User-centred car design and the role of feedback in driving

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A survey of car manufacturers reveals an impressive list of upcoming technologies, the combined effect of which is likely to have a profound impact upon feedback to the driver. Feedback is information that the situation provides back to the driver and is specified with reference to content, source, and timing. Feedback quality is achieved when the information requirements of the task, derived from a new task analysis of driving, are matched to the sources, content, and timing of feedback provided by the environment and the vehicle. An exploratory on-road study begins by observing that better quality feedback is implicated in increasing driver's situational awareness (even though drivers have little self awareness of this fact), and optimising mental workload. The exploratory level of analysis builds into the experimental, whereby a highly controlled simulator study replicates and builds upon these findings. Feedback is again seen to positively influence situational awareness, where changes in driver's confidence ratings as to the presence or absence of feedback information in the simulation were observed, according to the modality of feedback presented. This was achieved with a probe recall paradigm, and using psychophysical techniques as a useful extension to the Situational awareness Global Assessment Technique (SAGAI). Similarly, an analysis of mental workload via the NASA TLX self report questionnaire demonstrates that a combination of visual, steering force feedback and auditory feedback gives rise to lower mental workload, lower driver frustration, and lower, though possibly more realistic self ratings of performance. This knowledge can be discussed with reference to a feedback framework of driving that provides the theoretical backdrop to the key psychological variables implicated in driving task performance. Overall, the findings contribute to knowledge in terms of new and imaginative ways of designing future vehicle technologies in order to maximise safety, efficiency, and enjoyment.This research is funded by the Hamilton Research Studentship

Adaptive Streaming: From Bitrate Maximization to Rate-Distortion Optimization

The fundamental conflict between the increasing consumer demand for better Quality-of-Experience (QoE) and the limited supply of network resources has become significant challenges to modern video delivery systems. State-of-the-art adaptive bitrate (ABR) streaming algorithms are dedicated to drain available bandwidth in hope to improve viewers' QoE, resulting in inefficient use of network resources. In this thesis, we develop an alternative design paradigm, namely rate-distortion optimized streaming (RDOS), to balance the contrast demands from video consumers and service providers. Distinct from the traditional bitrate maximization paradigm, RDOS must operate at any given point along the rate-distortion curve, as specified by a trade-off parameter. The new paradigm has found plausible explanations in information theory, economics, and visual perception. To instantiate the new philosophy, we decompose adaptive streaming algorithms into three mutually independent components, including throughput predictor, reward function, and bitrate selector. We provide a unified framework to understand the connections among all existing ABR algorithms. The new perspective also illustrates the fundamental limitations of each algorithm by going behind its underlying assumptions. Based on the insights, we propose novel improvements to each of the three functional components. To alleviate a series of unrealistic assumptions behind bitrate-based QoE models, we develop a theoretically-grounded objective QoE model. The new objective QoE model combines the information from subject-rated streaming videos and the prior knowledge about human visual system (HVS) in a principled way. By analyzing a corpus of psychophysical experiments, we show the QoE function estimation can be formulated as a projection onto convex sets problem. The proposed model presents strong generalization capability over a broad range of source contents, video encoders, and viewing conditions. Most importantly, the QoE model disentangles bitrate with quality, making it an ideal component in the RDOS framework. In contrast to the existing throughput estimators that approximate the marginal probability distribution over all connections, we optimize the throughput predictor conditioned on each client. Although there are lack of training data for each Internet Protocol connection, we can leverage the latest advances in meta learning to incorporate the knowledge embedded in similar tasks. With a deliberately designed objective function, the algorithm learns to identify similar structures among different network characteristics from millions of realistic throughput traces. During the test phase, the model can quickly adapt to connection-level network characteristics with only a small amount of training data from novel streaming video clients with a small number of gradient steps. The enormous space of streaming videos, constantly progressing encoding schemes, and great diversity of throughput characteristics make it extremely challenging for modern data-driven bitrate selectors that are trained with limited samples to generalize well. To this end, we propose a Bayesian bitrate selection algorithm by adaptively fusing an online, robust, and short-term optimal controller with an offline, susceptible, and long-term optimal planner. Depending on the reliability of the two controllers in certain system states, the algorithm dynamically prioritizes the one of the two decision rules to obtain the optimal decision. To faithfully evaluate the performance of RDOS, we construct a large-scale streaming video dataset -- the Waterloo Streaming Video database. It contains a wide variety of high quality source contents, encoders, encoding profiles, realistic throughput traces, and viewing devices. Extensive objective evaluation demonstrates the proposed algorithm can deliver identical QoE to state-of-the-art ABR algorithms at a much lower cost. The improvement is also supported by so-far the largest subjective video quality assessment experiment

A gaze-contingent framework for perceptually-enabled applications in healthcare

Patient safety and quality of care remain the focus of the smart operating room of the future. Some of the most influential factors with a detrimental effect are related to suboptimal communication among the staff, poor flow of information, staff workload and fatigue, ergonomics and sterility in the operating room. While technological developments constantly transform the operating room layout and the interaction between surgical staff and machinery, a vast array of opportunities arise for the design of systems and approaches, that can enhance patient safety and improve workflow and efficiency. The aim of this research is to develop a real-time gaze-contingent framework towards a "smart" operating suite, that will enhance operator's ergonomics by allowing perceptually-enabled, touchless and natural interaction with the environment. The main feature of the proposed framework is the ability to acquire and utilise the plethora of information provided by the human visual system to allow touchless interaction with medical devices in the operating room. In this thesis, a gaze-guided robotic scrub nurse, a gaze-controlled robotised flexible endoscope and a gaze-guided assistive robotic system are proposed. Firstly, the gaze-guided robotic scrub nurse is presented; surgical teams performed a simulated surgical task with the assistance of a robot scrub nurse, which complements the human scrub nurse in delivery of surgical instruments, following gaze selection by the surgeon. Then, the gaze-controlled robotised flexible endoscope is introduced; experienced endoscopists and novice users performed a simulated examination of the upper gastrointestinal tract using predominately their natural gaze. Finally, a gaze-guided assistive robotic system is presented, which aims to facilitate activities of daily living. The results of this work provide valuable insights into the feasibility of integrating the developed gaze-contingent framework into clinical practice without significant workflow disruptions.Open Acces

Video compression algorithms for HEVC and beyond

PhDDue to the increasing number of new services and devices that allow the creation, distribution and consumption of video content, the amount of video information being transmitted all over the world is constantly growing. Video compression technology is essential to cope with the ever increasing volume of digital video data being distributed in today's networks, as more e cient video compression techniques allow support for higher volumes of video data under the same memory/bandwidth constraints. This is especially relevant with the introduction of new and more immersive video formats associated with signi cantly higher amounts of data. In this thesis, novel techniques for improving the e ciency of current and future video coding technologies are investigated. Several aspects that in uence the way conventional video coding methods work are considered. In particular, the properties and limitations of the Human Visual System are exploited to tune the performance of video encoders towards better subjective quality. Additionally, it is shown how the visibility of speci c types of visual artefacts can be prevented during the video encoding process, in order to avoid subjective quality degradations in the compressed content. Techniques for higher video compression e ciency are also explored, targeting to improve the compression capabilities of state-of-the-art video coding standards. Finally, the application of video coding technologies to practical use-cases is considered. Accurate estimation models are devised to control the encoding time and bit rate associated with compressed video signals, in order to meet speci c encoding time and transmission time restrictions

Submaximal running testing to monitor training responses in elite Australian rules football players

Monitoring training load and training responses in professional football continues to inform athlete management, injury prevention and player welfare. Maximising fitness and minimizing fatigue are finely balanced and differ within phases of the periodised year. It is possible that submaximal exercise tests are more useful than maximal exercise testing to regularly monitor individual training responses in a team environment. The overarching aim of this thesis was to demonstrate the effectiveness of using heart rate measured during a novel submaximal intermittent running test to monitor training responses throughout a season in elite Australian rules football players. The thesis comprised systematic and narrative reviews of the literature, focussing on advances in athlete monitoring within professional football codes. Findings informed the next three studies of original research

Eye quietness and quiet eye in expert and novice golf performance: an electrooculographic analysis

Quiet eye (QE) is the final ocular fixation on the target of an action (e.g., the ball in golf putting). Camerabased eye-tracking studies have consistently found longer QE durations in experts than novices; however, mechanisms underlying QE are not known. To offer a new perspective we examined the feasibility of measuring the QE using electrooculography (EOG) and developed an index to assess ocular activity across time: eye quietness (EQ). Ten expert and ten novice golfers putted 60 balls to a 2.4 m distant hole. Horizontal EOG (2ms resolution) was recorded from two electrodes placed on the outer sides of the eyes. QE duration was measured using a EOG voltage threshold and comprised the sum of the pre-movement and post-movement initiation components. EQ was computed as the standard deviation of the EOG in 0.5 s bins from –4 to +2 s, relative to backswing initiation: lower values indicate less movement of the eyes, hence greater quietness. Finally, we measured club-ball address and swing durations. T-tests showed that total QE did not differ between groups (p = .31); however, experts had marginally shorter pre-movement QE (p = .08) and longer post-movement QE (p < .001) than novices. A group × time ANOVA revealed that experts had less EQ before backswing initiation and greater EQ after backswing initiation (p = .002). QE durations were inversely correlated with EQ from –1.5 to 1 s (rs = –.48 - –.90, ps = .03 - .001). Experts had longer swing durations than novices (p = .01) and, importantly, swing durations correlated positively with post-movement QE (r = .52, p = .02) and negatively with EQ from 0.5 to 1s (r = –.63, p = .003). This study demonstrates the feasibility of measuring ocular activity using EOG and validates EQ as an index of ocular activity. Its findings challenge the dominant perspective on QE and provide new evidence that expert-novice differences in ocular activity may reflect differences in the kinematics of how experts and novices execute skills

