Mastering the correct use of laboratory equipment is a fundamental skill for undergraduate science students involved in laboratory-based training. However, hands-on laboratory time is often limited, and remote students may struggle as their absence from the physical lab limits their skill development. An air displacement micropipette was selected for this investigation, as accuracy and correct technique are essential in generating reliable assay data. Handling small liquid volumes demands hand dexterity and practice to achieve proficiency. This research assesses the importance of tactile authenticity during training by faithfully replicating the micropipette's key physical and operational characteristics. We developed a custom haptic training approach called 'Smart Pipette' which promotes accurate operation and enhances laboratory dexterity training. A comparative user study with 34 participants evaluated the effectiveness of the Smart Pipette custom haptic device against training with off-the-shelf hardware, specifically the Quest VR hand controller, which was chosen because it is held mid-air similar to a laboratory micropipette. Both training conditions are integrated with the same self-paced virtual simulation displayed on a computer screen, offering audiovisual instructions and real-time guidance. Results demonstrated that participants trained with the Smart Pipette custom haptic exhibited increased accuracy and precision while making fewer errors than those trained with off-the-shelf hardware. The Smart Pipette and the Quest VR controller had no significant differences in cognitive load or system usability scores. Tactile authentic interaction devices address challenges faced by online learners, while their applicability extends to traditional classrooms, where real-time feedback significantly enhances overall training performance outcomes.

User interfaces in virtual reality enable diverse interactions within the virtual world, though they typically lack the haptic cues provided by physical interface controls. Haptic retargeting enables flexible mapping between dynamic virtual interfaces and physical controls to provide real haptic feedback. This investigation aims to extend these remapped interfaces to support more diverse control types. Many interfaces incorporate sliders, switches, and knobs. These controls hold fixed states between interactions creating potential conflicts where a virtual control has a different state from the physical control. This paper presents two methods, “manual” and “automatic”, for synchronizing physical and virtual control states and explores the effects of these methods on the usability of remapped interfaces. Results showed that interfaces without retargeting were the ideal configuration, but they lack the flexibility that remapped interfaces provide. Automatic synchronization was faster and more usable; however, manual synchronization is suitable for a broader range of physical interfaces.

This article presents a set of adaptive reset techniques for use with haptic retargeting systems focusing on interaction with hybrid virtual reality interfaces that align with a physical interface. Haptic retargeting between changing physical and virtual targets requires a reset where the physical and virtual hand positions are re-aligned. We present a modified Point technique to guide the user in the direction of their next interaction such that the remaining distance to the target is minimized upon completion of the reset. This, along with techniques drawn from existing work are further modified to consider the angular and translational gain of each redirection and identify the optimal position for the reset to take place. When the angular and translational gain is within an acceptable range, the reset can be entirely omitted. This enables continuous retargeting between targets removing interruptions from a sequence of retargeted interactions. These techniques were evaluated in a user study which showed that adaptive reset techniques can provide a significant decrease in task completion time, travel distance, and the number of user errors.

This article presents the results from a Spatial Augmented Reality (SAR) study which evaluated the cognitive cost of several predictive cues. Participants performed a validated procedural button pressing task, where the predictive cue annotations guided them to the upcoming task. While existing research has evaluated predictive cues based on their performance and self-rated mental effort, actual cognitive cost has yet to be investigated. To measure the user's brain activity, this study utilized electroencephalogram (EEG) recordings. Cognitive load was evaluated by measuring brain responses for a secondary auditory oddball task, with reduced brain responses to oddball tones expected when cognitive load in the primary task is highest. A simple monitor n-back task and procedural task comparing monitor versus SAR were conducted, followed by a version of the procedural task comparing the SAR predictive cues. Results from the brain responses were able to distinguish between performance enhancing cues with a high and low cognitive load. Electrical brain responses also revealed that having an arc or arrow guide towards the upcoming task required the least amount of mental effort.

This paper presents Shape Aware Haptic Retargeting, an extension of "state-of-the-art" haptic retargeting that is the first to support retargeted interaction between any part of the user’s hand and any part of the target object. In previous haptic retargeting algorithms, the maximum retargeting is applied only when the hand position aligns with the target position. Shape Aware Haptic Retargeting generalizes the distance computation process to instead consider the hand and target geometry. The shortest hand-target distance is then used to calculate the applied retargeting offset. This ensures the full amount of haptic retargeting is applied at the point of contact with the passive haptic regardless of contact position on the hand or target. We leverage existing geometry algorithms to implement three distance computation methods: Multi-Point, Primitive and Mesh Geometry, in addition to conventional single position approaches. These are evaluated through a set of simulated interactions instead of the single position representation used in previous haptic retargeting systems. The evaluation demonstrated all three approaches can provide improved interaction accuracy over a Point distance computation method, with Mesh Geometry being the most accurate and Primitive being the preferred method for combined performance and interaction accuracy.

