high throughput analyses with minimal manual intervention. Conclusions: Tested with several diatom datasets from different sources and of various compositions, SHERPA proved its ability to successfully analyze large amounts of diatom micrographs depicting a broad range of species. SHERPA is unique in combining the following features: application of multiple segmentation methods and selection of the one giving the best result for each individual object; identification of shapes of interest based on outline matching against a template library; quality scoring and ranking of resulting outlines supporting quick quality checking; extraction of a wide range of outline shape descriptors widely used in diatom studies and elsewhere; minimizing the need for, but enabling manual quality control and corrections. Although primarily developed for analyzing images of diatom valves originating from automated microscopy, SHERPA can also be useful for other object detection, segmentation and outline-based identification problems.

Adaptive Brain-Computer Interface Systems For Communication in People with Severe Neuromuscular Disabilities

Brain-computer interfaces (BCI) have the potential to restore communication or control abilities in individuals with severe neuromuscular limitations, such as those with amyotrophic lateral sclerosis (ALS). The role of a BCI is to extract and decode relevant information that conveys a user's intent directly from brain electro-physiological signals and translate this information into executable commands to control external devices. However, the BCI decision-making process is error-prone due to noisy electro-physiological data, representing the classic problem of efficiently transmitting and receiving information via a noisy communication channel.

This research focuses on P300-based BCIs which rely predominantly on event-related potentials (ERP) that are elicited as a function of a user's uncertainty regarding stimulus events, in either an acoustic or a visual oddball recognition task. The P300-based BCI system enables users to communicate messages from a set of choices by selecting a target character or icon that conveys a desired intent or action. P300-based BCIs have been widely researched as a communication alternative, especially in individuals with ALS who represent a target BCI user population. For the P300-based BCI, repeated data measurements are required to enhance the low signal-to-noise ratio of the elicited ERPs embedded in electroencephalography (EEG) data, in order to improve the accuracy of the target character estimation process. As a result, BCIs have relatively slower speeds when compared to other commercial assistive communication devices, and this limits BCI adoption by their target user population. The goal of this research is to develop algorithms that take into account the physical limitations of the target BCI population to improve the efficiency of ERP-based spellers for real-world communication.

In this work, it is hypothesised that building adaptive capabilities into the BCI framework can potentially give the BCI system the flexibility to improve performance by adjusting system parameters in response to changing user inputs. The research in this work addresses three potential areas for improvement within the P300 speller framework: information optimisation, target character estimation and error correction. The visual interface and its operation control the method by which the ERPs are elicited through the presentation of stimulus events. The parameters of the stimulus presentation paradigm can be modified to modulate and enhance the elicited ERPs. A new stimulus presentation paradigm is developed in order to maximise the information content that is presented to the user by tuning stimulus paradigm parameters to positively affect performance. Internally, the BCI system determines the amount of data to collect and the method by which these data are processed to estimate the user's target character. Algorithms that exploit language information are developed to enhance the target character estimation process and to correct erroneous BCI selections. In addition, a new model-based method to predict BCI performance is developed, an approach which is independent of stimulus presentation paradigm and accounts for dynamic data collection. The studies presented in this work provide evidence that the proposed methods for incorporating adaptive strategies in the three areas have the potential to significantly improve BCI communication rates, and the proposed method for predicting BCI performance provides a reliable means to pre-assess BCI performance without extensive online testing.

Using Image Processing Methods to Improve the Detection of Buried Explosive Threats in GPR Data

Current state of the art techniques for landmine detection in ground penetrating radar (GPR) utilize statistical methods to identify characteristics of a landmine response. This research makes use of 2-D slices of data in which subsurface landmine responses have hyperbolic shapes. Various methods from the field of visual image processing are adapted to the 2-D GPR data, producing superior landmine detection results. This research goes on to develop a physics-based GPR augmentation method motivated by current advances in visual object detection. This GPR specific augmentation is used to mitigate issues caused by insufficient training sets. This work shows that augmentation improves detection performance under training conditions that are normally very difficult. Finally, this work introduces the use of convolutional neural networks as a method to learn feature extraction parameters. These learned convolutional features outperform hand-designed features in GPR detection tasks. This work presents a number of methods, both borrowed from and motivated by the substantial work in visual image processing. The methods developed and presented in this work show an improvement in overall detection performance and introduce a method to improve the robustness of statistical classification.

