Azadeh Kushki

Kernel-Based Positioning in Wireless Local Area Networks

The recent proliferation of location-based services (LBSs) has necessitated the development of effective indoor positioning solutions. In such a context, wireless local area network (WLAN) positioning is a particularly viable solution in terms of hardware and installation costs due to the ubiquity of WLAN infrastructures. This paper examines three aspects of the problem of indoor WLAN positioning using received signal strength (RSS). First, we show that, due to the variability of RSS features over space, a spatially localized positioning method leads to improved positioning results. Second, we explore the problem of access point (AP) selection for positioning and demonstrate the need for further research in this area. Third, we present a kernelized distance calculation algorithm for comparing RSS observations to RSS training records. Experimental results indicate that the proposed system leads to a 17 percent (0.56 m) improvement over the widely used K-nearest neighbor and histogram-based methods

Intranasal oxytocin versus placebo in the treatment of adults with autism spectrum disorders: a randomized controlled trial.

BackgroundThere are no effective medications for the treatment of social cognition/function deficits in autism spectrum disorder (ASD), and adult intervention literature in this area is sparse. Emerging data from animal models and genetic association studies as well as early, single-dose intervention studies suggest that the oxytocin system may be a potential therapeutic target for social cognition/function deficits in ASD. The primary aim of this study was to examine the safety/therapeutic effects of intranasal oxytocin versus placebo in adults with ASD, with respect to the two core symptom domains of social cognition/functioning and repetitive behaviors.MethodsThis was a pilot, randomized, double-blind, placebo-controlled, parallel design trial of intranasal oxytocin versus placebo in 19 adults with ASD (16 males; 33.20 ± 13.29 years). Subjects were randomized to 24 IU intranasal oxytocin or placebo in the morning and afternoon for 6 weeks. Measures of social function/cognition (the Diagnostic Analysis of Nonverbal Accuracy) and repetitive behaviors (Repetitive Behavior Scale Revised) were administered. Secondary measures included the Social Responsiveness Scale, Reading-the-Mind-in-the-Eyes Test and the Yale Brown Obsessive Compulsive Scale – compulsion subscale and quality of life (World Health Organization Quality of Life Questionnaire – emotional/social subscales). Full-information maximum-likelihood parameter estimates were obtained and tested using mixed-effects regression analyses.ResultsAlthough no significant changes were detected in the primary outcome measures after correcting for baseline differences, results suggested improvements after 6 weeks in measures of social cognition (Reading-the-Mind-in-the-Eyes Test, p = 0.002, d = 1.2), and quality of life (World Health Organization Quality of Life Questionnaire – emotion, p = 0.031, d = 0.84), both secondary measures. Oxytocin was well tolerated and no serious adverse effects were reported.ConclusionsThis pilot study suggests that there is therapeutic potential to daily administration of intranasal oxytocin in adults with ASD and that larger and longer studies are warranted.Trial registrationNCT00490802

Intelligent Dynamic Radio Tracking in Indoor Wireless Local Area Networks

Indoor positioning is an enabling technology for delivery of location-based services in mobile computing environments. This paper proposes a positioning solution using received signal strength in indoor wireless local area networks. In this application, an explicit measurement equation and the corresponding noise statistics are unknown because of the complexity of the indoor propagation channel. To address these challenges, we introduce a new state-space Bayesian filter: the nonparametric information (NI) filter. This filter effectively tracks motion in situations where the Kalman filter and its variants are inapplicable, while maintaining a computational complexity comparable to that of the Kalman filter. To deal with the noisy nature of the indoor propagation environment, the NI filter is used in the design of an intelligent dynamic WLAN tracking system. The system anticipates future position values and adapts its sensing and estimation parameters accordingly. Our experimental results conducted on measurements from a real office environment indicate that the combination of the intelligent design and the NI filter results in significant improvements over the Kalman and particle filters.

