Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Simple identification tools in FishBase

Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further development. It explores the possibility of a holistic and integrated computeraided strategy

Optisten illuusioiden käyttösovelluksia huonekalusuunnittelussa

Optical illusions prove that things are not always as they appear. This has inspired scientists, artists and architects throughout history. Applications of optical illusions have been used in fashion, in traffic planning and for camouflage on fabrics and vehicles. In this thesis, the author wants to examine if optical illusions could also be used as a structural element in furniture design. The theoretical basis for this thesis is compiled by collecting data about perception, optical art, other applications, meaning and building blocks of optical illusion. This creates the base for the knowledge of the theme and the phenomenon. The examination work is done by using the method of explorative prototyping: there are no answers when starting the project, but the process consists of planning and trying different ideas until one of them is deemed to be the right one to develop. The prototypes vary from simple sketches and 3D modeling exercises to 1:1 scale models. The author found six potential illusions and one concept was selected for further development based on criteria that were set before the work. The selected concept was used to create and develop WARP - a set of bar stools and shelves. The final objects combine the praxis of furniture design and optical illusions. They deceive the viewer, but the illusion is not only a visual effect; it also strengthens the structure. Other criteria for the final designs are its distinctiveness, newness and suitability for manufacturing.Optiset illuusiot ovat todiste, että kaikki tässä maailmassa ei ole sitä, miltä ne saattavat ensin näyttää. Tämä on inspiroinut tiedemiehiä, taiteilijoita ja arkkitehtejä kautta aikojen. Optisia illuusioita on käytetty hyväksi niin muodissa, liikennesuunnittelussa, kuin naamiointikeinona sodassa. Tässä opinnäytetyössä selvitetään, voiko optiset illuusiot olla myös rakenteellisena osana huonekalusuunnittelussa. Työn teoria koostuu kerättyyn tietoon havaitsemista, optisesta taiteesta, optisten illuusioiden merkityksestä, niiden käyttösovelluksista ja rakentumisesta. Tämä luo tietopohjan ko. aiheelle ja ilmiölle. Tutkimustyö toteutetaan käyttäen tutkivan koemallintamisen (explorative prototyping) keinoja: Työn alkaessa ei ole vastauksia, vaan erilaisia ideoita suunnitellaan ja kokeillaan, kunnes löydetään yksi, joka vaikuttaa oikealta jatkokehitettäväksi. Prototyypit vaihtelevat yksinkertaisista luonnoksista ja 3D-mallinnuksista kokonaisiin 1:1 malleihin. Kuudesta illuusiosta yksi konsepti valitaan jatkokehitettäväksi perustuen työn alussa määriteltyihin kriteereihin. Valitun konseptin tuotekehityksen myötä syntyy WARP -baarijakkara ja -hylly, joissa yhdistyy käytänteet huonekalusuunnittelusta ja optisista illuusioista. Kalusteet hämäävät katsojaa, mutta illuusio ei ole vain visuaalinen efekti, vaan se lujittaa myös rakenteen. Kriteereihin kuuluu myös tuotteiden huomioarvo, uudenlaisuus ja tuotantokelpoisuus

Integration of multiple data types in 3-D immersive virtual reality (VR) environments

Intelligent sensors have begun to play a key part in the monitoring and maintenance of complex infrastructures. Sensors have the capability not only to provide raw data, but also provide information by indicating the reliability of the measurements. The effect of this added information is a voluminous increase in the total data that is gathered. If an operator is required to perceive the state of a complex system, novel methods must be developed for sifting through enormous data sets. Virtual reality (VR) platforms are proposed as ideal candidates for performing this task-- a virtual world will allow the user to experience a complex system that is gathering a multitude of sensor data and are referred as Integrated Awareness models. This thesis presents techniques for visualizing such multiple data sets, specifically - graphical, measurement and health data inside a 3-D VR environment. The focus of this thesis is to develop pathways to generate the required 3-D models without sacrificing visual fidelity. The tasks include creating the visual representation, integrating multi-sensor measurements, creating user-specific visualizations and a performance evaluation of the completed virtual environment

Towards Energy Efficient Mobile Eye Tracking for AR Glasses through Optical Sensor Technology