MINDREADING: INTROVERSION VERSUS EXTRAVERSION

Theory of mind (also called ‘mindreading’), is the ability to explain and predict others’ behaviour by inferring their mental states, such as their knowledge, beliefs, perceptions and desires. One largely unexplored question in theory of mind research is the relationship between personality and theory of mind abilities in adults. The current study investigated introverts’ and extraverts’ performance on two theory of mind tasks: one task involved judging emotional states from pictures of eyes (RMTE task), and the other involved making judgments about one’s own and others’ visual perspective (AVP task). In both tasks, the personal relevance of the situation was varied to examine whether this factor would differentially affect the performance of introverts and extraverts. There was a significant interaction between personality (introvert vs. extravert) and condition (personal vs. impersonal) in the AVP task, with extraverts performing better in the personal than in the impersonal condition but introverts performing the same in both conditions. In the RMTE task there was no interaction, as all participants performed better in the personal condition regardless of personality. There was also a main effect of personality in the RMTE, with introverts performing better overall than extraverts at judging emotions from eyes. Possible reasons behind these and other observed differences are discussed.

Tinta Barroca: identidade e comunicação para uma marca de promoção de eventos hoteleiros

A ilustração aplicada ao branding resulta de um modo reflexivo por parte do autor. Esse modo é, por si só, o papel do ilustrador como designer gráfico. A identidade de uma marca nasce da sua história, contexto e sensações, as quais o autor adquire e transmite, segundo as suas vivências, de modo a responder às necessidades das pessoas que o rodeiam. O desenvolvimento de uma marca é um longo processo de análise e reflexão, contínuo e exigente. Aplicando a ilustração a este meio, como objeto visual principal, a língua deixa de ser um entrave e a identidade passa a ser comunicada aos olhos e memória de qualquer um, de forma imediata e eficaz. Conceptualmente, a Tinta Barroca absorve estes princípios, transformando-se numa marca de eventos culturais, embora bastante focada em eventos que podem abranger jantares bem portugueses ou provas de vinho. O projeto foi desenvolvido à base do experimentalismo. Todas as ilustrações da marca foram, numa primeira fase, produzidas manualmente e posteriormente tratadas digitalmente, testando diferentes formas, texturas e materiais. A excessividade ilustrativa é o ponto de partida para comunicar as ideologias da Tinta Barroca, baseando-se no barroquismo, erotismo e nos prazeres da vida. A identidade gráfica da marca misturase com uma decoração já pré-definida: uma mesa bem preenchida e recheada de flores, frutos, vinho e comidas divinais, que se aproximam, pelo excesso, dos princípios do barroco.

Hand detection on images based on deformable part models and additional features

Hand detection on images has important applications on person activities recognition. This thesis focuses on PASCAL Visual Object Classes (VOC) system for hand detection. VOC has become a popular system for object detection, based on twenty common objects, and has been released with a successful deformable parts model in VOC2007. A hand detection on an image is made when the system gets a bounding box which overlaps with at least 50% of any ground truth bounding box for a hand on the image. The initial average precision of this detector is around 0.215 compared with a state-of-art of 0.104; however, color and frequency features for detected bounding boxes contain important information for re-scoring, and the average precision can be improved to 0.218 with these features. Results show that these features help on getting higher precision for low recall, even though the average precision is similar.

Action and perception: Neural indices of learning in infants

Early human development offers a unique perspective in investigating the potential cognitive and social implications of action and perception. Specifically, during infancy, action production and action perception undergo foundational developments. One essential component to examine developments in action processing is the analysis of others’ actions as meaningful and goal-directed. Little research, however, has examined the underlying neural systems that may be associated with emerging action and perception abilities, and infants’ learning of goal-directed actions. The current study examines the mu rhythm—a brain oscillation found in the electroencephalogram (EEG)—that has been associated with action and perception. Specifically, the present work investigates whether the mu signal is related to 9-month-olds’ learning of a novel goal-directed means-end task. The findings of this study demonstrate a relation between variations in mu rhythm activity and infants’ ability to learn a novel goal-directed means-end action task (compared to a visual pattern learning task used as a comparison task). Additionally, we examined the relations between standardized assessments of early motor competence, infants’ ability to learn a novel goal-directed task, and mu rhythm activity. We found that: 1a) mu rhythm activity during observation of a grasp uniquely predicted infants’ learning on the cane training task, 1b) mu rhythm activity during observation and execution of a grasp did not uniquely predict infants’ learning on the visual pattern learning task (comparison learning task), 2) infants’ motor competence did not predict infants’ learning on the cane training task, 3) mu rhythm activity during observation and execution was not related to infants’ measure of motor competence, and 4) mu rhythm activity did not predict infants’ learning on the cane task above and beyond infants’ motor competence. The results from this study demonstrate that mu rhythm activity is a sensitive measure to detect individual differences in infants’ action and perception abilities, specifically their learning of a novel goal-directed action.

