Real-time Immersive human-computer interaction based on tracking and recognition of dynamic hand gestures

With fast developing and ever growing use of computer based technologies, human-computer interaction (HCI) plays an increasingly pivotal role. In virtual reality (VR), HCI technologies provide not only a better understanding of three-dimensional shapes and spaces, but also sensory immersion and physical interaction. With the hand based HCI being a key HCI modality for object manipulation and gesture based communication, challenges are presented to provide users a natural, intuitive, effortless, precise, and real-time method for HCI based on dynamic hand gestures, due to the complexity of hand postures formed by multiple joints with high degrees-of-freedom, the speed of hand movements with highly variable trajectories and rapid direction changes, and the precision required for interaction between hands and objects in the virtual world. Presented in this thesis is the design and development of a novel real-time HCI system based on a unique combination of a pair of data gloves based on fibre-optic curvature sensors to acquire finger joint angles, a hybrid tracking system based on inertia and ultrasound to capture hand position and orientation, and a stereoscopic display system to provide an immersive visual feedback. The potential and effectiveness of the proposed system is demonstrated through a number of applications, namely, hand gesture based virtual object manipulation and visualisation, hand gesture based direct sign writing, and hand gesture based finger spelling. For virtual object manipulation and visualisation, the system is shown to allow a user to select, translate, rotate, scale, release and visualise virtual objects (presented using graphics and volume data) in three-dimensional space using natural hand gestures in real-time. For direct sign writing, the system is shown to be able to display immediately the corresponding SignWriting symbols signed by a user using three different signing sequences and a range of complex hand gestures, which consist of various combinations of hand postures (with each finger open, half-bent, closed, adduction and abduction), eight hand orientations in horizontal/vertical plans, three palm facing directions, and various hand movements (which can have eight directions in horizontal/vertical plans, and can be repetitive, straight/curve, clockwise/anti-clockwise). The development includes a special visual interface to give not only a stereoscopic view of hand gestures and movements, but also a structured visual feedback for each stage of the signing sequence. An excellent basis is therefore formed to develop a full HCI based on all human gestures by integrating the proposed system with facial expression and body posture recognition methods. Furthermore, for finger spelling, the system is shown to be able to recognise five vowels signed by two hands using the British Sign Language in real-time

Real-time immersive human-computer interaction based on tracking and recognition of dynamic hand gestures

With fast developing and ever growing use of computer based technologies, human-computer interaction (HCI) plays an increasingly pivotal role. In virtual reality (VR), HCI technologies provide not only a better understanding of three-dimensional shapes and spaces, but also sensory immersion and physical interaction. With the hand based HCI being a key HCI modality for object manipulation and gesture based communication, challenges are presented to provide users a natural, intuitive, effortless, precise, and real-time method for HCI based on dynamic hand gestures, due to the complexity of hand postures formed by multiple joints with high degrees-of-freedom, the speed of hand movements with highly variable trajectories and rapid direction changes, and the precision required for interaction between hands and objects in the virtual world. Presented in this thesis is the design and development of a novel real-time HCI system based on a unique combination of a pair of data gloves based on fibre-optic curvature sensors to acquire finger joint angles, a hybrid tracking system based on inertia and ultrasound to capture hand position and orientation, and a stereoscopic display system to provide an immersive visual feedback. The potential and effectiveness of the proposed system is demonstrated through a number of applications, namely, hand gesture based virtual object manipulation and visualisation, hand gesture based direct sign writing, and hand gesture based finger spelling. For virtual object manipulation and visualisation, the system is shown to allow a user to select, translate, rotate, scale, release and visualise virtual objects (presented using graphics and volume data) in three-dimensional space using natural hand gestures in real-time. For direct sign writing, the system is shown to be able to display immediately the corresponding SignWriting symbols signed by a user using three different signing sequences and a range of complex hand gestures, which consist of various combinations of hand postures (with each finger open, half-bent, closed, adduction and abduction), eight hand orientations in horizontal/vertical plans, three palm facing directions, and various hand movements (which can have eight directions in horizontal/vertical plans, and can be repetitive, straight/curve, clockwise/anti-clockwise). The development includes a special visual interface to give not only a stereoscopic view of hand gestures and movements, but also a structured visual feedback for each stage of the signing sequence. An excellent basis is therefore formed to develop a full HCI based on all human gestures by integrating the proposed system with facial expression and body posture recognition methods. Furthermore, for finger spelling, the system is shown to be able to recognise five vowels signed by two hands using the British Sign Language in real-time.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Brain Computer Interfaces and Emotional Involvement: Theory, Research, and Applications

This reprint is dedicated to the study of brain activity related to emotional and attentional involvement as measured by Brain–computer interface (BCI) systems designed for different purposes. A BCI system can translate brain signals (e.g., electric or hemodynamic brain activity indicators) into a command to execute an action in the BCI application (e.g., a wheelchair, the cursor on the screen, a spelling device or a game). These tools have the advantage of having real-time access to the ongoing brain activity of the individual, which can provide insight into the user’s emotional and attentional states by training a classification algorithm to recognize mental states. The success of BCI systems in contemporary neuroscientific research relies on the fact that they allow one to “think outside the lab”. The integration of technological solutions, artificial intelligence and cognitive science allowed and will allow researchers to envision more and more applications for the future. The clinical and everyday uses are described with the aim to invite readers to open their minds to imagine potential further developments

Prediction of drivers’ performance in highly automated vehicles

Purpose: The aim of this research was to assess the predictability of driver’s response to critical hazards during the transition from automated to manual driving in highly automated vehicles using their physiological data.Method: A driving simulator experiment was conducted to collect drivers’ physiological data before, during and after the transition from automated to manual driving. A total of 33 participants between 20 and 30 years old were recruited. Participants went through a driving scenario under the influence of different non-driving related tasks. The repeated measures approach was used to assess the effect of repeatability on the driver’s physiological data. Statistical and machine learning methods were used to assess the predictability of drivers’ response quality based on their physiological data collected before responding to a critical hazard. Findings: - The results showed that the observed physiological data that was gathered before the transition formed strong indicators of the drivers’ ability to respond successfully to a potential hazard after the transition. In addition, physiological behaviour was influenced by driver’s secondary tasks engagement and correlated with the driver’s subjective measures to the difficulty of the task. The study proposes new quality measures to assess the driver’s response to critical hazards in highly automated driving. Machine learning results showed that response time is predictable using regression methods. In addition, the classification methods were able to classify drivers into low, medium and high-risk groups based on their quality measures values. Research Implications: Proposed models help increase the safety of automated driving systems by providing insights into the drivers’ ability to respond to future critical hazards. More research is required to find the influence of age, drivers’ experience of the automated vehicles and traffic density on the stability of the proposed models. Originality: The main contribution to knowledge of this study is the feasibility of predicting drivers’ ability to respond to critical hazards using the physiological behavioural data collected before the transition from automated to manual driving. With the findings, automation systems could change the transition time based on the driver’s physiological state to allow for the safest transition possible. In addition, it provides an insight into driver’s readiness and therefore, allows the automated system to adopt the correct driving strategy and plan to enhance drivers experience and make the transition phase safer for everyone.</div

Measuring knowledge sharing processes through social network analysis within construction organisations

The construction industry is a knowledge intensive and information dependent industry. Organisations risk losing valuable knowledge, when the employees leave them. Therefore, construction organisations need to nurture opportunities to disseminate knowledge through strengthening knowledge-sharing networks. This study aimed at evaluating the formal and informal knowledge sharing methods in social networks within Australian construction organisations and identifying how knowledge sharing could be improved. Data were collected from two estimating teams in two case studies. The collected data through semi-structured interviews were analysed using UCINET, a Social Network Analysis (SNA) tool, and SNA measures. The findings revealed that one case study consisted of influencers, while the other demonstrated an optimal knowledge sharing structure in both formal and informal knowledge sharing methods. Social networks could vary based on the organisation as well as the individuals’ behaviour. Identifying networks with specific issues and taking steps to strengthen networks will enable to achieve optimum knowledge sharing processes. This research offers knowledge sharing good practices for construction organisations to optimise their knowledge sharing processes

The 45th Australasian Universities Building Education Association Conference: Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment, Conference Proceedings, 23 - 25 November 2022, Western Sydney University, Kingswood Campus, Sydney, Australia

This is the proceedings of the 45th Australasian Universities Building Education Association (AUBEA) conference which will be hosted by Western Sydney University in November 2022. The conference is organised by the School of Engineering, Design, and Built Environment in collaboration with the Centre for Smart Modern Construction, Western Sydney University. This year’s conference theme is “Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment”, and expects to publish over a hundred double-blind peer review papers under the proceedings

Presence 2005: the eighth annual international workshop on presence, 21-23 September, 2005 University College London (Conference proceedings)

OVERVIEW (taken from the CALL FOR PAPERS) Academics and practitioners with an interest in the concept of (tele)presence are invited to submit their work for presentation at PRESENCE 2005 at University College London in London, England, September 21-23, 2005. The eighth in a series of highly successful international workshops, PRESENCE 2005 will provide an open discussion forum to share ideas regarding concepts and theories, measurement techniques, technology, and applications related to presence, the psychological state or subjective perception in which a person fails to accurately and completely acknowledge the role of technology in an experience, including the sense of 'being there' experienced by users of advanced media such as virtual reality. The concept of presence in virtual environments has been around for at least 15 years, and the earlier idea of telepresence at least since Minsky's seminal paper in 1980. Recently there has been a burst of funded research activity in this area for the first time with the European FET Presence Research initiative. What do we really know about presence and its determinants? How can presence be successfully delivered with today's technology? This conference invites papers that are based on empirical results from studies of presence and related issues and/or which contribute to the technology for the delivery of presence. Papers that make substantial advances in theoretical understanding of presence are also welcome. The interest is not solely in virtual environments but in mixed reality environments. Submissions will be reviewed more rigorously than in previous conferences. High quality papers are therefore sought which make substantial contributions to the field. Approximately 20 papers will be selected for two successive special issues for the journal Presence: Teleoperators and Virtual Environments. PRESENCE 2005 takes place in London and is hosted by University College London. The conference is organized by ISPR, the International Society for Presence Research and is supported by the European Commission's FET Presence Research Initiative through the Presencia and IST OMNIPRES projects and by University College London

Procedures and Methodologies for the Control and Improvement of Energy-Environmental Quality in Construction

This Special Issue aims at providing the state-of-the-art on procedures and methodologies developed to improve energy and environmental performance through building renovation. We are greatly thankful to our colleagues building physics experts, building technology researchers, and urban environment scholars who contributed to this Special Issue, for sharing their original works in the field

Structural and functional brain alterations in fibromyalgia syndrome patients

Fibromyalgia syndrome (FMS) is a widespread chronic pain disorder affecting 2−5% of the general population and particularly women of middle age (McBeth and Mulvey, 2012). The syndrome is frequently comorbid with a variety of clinical, functional and psychological disorders (Weir et al., 2006) and associated with a large socio-economic burden (Lachaine et al., 2010). In spite of significant previous research, the underlying aetiology and pathophysiology of FMS is not fully understood (Schmidt-Wilcke and Clauw, 2011). However, aberrant structural and functional brain alterations have been proposed as a casual or maintaining factor of the disorder (Schweinhardt et al., 2008). This thesis utilised functional and structural imaging methods and novel experimental paradigms to explore brain alterations in FMS patients. A comprehensive review of previous experimental findings was performed to identify novel research questions. EEG and MRI data for 5 unique studies was collected over two sessions. In the first study dynamic mechanical stimulation was applied to the forearm of FMS patients and healthy participants, and an ERD analysis of corresponding EEG data was performed. The results revealed that FMS patients exhibited alterations to cortical excitability during brushing stimuli which correlated with clinical measures. These findings indicate that abnormal processing of innocuous somatosensory stimulation may contribute to the pathophysiology and clinical symptom severity of FMS. Secondly, an ERP analysis of EEG data from the observation of pain and non-pain pictures was performed. FMS patients exhibited differences in ERP components and source activation patterns during observation of pain pictures relative to healthy people. Alterations to processing of observed pain occurred in parahippocampal gyrus and may relate to clinical and psychological aspects of FMS, this finding could be utilised to further understand the heterogeneity of psychological profiles of FMS patients in order to better target therapeutic interventions. The third study of the thesis describes a novel comparison of functional connectivity with resting-state network structures utilising fMRI recordings. Functional connectivity with default mode network structures was shown to be altered in FMS. This finding may reflect an ongoing time-dependent reorganisation of resting-state networks due to ongoing chronic pain. In the fourth study, a morphological analysis of subcortical structures was performed using high-resolution T1-weighted MR images. FMS patients demonstrated alterations to the morphology of the brainstem, an important structure in descending nociceptive control. Volumetric alterations in this structure correlated with clinical measures of symptom severity suggesting an important role for brainstem alterations in FMS pain symptoms. In the final study the microstructural integrity of white matter was compared between FMS patients and healthy participants. Although no significant differences were identified the findings indicate that FMS is not likely to be related to abnormal development of white matter tracts. Therefore structural alterations associated with FMS are likely to occur only in the grey matter