Handwriting Difficulties in Children with Autism Spectrum Disorders: A Scoping Review

Functional handwriting involves complex interactions among physical, cognitive and sensory systems. Impairments in many aspects of these systems are associated with Autism spectrum disorders (ASD), suggesting a heightened risk of handwriting difficulties in children with ASD. This scoping review aimed to: (1) survey the existing evidence about potential contributions to compromised handwriting function in children with ASD, and (2) map out the existing studies documenting handwriting difficulties in children with ASD. The current evidence implicates impairments in fine motor control and visual-motor integration as likely contributors to handwriting difficulties in children with ASD, though the role of the latter is not well-understood. Moreover, diminished overall legibility and compromised letter formation are emerging points of convergence among existing studies of handwriting quality in children with ASD.

Investigating the Autonomic Nervous System Response to Anxiety in Children with Autism Spectrum Disorders

Assessment of anxiety symptoms in autism spectrum disorders (ASD) is a challenging task due to the symptom overlap between the two conditions as well as the difficulties in communication and awareness of emotions in ASD. This motivates the development of a physiological marker of anxiety in ASD that is independent of language and does not require observation of overt behaviour. In this study, we investigated the feasibility of using indicators of autonomic nervous system (ANS) activity for this purpose. Specially, the objectives of the study were to 1) examine whether or not anxiety causes significant measurable changes in indicators of ANS in an ASD population, and 2) characterize the pattern of these changes in ASD. We measured three physiological indicators of the autonomic nervous system response (heart rate, electrodermal activity, and skin temperature) during a baseline (movie watching) and anxiety condition (Stroop task) in a sample of typically developing children (n = 17) and children with ASD (n = 12). The anxiety condition caused significant changes in heart rate and electrodermal activity in both groups, however, a differential pattern of response was found between the two groups. In particular, the ASD group showed elevated heart rate during both baseline and anxiety conditions. Elevated and blunted phasic electrodermal activity were found in the ASD group during baseline and anxiety conditions, respectively. Finally, the ASD group did not show the typical decrease in skin temperature in response to anxiety. These results suggest that 1) signals of the autonomic nervous system may be used as indicators of anxiety in children with ASD, and 2) ASD may be associated with an atypical autonomic response to anxiety that is most consistent with sympathetic over-arousal and parasympathetic under-arousal.

A Review of EEG-Based Brain-Computer Interfaces as Access Pathways for Individuals with Severe Disabilities

Electroencephalography (EEG) is a non-invasive method for measuring brain activity and is a strong candidate for brain-computer interface (BCI) development. While BCIs can be used as a means of communication for individuals with severe disabilities, the majority of existing studies have reported BCI evaluations by able-bodied individuals. Considering the many differences in body functions and usage scenarios between individuals with disabilities and able-bodied individuals, involvement of the target population in BCI evaluation is necessary. In this review, 39 studies reporting EEG-oriented BCI assessment by individuals with disabilities were identified in the past decade. With respect to participant populations, a need for assessing BCI performance for the pediatric population with severe disabilities was identified as an important future direction. Acquiring a reliable communication pathway during early stages of development is crucial in avoiding learned helplessness in pediatric-onset disabilities. With respect to evaluation, augmenting traditional measures of system performance with those relating to contextual factors was recommended for realizing user-centered designs appropriate for integration in real-life. Considering indicators of user state and developing more effective training paradigms are recommended for future studies of BCI involving individuals with disabilities.