Identificazione e classificazione delle lesioni endocavitarie uterine dalle immagini isteroscopiche con il deep learning

Anche se l'isteroscopia con la biopsia endometriale è il gold standard nella diagnosi della patologia intracavitaria uterina, l'esperienza dell’isteroscopista è fondamentale per una diagnosi corretta. Il Deep Learning (DL) come metodica di intelligenza artificiale potrebbe essere un aiuto per superare questo limite. Sono disponibili pochi studi con risultati preliminari e mancano ricerche che valutano le prestazioni dei modelli di DL nell'identificazione delle lesioni intrauterine e il possibile aiuto derivato dai fattori clinici. Obiettivo: Sviluppare un modello di DL per identificare e classificare le patologie endocavitarie uterine dalle immagini isteroscopiche. Metodi: È stato eseguito uno studio di coorte retrospettivo osservazionale monocentrico su una serie consecutiva di casi isteroscopici di pazienti con patologia intracavitaria uterina confermata all’esame istologico eseguiti al Policlinico S. Orsola. Le immagini isteroscopiche sono state usate per costruire un modello di DL per la classificazione e l'identificazione delle lesioni intracavitarie con e senza l'aiuto di fattori clinici (età, menopausa, AUB, terapia ormonale e tamoxifene). Come risultati dello studio abbiamo calcolato le metriche diagnostiche del modello di DL nella classificazione e identificazione delle lesioni uterine intracavitarie con e senza l'aiuto dei fattori clinici. Risultati: Abbiamo esaminato 1.500 immagini provenienti da 266 casi: 186 pazienti avevano lesioni focali benigne, 25 lesioni diffuse benigne e 55 lesioni preneoplastiche/neoplastiche. Sia per quanto riguarda la classificazione che l’identificazione, le migliori prestazioni sono state raggiunte con l'aiuto dei fattori clinici, complessivamente con precision dell'80,11%, recall dell'80,11%, specificità del 90,06%, F1 score dell’80,11% e accuratezza dell’86,74% per la classificazione. Per l’identificazione abbiamo ottenuto un rilevamento complessivo dell’85,82%, precision 93,12%, recall del 91,63% ed F1 score del 92,37%. Conclusioni: Il modello DL ha ottenuto una bassa performance nell’identificazione e classificazione delle lesioni intracavitarie uterine dalle immagini isteroscopiche. Anche se la migliore performance diagnostica è stata ottenuta con l’aiuto di fattori clinici specifici, questo miglioramento è stato scarso.

Biologically motivated model for object detection and identification in real-world scenes

The classical computer vision methods can only weakly emulate some of the multi-level parallelisms in signal processing and information sharing that takes place in different parts of the primates’ visual system thus enabling it to accomplish many diverse functions of visual perception. One of the main functions of the primates’ vision is to detect and recognise objects in natural scenes despite all the linear and non-linear variations of the objects and their environment. The superior performance of the primates’ visual system compared to what machine vision systems have been able to achieve to date, motivates scientists and researchers to further explore this area in pursuit of more efficient vision systems inspired by natural models. In this paper building blocks for a hierarchical efficient object recognition model are proposed. Incorporating the attention-based processing would lead to a system that will process the visual data in a non-linear way focusing only on the regions of interest and hence reducing the time to achieve real-time performance. Further, it is suggested to modify the visual cortex model for recognizing objects by adding non-linearities in the ventral path consistent with earlier discoveries as reported by researchers in the neuro-physiology of vision.

Robust abandoned object detection integrating wide area visual surveillance and social context

This paper presents a video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes. The framework is based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects. Implementation is achieved through development of a logic-based inference engine based on Prolog. Threat detection performance is conducted by testing against a range of datasets describing realistic situations and demonstrates a reduction in the number of false alarms generated. The proposed system represents the approach employed in the EU SUBITO project (Surveillance of Unattended Baggage and the Identification and Tracking of the Owner).

3D Object following based on visual information for Unmanned Aerial Vehicles

This article presents a novel system and a control strategy for visual following of a 3D moving object by an Unmanned Aerial Vehicle UAV. The presented strategy is based only on the visual information given by an adaptive tracking method based on the color information, which jointly with the dynamics of a camera fixed to a rotary wind UAV are used to develop an Image-based visual servoing IBVS system. This system is focused on continuously following a 3D moving target object, maintaining it with a fixed distance and centered on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation