The relationship between game content and gameplay remains underexplored. High level debate about the relative narrativity of games remains common, but there is a gap in the understanding about the particularities of how diegetic objects relates to the business of managing player experience and behaviour at the heart of gameplay. The first half of this thesis proposes a new model for understanding gameplay as a network of affordance relationships which define supported actions. The theoretical focus upon supported actions rather than object characteristics enables a better understanding of the framework of gameplay created by a complex system of interrelated objects. In particular, it illustrates how the essential ludic structure of first-person games can be described in very simple terms, thus defining a discontinuity between complexity of experience and simplicity of structure. It is proposed that story is a primary means of managing this discontinuity to provide an immersive and seamless experience. Traditional models of narrative and interactive narrative are discussed to illustrate the problems of attempting to apply them directly to gameplay, and this is summarised in a discussion of the narratology/ludology debate. Instead, a new conceptualisation of narrative, drawn from the use of narrative as a model and metaphor in psychology, and based on schema theory is offered. It is argued that this new, game-specific conceptualisation - of a network of protonarrative units - maps efficiently and effectively onto the affordance model of gameplay and thus resolves the historical problem. In the second half of the thesis, evidence is offered to support the argument that not only can story be understood as a form of affordance, but that by examining commercial FPS titles, it is clear that story is used to manipulate player behaviour - that it serves a distinct gameplay function. This is achieved by analysing core elements of story: worlds and their populations; the avatar as a key device in managing the player/system relationship; and plot as the predetermined changes to object relationships over the course of a game. It is concluded that when gameplay is understood as a network of affordances, and story as a network of proto narrative units, and when the genre is analysed with this model in mind, not only is an understanding of the gameplay function of story evident, but this analysis yields a deeper level of understanding about the nature of FPS games and gameplay than has previously been available.

Psychomotor slowing, and in particular slow walking, is a common correlate of illness or injury, and often persists long after the precipitating condition has improved. Since slow walking has implications for long term physical and social wellbeing, it is important to find ways to address this issue. However, whilst it is well established that exercise programmes are good approaches to increase movement speed, adherence to therapy remains poor. The main reasons for this appear to be pain and lack of interest and enjoyment in the exercise. Virtual Rehabilitation combines physical therapy with Virtual Reality (VR). This is a rapidly growing area of health care, which seems to offer a potential solution to these issues, by offering the benefits of increased patient engagement and decreased perception of pain. However, the question of how to encourage patients to increase their walking speed whilst interacting with VR has remained unanswered. Moreover, to maximise the benefits of this type of therapy, there needs to be a greater understanding of how different factors in treadmill-mediated VR can facilitate (or hinder) optimal walking. Therefore this thesis investigated the factors influencing walking and perception of walking in treadmill-mediated VR, using a series of empirical investigations to determine the effect of a variety of factors in VR, which can then be applied in a clinical setting. A review of the literature identified that high contrast stereoscopic virtual environments, calibrated to real-world dimensions, with a wide field of view and peripheral visual cues, are likely to facilitate accurate self-motion perception. Empirical studies demonstrated that decreasing the visual gain (ratio of optic flow to walk speed) in VR can lead to a sustained increase in walk speed. However, these lower rates of visual gain are likely to be perceived as unrealistic, and may decrease immersion. Further investigation demonstrated that there is a range of visual gain which is perceived as acceptably normal, although even the lower bound of this acceptable gain is still higher than the optimum gain for facilitating faster movements. Thus there is a trade-off between visual gain for realistic perception, and visual gain for improved walking speeds. Therefore other components that can improve walking speed need to be identified, particularly for those applications where reduction of the visual gain is undesirable. Further empirical studies demonstrated that fast audio cues (125% of baseline cadence), in the form of a footstep sound, can increase the walk speed without disrupting the natural walk ratio. This effect was demonstrated in healthy populations, and also shown to be evident in a group of patients with chronic musculoskeletal pain. It was noted that in all the studies comparing a pain and non-pain group, the pain group walked more slowly across all conditions. Additional empirical studies demonstrated that the use of self-paced treadmills for interfacing with VR was found to be associated with somewhat lower baseline walk speeds than normal overground walking, although the self-paced treadmills preserved the normal walk ratio. This slowing of walking and preservation of walk ratio was seen in both healthy participants and also in participants with chronic musculoskeletal pain. Therefore, whilst self-paced treadmills can support natural walking, additional factors need to be considered if treadmill-mediated VR is to be used to facilitate the increase in walking speeds desirable for rehabilitation. Thus designing VR for rehabilitation is likely to involve consideration of a number of factors, and making individualised design decision based on specific therapeutic goals.

A vehicle active suspension system, in comparison with its counterparts, plays a crucial role in adequately guarantee the stability of the vehicle and improve the suspension performances. With a full understanding of the state of the art in vehicle control systems, this thesis identifies key issues in robust control design for active suspension systems with uncertainty, contributes to enhance the suspension performances via handling tradeoffs between ride comfort, road holding and suspension deflection. Priority of this thesis is to emphasize the contributions in handing actuator-related challenges and suspension model parameter uncertainty. The challenges in suspension actuators are identified as time-varying actuator delay and actuator faults. Time-varying delay and its effects in suspension actuators are targeted and analyzed. By removing the assumptions from the state of the art methods, state-feedback and output-feedback controller design methods are proposed to design less conservative state-feedback and output-feedback controller existence conditions. It overcomes the challenges brought by generalized timevarying actuator delay. On the other hand, a novel fault-tolerant controller design algorithm is developed for active suspension systems with uncertainty of actuator faults. A continuous-time homogeneous Markov process is presented for modeling the actuator failure process. The fault-tolerant H∞ controller is designed to guarantee asymptotic the stability, H∞ performance, and the constrained performance with existing possible actuator failures. It is evident that vehicle model parameter uncertainty is a vital factor affecting the performances of suspension control system. Consequently, this thesis presents two robust control solutions to overcome suspension control challenges with nonlinear constraints. A novel fuzzy control design algorithm is presented for active suspension systems with uncertainty. By using the sector nonlinearity method, Takagi-Sugeno (T-S) fuzzy systems are used to model the system. Based on Lyapunov stability theory, a new reliable fuzzy controller is designed to improve suspension performances. A novel adaptive sliding mode controller design approach is also developed for nonlinear uncertain vehicle active suspension systems. An adaptive sliding mode controller is designed to guarantee the stability and improve the suspension performances. In conclusion, novel control design algorithms are proposed for active suspension systems with uncertainty in order to guarantee and improve the suspension performance. Simulation results and comparison with the state of the art methods are provided to evaluate the effectiveness of the research contributions. The thesis shows insights into practical solutions to vehicle active suspension systems, it is expected that these algorithms will have significant potential in industrial applications and electric vehicles industry.

Inspired by Brian Eno's ambient music, which is persistent and supports different levels of engagement, this research explores ambient gameplay in computer, video and pervasive games. Through the creation of original games containing ambient gameplay and looking for ambient gameplay in existing commercial games, this research focuses on gameplay that supports a range of depths of player engagement. This research is not concerned with ambient intelligent environments or other technologies that might support ambience, but focusses on gameplay mechanisms. The definition of ambient music is used as a starting point for developing a tentative set of properties that enable ambient gameplay. A game design research methodology is initially used. Two very different research games, Ambient Quest (using pedometers) and Pirate Moods (using RFID, radio-frequency identification, technology) are analysed. The resulting qualitative ambient gameplay schema contains themes of persistence, discovery, engagement, invention, ambiguity and complexity. In order to confirm the wider applicability of this result a case study of an existing commercial game, Civilization IV, is undertaken. Ambient gameplay properties of engagement, complexity, abstraction, persistence and modelessness identified in Civilization IV, and other commercial games, are combined with the ambient gameplay schema to develop a definition of ambient gameplay. This definition is the basis for a set of investigative lenses (lenses of persistence, attention, locative simultaneity, modelessness, automation and abstraction) for identifying ambient gameplay. This research creates a deeper understanding of computer games and hence gives game designers new ways of developing richer gameplay and gives games researchers new ways of viewing and investigating games.

Unconstrained human hand motions consisting of grasp motion and inhand manipulation lead to a fundamental challenge that many recognition algorithms have to face, in both theoretical and practical development, mainly due to the complexity and dexterity of the human hand. The main contribution of this thesis is a novel fuzzy framework of three proposed recognition algorithms. This consists of extended Time Clustering (TC), Fuzzy Gaussian Mixture Model (FGMM) and Fuzzy Empirical Copula (FEC), using numerical values, Gaussian pattern and data dependency structure respectively in the context of optimal real-time human hand motion recognition. First of all, a fuzzy time-modeling approach, TC, is proposed based on fuzzy clustering and Takagi-Sugeno modeling with a numerical value as output. The extended TC is not only capable of learning repeated motions from the same subject but also can effectively model similar motions from various subjects. The recognition algorithm itself can identify the start point and end point of the testing motion. It is applicable to motion planning directly transfered from the recognition result. Secondly, FGMMis developed to effectively extract abstract Gaussian patterns to represent components of hand gestures with a fast convergence. The dissimilarity function in fuzzy C-means, which maintains the exponential relationship between membership and distance, is refined for FGMM with a degree of fuzziness in terms of the membership grades. Not only does it possess non-linearity but it also offers the characteristic of computationally inexpensive convergence. It is applicable to applications which have a small model storage space and require a method to generate the desired trajectory. Thirdly, FEC is proposed by integrating the fuzzy clustering by local approximation of memberships with Empirical Copula (EC). To save the computational cost, fuzzy clustering reduces the required sampling data and maintains the interrelations before data dependence structure estimation takes over. FEC utilizes the dependence structure among the finger joint angles to recognize the motion type. It is capable of effectively recognizing human handmotions for both single subject andmultiple subjects with a few training samples. It can be used in applications requiring high recognition rate and no desired trajectory with limited training samples. All the proposed algorithms have been evaluated on a wide range of scenarios of human hand recognition: a) datasets including 13 grasps and 10 in-hand manipulations; b) single subject and multiple subjects. c) varying training samples. The experimental results have demonstrated that all the proposed methods in the framework outperform Hidden Markov Model (HMM) and Gaussian Mixture Model (GMM) in terms of both effectiveness and efficiency criteria.

Enormous uncertainties in unconstrained human motions lead to a fundamental challenge that many recognising algorithms have to face in practice: efficient and correct motion recognition is a demanding task, especially when human kinematic motions are subject to variations of execution in the spatial and temporal domains, heavily overlap with each other,and are occluded. Due to the lack of a good solution to these problems, many existing methods tend to be either effective but computationally intensive or efficient but vulnerable to misclassification. This thesis presents a novel inference engine for recognising occluded 3D human motion assisted by the recognition context. First, uncertainties are wrapped into a fuzzy membership function via a novel method called Fuzzy Quantile Generation which employs metrics derived from the probabilistic quantile function. Then, time-dependent and context-aware rules are produced via a genetic programming to smooth the qualitative outputs represented by fuzzy membership functions. Finally, occlusion in motion recognition is taken care of by introducing new procedures for feature selection and feature reconstruction. Experimental results demonstrate the effectiveness of the proposed framework on motion capture data from real boxers in terms of fuzzy membership generation, context-aware rule generation, and motion occlusion. Future work might involve the extension of Fuzzy Quantile Generation in order to automate the choice of a probability distribution, the enhancement of temporal pattern recognition with probabilistic paradigms, the optimisation of the occlusion module, and the adaptation of the present framework to different application domains.

The derivation of margins for use in external beam radiotherapy involves a complex balance between ensuring adequate tumour dose coverage that will lead to cure of the cancer whilst sufficiently sparing the surrounding organs at risk (OARs). The treatment of cancer using ionising radiation is currently witnessing unprecedented levels of new treatment techniques and equipment being introduced. These new treatment strategies, with improved imaging during treatment, are aimed at improved radiation dose conformity to dynamic targets and better sparing of the healthy tissues. However, with the adoption of these new techniques for radiotherapy, the validity of the continued use of recommended statistical model based margin formulations to calculate the treatment margins is now being questioned more than ever before. To derive margins for use in treatment planning which address present shortcomings, this study utilised novel applications of fuzzy logic and neural network techniques to the PTV margin problem. As an extension of this work a new hybrid fuzzy network technique was also adopted for use in margin derivation, a novel application of this technique which required new rule formulations and rule base manipulations. The new margin models developed in this study utilised a novel combination of the radiotherapy errors and their radiobiological effects which was previously difficult to establish using mathematical methods. This was achieved using fuzzy rules and neural network input layers. An advantage of the neural network procedure was that fewer computational steps were needed to calculate the final result whereas the fuzzy based techniques required a significant number of iterative computational steps including the definition of the fuzzy rules and membership functions prior to computation of the final result. An advantage of the fuzzy techniques was their ability to use fewer data points to deduce the relationship between the output and input parameters. In contrast the neural network model requires a large amount of training data. The previously stated limitations of currently recommended statistical techniques were addressed by application of the fuzzy and neural network models. A major advantage of the computational intelligence methods from this study is that they allow the calculation of patient-specific margins. Radiotherapy planning currently relies on the use of ‘one size fits all’ class solutions for margins for each tumour site and with the large variability in patient physiology these margins may not be suitable for use in some cases. The models from this study can be applied to other treatment sites, including brain, lung and gastric tumours.

To the best of the author’s knowledge, this is one of the first times that a large quantity of flight data has been studied in order to improve safety. A two phase novelty detection approach to locating abnormalities in the descent phase of aircraft flight data is presented. It has the ability to model normal time series data by analysing snapshots at chosen heights in the descent, weight individual abnormalities and quantitatively assess the overall level of abnormality of a flight during the descent. The approach expands on a recommendation by the UK Air Accident Investigation Branch to the UK Civil Aviation Authority. The first phase identifies and quantifies abnormalities at certain heights in a flight. The second phase ranks all flights to identify the most abnormal; each phase using a one class classifier. For both the first and second phases, the Support Vector Machine (SVM), the Mixture of Gaussians and the K-means one class classifiers are compared. The method is tested using a dataset containing manually labelled abnormal flights. The results show that the SVM provides the best detection rates and that the approach identifies unseen abnormalities with a high rate of accuracy. Furthermore, the method outperforms the event based approach currently in use. The feature selection tool F-score is used to identify differences between the abnormal and normal datasets. It identifies the heights where the discrimination between the two sets is largest and the aircraft parameters most responsible for these variations.

The phenomenon of pervasive games is a relatively new and unexplored area of games research. These are games that, unlike card, computer, or board games, incorporate elements from outside the perceived boundaries of play, in order to blur the line between reality and fiction and make the game feel more ‘real’. This thesis investigates the player experience of pervasive games, using a novel approach that is informed by the methodology of Glaserian Grounded Theory (Glaser 1978; 1998) in order to clarify understanding and explore issues that players of pervasive games would be likely to encounter. Following a discussion of various themes such as player interpretation, creative play, ambiguity in games and the ‘magic circle of play’, and guided by the preparatory work of the researcher, SF0 (www.sf0.org) is identified as a particularly suitable example of a pervasive game to use for an in-depth study. 24 players of SF0 are interviewed about the gameplay process, and their responses are analysed using the methods implied by Grounded Theory. A theory evolves regarding their experiences, namely that SF0 is providing the means and motive to take part in everyday activities that they somehow could not, or might not, have done before. In particular, SF0 is helping players to be artistic, outgoing and wise. Informed by the methodology, no formal literature review is conducted prior to the main study, therefore the literature is mainly consulted after theory generation in order to more widely situate the results in the context of games literature. Real-world benefit, such as that promoted by ‘serious games’, appears to be emerging from the gameplay in SF0, despite SF0 not appearing to be marketed as a serious game. This unexpected outcome is discussed in terms of implicit rules (Salen & Zimmerman, 2004), player satisfaction, knowledge transfer, and emergence (Johnson, 2001). It is suggested that one explanation for this outcome is the positive attitude SF0 holds towards contradictions in implicit rules which occur from player-to-player. It is recommended that the future study of emergent benefit in games should not be limited to the games overtly labelled as serious games.

Shoulder dysfunction is common and accounts for around four million days of sick leave in the UK each year. Treatment approaches aim to reduce pain, and improve range of motion (ROM). However, patient adherence to therapeutic regimes is poor, partly due to pain avoidance behaviour and lack of engaging therapeutic exercises. Virtual rehabilitation is an area of healthcare which combines physical therapy with virtual reality (VR). It has been shown to facilitate patient engagement and reduce pain perception. Reaching and grasping tasks are well suited to VR applications, and there are a number of studies using VR to explore upper limb motion. However, current approaches for evaluating active shoulder rotation are problematic. A functional test known as Apley’s scratch test could potentially be adapted with magnetic motion tracking, to provide an objective proxy rotation measure to assess changes in ROM in a VR context. An empirical study demonstrated that active rotational movements of the shoulder could be successfully tracked in VR, and that there was evidence of pain suppression during the motion tasks. In addition, head tracking for patients with shoulder and neck pain, was addressed using a novel eye-hand tracking approach. In addition, observations of participants revealed aberrant motion patterns that could compromise rehabilitation outcomes. Despite providing depth cues in the VE itself, analysis suggested that a number of participants remained unsure of the spatial location of the target object which would lead to suboptimal movement behaviour. It was hypothesised that target object geometry may have a particular role in distance judgments, such that a simple icosahedron would provide richer cues with lower computational demand than commonly used spheres or detailed realistic modelled geometry. It was also proposed that providing a proximity cue using exaggerated brightness changes might improve the ability to locate and grasp the object in virtual space. Empirical studies demonstrated that the sphere had a significantly higher duration of time-to-target required in the terminal phase of reaching. Furthermore they demonstrated that a simple icosahedron was more effectively located in virtual space than the sphere object, and performed as well as a more computationally complex “realistic” model. The introduction of richer visual cues only in the terminal phase of reaching was ineffective as was the use of brightness as a proximity cue demonstrating that the use of richer geometry cues throughout was more influential. Nevertheless whilst target object geometry can facilitate spatial perception and influence reaching and grasping task performance, it was not associated with a reduction in arm elevation rigid system behaviour, suggesting other factors still warrant further investigation. This thesis demonstrates that the visual properties of the VE component of a VR system, and specifically the target objects within it, should be taken into consideration when designing spatial perception or reaching tasks in VR, especially within a rehabilitation context.