Intersession Consistency of Single-Trial Classification of the Prefrontal Response to Mental Arithmetic and the No-Control State by NIRS

Near-infrared spectroscopy (NIRS) has been recently investigated for use in noninvasive brain-computer interface (BCI) technologies. Previous studies have demonstrated the ability to classify patterns of neural activation associated with different mental tasks (e.g., mental arithmetic) using NIRS signals. Though these studies represent an important step towards the realization of an NIRS-BCI, there is a paucity of literature regarding the consistency of these responses, and the ability to classify them on a single-trial basis, over multiple sessions. This is important when moving out of an experimental context toward a practical system, where performance must be maintained over longer periods. When considering response consistency across sessions, two questions arise: 1) can the hemodynamic response to the activation task be distinguished from a baseline (or other task) condition, consistently across sessions, and if so, 2) are the spatiotemporal characteristics of the response which best distinguish it from the baseline (or other task) condition consistent across sessions. The answers will have implications for the viability of an NIRS-BCI system, and the design strategies (especially in terms of classifier training protocols) adopted. In this study, we investigated the consistency of classification of a mental arithmetic task and a no-control condition over five experimental sessions. Mixed model linear regression on intrasession classification accuracies indicate that the task and baseline states remain differentiable across multiple sessions, with no significant decrease in accuracy (p = 0.67). Intersession analysis, however, revealed inconsistencies in spatiotemporal response characteristics. Based on these results, we investigated several different practical classifier training protocols, including scenarios in which the training and test data come from 1) different sessions, 2) the same session, and 3) a combination of both. Results indicate that when selecting optimal classifier training protocols for NIRS-BCI, a compromise between accuracy and convenience (e.g., in terms of duration/frequency of training data collection) must be considered.

Query feedback for interactive image retrieval

From a perceptual standpoint, the subjectivity inherent in understanding and interpreting visual content in multimedia indexing and retrieval motivates the need for online interactive learning. Since efficiency and speed are important factors in interactive visual content retrieval, most of the current approaches impose restrictive assumptions on similarity calculation and learning algorithms. Specifically, content-based image retrieval techniques generally assume that perceptually similar images are situated close to each other within a connected region of a given space of visual features. This paper proposes a novel method for interactive image retrieval using query feedback. Query feedback learns the user query as well as the correspondence between high-level user concepts and their low-level machine representation by performing retrievals according to multiple queries supplied by the user during the course of a retrieval session. The results presented in this paper demonstrate that this algorithm provides accurate retrieval results with acceptable interaction speed compared to existing methods.

Changes in Kinetics and Kinematics of Handwriting during a Prolonged Writing Task in Children with and without Dysgraphia.

Handwriting difficulties or dysgraphia have a profound impact on childrens psychosocial development, and yet, 10-30% of school-aged children are reported to experience difficulties mastering this skill. Several studies have examined the nature and biomechanical underpinnings of handwriting difficulties in children with and without dysgraphia. While the majority of these studies have considered short handwriting activities involving a sentence or a paragraph, handwriting quality and speed are reported to vary with the length of the writing task. Further, it is suggested that the biomechanics of handwriting also evolve over extended writing periods, and that these changes may be distinct between children with and without dysgraphia. The nature and specificity of these biomechanical alterations remain unknown. To address this knowledge gap, we examined changes in writing speed, grip forces on the pen barrel, and normal forces on the writing surface, over the course of a 10-min writing task, in a large cohort of 4th grade children with and without dysgraphia. Horizontal stroke speed, grip force and normal force increased over time while vertical stroke speed decreased in all children. These biomechanical changes may be attributable to physical and psychological fatigue and the corresponding compensatory processes invoked by the motor system.

Retrieval of images from artistic repositories using a decision fusion framework

The large volumes of artistic visual data available to museums, art galleries, and online collections motivate the need for effective means to retrieve :relevant information from such repositories. The paper proposes a decision making framework for content-based retrieval of art images based on a combination of low-level features. Traditionally, the similarity between two images has been calculated as a weighted distance between two feature vectors. This approach, however, may not be mathematically and computationally appropriate, and does not provide enough flexibility in modeling user queries. The paper proposes a framework that generalizes a wide set of previous approaches to similarity calculation, including the weighted distance approach. Image similarities are obtained through a decision making process based on low-level feature distances using fuzzy theory. The analysis and results indicate that the presented aggregation technique provides an effective, general, and flexible tool for similarity calculation based on the combination of individual descriptors and features.