Spatial Augmented Reality (SAR) is a useful tool for procedural tasks as virtual instructions can be co-located with the physical task. Predictive cue annotations have been utilized to further enhance user performance through SAR. These predictive cues have only been measured under ordinary circumstances. This paper aims to investigate predictive cues under a sub-optimal scenario by depriving users of sleep. Sleep deprivation is a common form of fatigue, which is known to have serious detriments on user performance. Based upon existing sleep literature, we expected predictive cue performance to degrade over time with sharp declines during the early hours of the morning. Despite these drops in performance, we hypothesized that having a predictive cue would benefit user performance in comparison to no cue. Results from a 62-hour sleep deprivation experiment indicated that providing SAR predictive cues was beneficial throughout sleep deprivation. Furthermore, having no predictive cue caused accuracy to decline earlier in the sleep deprivation period. From the predictive cues outlined in this paper, the line cue maintained the fastest response time and was least impacted by early morning performance declines.

This paper proposes a novel interface for virtual reality in which physical interface components are mapped to multiple virtual counterparts using haptic retargeting illusions. This gives virtual reality interfaces the ability to have correct haptic sensations for many virtual buttons although in the physical space there is only one. This is a generic system that can be applied to areas including design, interaction tasks, product prototype development and interactive games in virtual reality. The system presented extends existing retargeting algorithms to support asymmetric bimanual interactions. A new warp technique, called interface warp, was developed to support remapped virtual reality user interfaces. Through an experimental user study, we explore the effects of bimanual retargeting and the interface warp technique on task response time, errors, presence, perceived manipulation compared to unimanual (single handed) retargeting and other existing warp techniques. The results demonstrated faster task response time and less errors for the interface warp technique and shows no significant effect of bimanual interactions.

Previous research has demonstrated that Augmented Reality can reduce a user's task response time and mental effort when completing a procedural task. This paper investigates techniques to improve user performance and reduce mental effort by providing projector-based Spatial Augmented Reality predictive cues for future responses. The objective of the two experiments conducted in this study was to isolate the performance and mental effort differences from several different annotation cueing techniques for simple (Experiment 1) and complex (Experiment 2) button-pressing tasks. Comporting with existing cognitive neuroscience literature on prediction, attentional orienting, and interference, we hypothesized that for both simple procedural tasks and complex search-based tasks, having a visual cue guiding to the next task's location would positively impact performance relative to a baseline, no-cue condition. Additionally, we predicted that direction-based cues would provide a more significant positive impact than target-based cues. The results indicated that providing a line to the next task was the most effective technique for improving the users' task time and mental effort in both the simple and complex tasks.

Mobile devices such as some recent phones are now fitted with projection capabilities that support Spatial Augmented Reality (SAR) and require investigation to uncover new interaction possibilities. This paper presents a study measuring user performance in a search and select task using a tracked handheld projector and data tags, a 3D physical cue. This physical cue is used to mark the location of hidden SAR information. The experiment required participants to search for virtual symbols presented on two 5ft, multi-sided control panels. Two methods of presenting AR information were employed, SAR alone and SAR with the inclusion of physical cues to indicate the location of the information. The results showed that attaching data tags, compared to virtual content alone lowered the overall task completion time and reduced handheld projector movement. Subjectively, participants also preferred the combination of virtual data with data tags across both task variations

Industrial uses of Augmented Reality (AR) are growing, however their uses are consistently fashioned with an emphasis on consumption, delivering additional information to the worker to assist them in the completion of their job. A promising alternative is to allow user data creation during the actual process by the worker performing their duties. This not only allows spatially located annotations to be produced, it also allows an AR scene to be developed in-situ and in real-time. Tangible markers offer a physical interface while also creating physical containers to allow for fluent interactions. This form factor allows both attached and detached annotations, whilst allowing the creation of an AR scene during the process. This annotated scene will allow asynchronous collaboration to be conducted between multiple stakeholders, both locally and remotely. In this paper we discuss our reasoning behind such an approach, and present the current work on our prototype created to test and validate our proposition.

This paper focuses on enhancing the effectiveness of information visualisation approaches through the use of visual interaction interfaces (VIIs). We define VIIs as being graphical components which help users understand and interact with visual representations of a target environment (or data space). These types of components have been effectively used in computer-based games to enhance user experience. However, few such techniques are used in visualisation approaches designed to support decision-makers in real-world domains. A characterisation model, based on the capture and analysis of some 200 VIIs, has been developed to help describe and understand these types of visualisation components and hence support the transitioning of these techniques into future visualisation systems.

This paper introduces Imago, an environment that supports the prototyping, evaluation and transitioning of information visualisation approaches into practice. The approach is based on the use of an underlying semantic model of contextual and visualisation knowledge and integrated evaluation capabilities to aid the transitioning process. We discuss the use of Imago in relation to our experiences in researching and providing information visualisation approaches for command and control activities.

Development of high level Hardware Description Languages (HDLs) is an integral area of research in Reconfigurable Computing (RC). There is an apparent need to enhance the development tools available and achieve more abstraction in languages to make hardware development easier for software programmers. The lack of a unified hardware/software language and difficulties in system verification are also other issues currently being faced. To overcome these issues, we propose a Hardware Join Java language that uses the high level syntax and semantics of Java with additions to support reconfigurable hardware description. The language adopts Join Java semantics to allow specification of concurrency without the inherent complexity of Java's standard thread and monitor mechanisms. From a specification, hardware classes will be compiled and linked with VHDL source code. Standard Java classes can be used for the software part of an application and will serve as an interface.