On the incremental learning and recognition of the pattern of movement of multiple labelled objects in dynamic scenes

In this paper we discuss combining incremental learning and incremental recognition to classify patterns consisting of multiple objects, each represented by multiple spatio-temporal features. Importantly the technique allows for ambiguity in terms of the positions of the start and finish of the pattern. This involves a progressive classification which considers the data at each time instance in the query and thus provides a probable answer before all the query information becomes available. We present two methods that combine incremental learning and incremental recognition: a time instance method and an overall best match method.

Learning people movement model from multiple cameras for behaviour recognition

In surveillance systems for monitoring people behaviours, it is important to build systems that can adapt to the signatures of people's tasks and movements in the environment. At the same time, it is important to cope with noisy observations produced by a set of cameras with possibly different characteristics. In previous work, we have implemented a distributed surveillance system designed for complex indoor environments [1]. The system uses the Abstract Hidden Markov mEmory Model (AHMEM) for modelling and specifying complex human behaviours that can take place in the environment. Given a sequence of observations from a set of cameras, the system employs approximate probabilistic inference to compute the likelihood of different possible behaviours in real-time. This paper describes the techniques that can be used to learn the different camera noise models and the human movement models to be used in this system. The system is able to monitor and classify people behaviours as data is being gathered, and we provide classification results showing the system is able to identify behaviours of people from their movement signatures.

Inside Movement Knowledge

Inside Movement Knowledge was a two-year (2008-2010) collaborative, interdisciplinary research project into new methods for the documentation, transmission and preservation of contemporary choreographic and dance knowledge. The project has evolved out of research initiated in 2004 by Amsterdam-based dance company Emio Greco | PC (Pieter C. Scholten) into systems for recording and transmitting the essential elements of their creative work. Inside Movement Knowledge took the outcomes of this earlier research (book, interactive DVD and installation) as a ‘case-study’ to continue exploring the questions of Emio Greco | PC in collaboration with a new consortium made up of the Netherlands Media Art Institute (through their preservation department); the University of Utrecht (through the newly established Theatre Studies program); and the Dance Department/ Theaterschool, Amsterdam School of the Arts. This expanded research project was supported by the Dutch Ministry of Education, Culture and Science.

The documentation website will remain on-line indefinitely as a resource for researchers interested in the documentation, transmission and preservation of contemporary dance and in how this project was set up to explore these topics.

Coupling online control and inhibitory systems in children with developmental coordination disorder: goal-directed reaching

For children with Developmental Coordination Disorder (DCD), the real-time coupling between frontal executive function and online motor control has not been explored despite reported deficits in each domain. The aim of the present study was to investigate how children with DCD enlist online control under task constraints that compel the need for inhibitory control. A total of 129 school children were sampled from mainstream primary schools. Forty-two children who met research criteria for DCD were compared with 87 typically developing controls on a modified double-jump reaching task. Children within each skill group were divided into three age bands: younger (6-7 years), mid-aged (8-9), and older (10-12). Online control was compared between groups as a function of trial type (non-jump, jump, anti-jump). Overall, results showed that while movement times were similar between skill groups under simple task constraints (non-jump), on perturbation (or jump) trials the DCD group were significantly slower than controls and corrected trajectories later. Critically, the DCD group was further disadvantaged by anti-jump trials where inhibitory control was required; however, this effect reduced with age. While coupling online control and executive systems is not well developed in younger and mid-aged children, there is evidence of age-appropriate coupling in older children. Longitudinal data are needed to clarify this intriguing finding. The theoretical and applied implications of these results are discussed.

Why has the safety and quality movement been slow to improve care?

Buist and Middleton lament that the safety and quality 'agenda' has failed to fundamentally alter the safety of healthcare systems, in part because of the disengagement of doctors from their responsibilities for patient safety . While there have been discernable improvements in the efficiency and effectiveness of care in some settings, patients still experience unacceptable harm and often struggle to have their voices heard; processes are not as efficient as they could be; and costs continue to rise at alarming rates while quality issues remain . Perhaps of most concern, recent public reports into health system failures continue to document a widespread lack of attentiveness to patient concerns, a culture of denial and widespread lack of professionalism . Alarmingly, clinician discontentment, cynicism and burn-out are reflected in antagonistic language by clinicians about the healthcare system and their patients. Taken together with the many dissatisfied and now more vocal patient groups, all point to an unprecedented crisis of faith in our healthcare systems which has been getting worse over past decade . This personal perspective aims to address the fundamental tensions that are keeping much of healthcare reform efforts from successfully transforming the culture and outcomes except at the margins.

Detection of respiratory paradoxical movement via doppler radar measurements

 This paper presents an evaluation of microwave Doppler radar in capturing the respiration signal from the chest and abdomen simultaneously using two radar systems. Two experiments were conducted to investigate the feasibility of using Doppler radar in measuring respiration from both chest and abdomen simultaneously. Results obtained indicate that the respiration patterns from the radar were highly correlated with the reference respiration strap readings for normal breathing scenarios and also sensitive enough in capturing the paradoxical movement between the chest and the abdomen in the professionally role played experiments.

Viable approaches for increasing the efficiency of buiding integrated photovoltaic systems

Nowadays, there is growing interest towards the area of building integrated photovoltaic (BIPV) systems and PV microgrids (MGs) in the field of power generation and distribution systems. This is mainly due to the higher adaptability and compatibility of these systems with preplanned sustainable development strategies in the most urban areas. The quiet operating process and movement free characteristic of photovoltaic systems brought them to the roof tops of the buildings in urban and rural areas and made them the most demanded means of renewable energy systems. This study highlights the problems affecting the performance and efficiency of BIPV systems and presents miscellaneous solutions and recommendations to solve these problems.

Robust real-time bio-kinematic movement tracking using multiple kinects for tele-rehabilitation

This paper investigates the robust and accurate capture of human joint poses and bio-kinematic movements for exercise monitoring in real-time tele-rehabilitation applications. Recently developed model-based estimation ideas are used to improve the accuracy, robustness, and real-time characteristics considered vital for applications, where affordability and domestic use are the primary focus. We use the spatial diversity of the arbitrarily positioned Microsoft Kinect receivers to improve the reliability and promote the uptake of the concept. The skeleton-based information is fused to enhance accuracy and robustness, critical for biomedical applications. A specific version of a robust Kalman filter (KF) in a linear framework is employed to ensure superior estimator convergence and real-time use, compared to other commonly used filters. The algorithmic development was conducted in a generic form and computer simulations were conducted to verify our assertions. Hardware implementations were carried out to test the viability of the proposed state estimator in terms of the core requirements of reliability, accuracy, and real-time use. Performance of the overall system implemented in an information fusion context was evaluated against the commercially available and industry standard Vicon system for different exercise routines, producing comparable results with much less infrastructure and financial investment.