Biorefarmeries: Milking ethanol from algae for the mobility of tomorrow

The idea of this project is to fully exploit microalgae to the best of its potential, possibly proposing a sort of fourth generation fuel based on a continuous milking of macro- and microorganisms (as cows in a milk farm), which produce fuel by photosynthetic reactions. This project proposes a new transportation concept supported by a new socio-economic approach, in which biofuel production is based on biorefarmeries delivering fourth generation fuels which also have decarbonization capabilities, potential negative CO2 emissions plus positive impacts on mobility, the automotive Industry, health and environment and the econom

Investigation into Stand-alone Brain-computer Interfaces for Musical Applications

Brain-computer interfaces (BCIs) aim to establish a communication medium that is independent of muscle control. This project investigates how BCIs can be harnessed for musical applications. The impact of such systems is twofold — (i) it offers a novel mechanism of control for musicians during performance and (ii) it is beneficial for patients who are suffering from motor disabilities. Several challenges are encountered when attempting to move these technologies from laboratories to real-world scenarios. Additionally, BCIs are significantly different from conventional computer interfaces and realise low communication rates. This project considers these challenges and uses a dry and wireless electroencephalogram (EEG) headset to detect neural activity. It adopts a paradigm called steady state visually evoked potential (SSVEP) to provide the user with control. It aims to encapsulate all braincomputer music interface (BCMI)-based operations into a stand-alone application, which would improve the portability of BCMIs. This projects addresses various engineering problems that are faced while developing a stand-alone BCMI. In order to efficiently present the visual stimulus for SSVEP, it requires hardware-accelerated rendering. EEG data is received from the headset through Bluetooth and thus, a dedicated thread is designed to receive signals. As this thesis is not using medical-grade equipment to detect EEG, signal processing techniques need to be examined to improve the signal to noise ratio (SNR) of brain waves. This projects adopts canonical correlation analysis (CCA), which is multi-variate statistical technique and explores filtering algorithms to improve communication rates of BCMIs. Furthermore, this project delves into optimising biomedical engineering-based parameters, such as placement of the EEG headset and size of the visual stimulus. After implementing the optimisations, for a time window of 4s and 2s, the mean accuracies of the BCMI are 97.92±2.22% and 88.02±9.30% respectively. The obtained information transfer rate (ITR) is 36.56±9.17 bits min-1, which surpasses communication rates of earlier BCMIs. This thesis concludes by building a system which encompasses a novel control flow, which allows the user to play a musical instrument by gazing at it.The School of Humanities and Performing Arts, University of Plymout

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

Quality of experience in digital mobile multimedia services

People like to consume multimedia content on mobile devices. Mobile networks can deliver mobile TV services but they require large infrastructural investments and their operators need to make trade-offs to design worthwhile experiences. The approximation of how users experience networked services has shifted from the inadequate packet level Quality of Service (QoS) to the user perceived Quality of Experience (QoE) that includes content, user context and their expectations. However, QoE is lacking concrete operationalizations for the visual experience of content on small, sub-TV resolution screens displaying transcoded TV content at low bitrates. The contribution of my thesis includes both substantive and methodological results on which factors contribute to the QoE in mobile multimedia services and how. I utilised a mix of methods in both lab and field settings to assess the visual experience of multimedia content on mobile devices. This included qualitative elicitation techniques such as 14 focus groups and 75 hours of debrief interviews in six experimental studies. 343 participants watched 140 hours of realistic TV content and provided feedback through quantitative measures such as acceptability, preferences and eye-tracking. My substantive findings on the effects of size, resolution, text quality and shot types can improve multimedia models. My substantive findings show that people want to watch mobile TV at a relative size (at least 4cm of screen height) similar to living room TV setups. In order to achieve these sizes at 35cm viewing distance users require at least QCIF resolution and are willing to scale it to a much lower angular resolution (12ppd) then what video quality research has found to be the best visual quality (35ppd). My methodological findings suggest that future multimedia QoE research should use a mixed methods approach including qualitative feedback and viewing ratios akin to living room setups to meet QoE’s ambitious scope