After the introduction of smartphones and smartwatches, Augmented Reality (AR) glasses are considered the next breakthrough in the field of wearables. While the transition from smartphones to smartwatches was based mainly on established display technologies, the display technology of AR glasses presents a technological challenge. Many display technologies, such as retina projectors, are based on continuous adaptive control of the display based on the user’s pupil position. Furthermore, head-mounted systems require an adaptation and extension of established interaction concepts to provide the user with an immersive experience. Eye-tracking is a crucial technology to help AR glasses achieve a breakthrough through optimized display technology and gaze-based interaction concepts. Available eye-tracking technologies, such as Video Oculography (VOG), do not meet the requirements of AR glasses, especially regarding power consumption, robustness, and integrability. To further overcome these limitations and push mobile eye-tracking for AR glasses forward, novel laser-based eye-tracking sensor technologies are researched in this thesis. The thesis contributes to a significant scientific advancement towards energy-efficientmobile eye-tracking for AR glasses. In the first part of the thesis, novel scanned laser eye-tracking sensor technologies for AR glasses with retina projectors as display technology are researched. The goal is to solve the disadvantages of VOG systems and to enable robust eye-tracking and efficient ambient light and slippage through optimized sensing methods and algorithms. The second part of the thesis researches the use of static Laser Feedback Interferometry (LFI) sensors as low power always-on sensor modality for detection of user interaction by gaze gestures and context recognition through Human Activity Recognition (HAR) for AR glasses. The static LFI sensors can measure the distance to the eye and the eye’s surface velocity with an outstanding sampling rate. Furthermore, they offer high integrability regardless of the display technology. In the third part of the thesis, a model-based eye-tracking approach is researched based on the static LFI sensor technology. The approach leads to eye-tracking with an extremely high sampling rate by fusing multiple LFI sensors, which enables methods for display resolution enhancement such as foveated rendering for AR glasses and Virtual Reality (VR) systems. The scientific contributions of this work lead to a significant advance in the field of mobile eye-tracking for AR glasses through the introduction of novel sensor technologies that enable robust eye tracking in uncontrolled environments in particular. Furthermore, the scientific contributions of this work have been published in internationally renowned journals and conferences

Tangible auditory interfaces : combining auditory displays and tangible interfaces

Bovermann T. Tangible auditory interfaces : combining auditory displays and tangible interfaces. Bielefeld (Germany): Bielefeld University; 2009.Tangible Auditory Interfaces (TAIs) investigates into the capabilities of the interconnection of Tangible User Interfaces and Auditory Displays. TAIs utilise artificial physical objects as well as soundscapes to represent digital information. The interconnection of the two fields establishes a tight coupling between information and operation that is based on the human's familiarity with the incorporated interrelations. This work gives a formal introduction to TAIs and shows their key features at hand of seven proof of concept applications

Segmentation of neuroanatomy in magnetic resonance images

Segmentation in neurological Magnetic Resonance Imaging (MRI) is necessary for volume measurement, feature extraction and for the three-dimensional display of neuroanatomy. This thesis proposes several automated and semi-automated methods which offer considerable advantages over manual methods because of their lack of subjectivity, their data reduction capabilities, and the time savings they give. Work has concentrated on the use of dual echo multi-slice spin-echo data sets in order to take advantage of the intrinsically multi-parametric nature of MRI. Such data is widely acquired clinically and segmentation therefore does not require additional scans. The literature has been reviewed. Factors affecting image non-uniformity for a modem 1.5 Tesla imager have been investigated. These investigations demonstrate that a robust, fast, automatic three-dimensional non-uniformity correction may be applied to data as a pre-processing step. The merit of using an anisotropic smoothing method for noisy data has been demonstrated. Several approaches to neurological MRI segmentation have been developed. Edge-based processing is used to identify the skin (the major outer contour) and the eyes. Edge-focusing, two threshold based techniques and a fast radial CSF identification approach are proposed to identify the intracranial region contour in each slice of the data set. Once isolated, the intracranial region is further processed to identify CSF, and, depending upon the MRI pulse sequence used, the brain itself may be sub-divided into grey matter and white matter using semiautomatic contrast enhancement and clustering methods. The segmentation of Multiple Sclerosis (MS) plaques has also been considered. The utility of the stack, a data driven multi-resolution approach to segmentation, has been investigated, and several improvements to the method suggested. The factors affecting the intrinsic accuracy of neurological volume measurement in MRI have been studied and their magnitudes determined for spin-echo imaging. Geometric distortion - both object dependent and object independent - has been considered, as well as slice warp, slice profile, slice position and the partial volume effect. Finally, the accuracy of the approaches to segmentation developed in this thesis have been evaluated. Intracranial volume measurements are within 5% of expert observers' measurements, white matter volumes within 10%, and CSF volumes consistently lower than the expert observers' measurements due to the observers' inability to take the partial volume effect into account

Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons