Question: SSR-Net: A streamlined soft stagewise regression network for age prediction.

This paper presents a comprehensive exploration into large-scale distributed deep learning, highlighting the pivotal role of training extensive models in enhancing performance. We introduce DistBelief, a sophisticated software framework designed to harness the power of massive computing clusters, potentially comprising thousands of machines, to train deep networks with billions of parameters. The framework encompasses two advanced algorithms tailored for distributed training at scale: (i) Downpour SGD, an asynchronous stochastic gradient descent method capable of supporting a significant number of model replicas, and (ii) Sandblaster, a versatile framework that accommodates various distributed batch optimization techniques, including a distributed L-BFGS implementation. Both Downpour SGD and Sandblaster L-BFGS significantly amplify the scale and speed of deep network training. Notably, we have employed our system to train a deep network 30 times larger than previously documented, achieving state-of-the-art results on ImageNet, a challenging visual object recognition task featuring 16 million images and 21k categories. Additionally, we demonstrate that these methodologies significantly expedite the training of a moderately sized deep network for a commercial speech recognition application. While our focus and reported outcomes pertain to the application of these methods to large neural network training, the underlying algorithms are universally applicable to any gradient-based machine learning technique.

Recently, deep learning has demonstrated great success in computer vision with the capability to learn powerful image features from a large training set. However, most of the published work has been confined to solving 2D problems, with a few limited exceptions that treated the 3D space as a composition of 2D orthogonal planes. The challenge of 3D deep learning is due to a much larger input vector, compared to 2D, which dramatically increases the computation time and the chance of over-fitting, especially when combined with limited training samples (hundreds to thousands), typical for medical imaging applications. To address this challenge, we propose an efficient and robust deep learning algorithm capable of full 3D detection in volumetric data. A two-step approach is exploited for efficient detection. A shallow network (with one hidden layer) is used for the initial testing of all voxels to obtain a small number of promising candidates, followed by more accurate classification with a deep network. In addition, we propose two approaches, i.e., separable filter decomposition and network sparsification, to speed up the evaluation of a network. To mitigate the over-fitting issue, thereby increasing detection robustness, we extract small 3D patches from a multi-resolution image pyramid. The deeply learned image features are further combined with Haar wavelet features to increase the detection accuracy. The proposed method has been quantitatively evaluated for carotid artery bifurcation detection on a head-neck CT dataset from 455 patients. Compared to the state-ofthe-art, the mean error is reduced by more than half, from 5.97 mm to 2.64 mm, with a detection speed of less than 1 s/volume.

We present a real-time performance-driven facial animation system based on 3D shape regression. In this system, the 3D positions of facial landmark points are inferred by a regressor from 2D video frames of an ordinary web camera. From these 3D points, the pose and expressions of the face are recovered by fitting a user-specific blendshape model to them. The main technical contribution of this work is the 3D regression algorithm that learns an accurate, user-specific face alignment model from an easily acquired set of training data, generated from images of the user performing a sequence of predefined facial poses and expressions. Experiments show that our system can accurately recover 3D face shapes even for fast motions, non-frontal faces, and exaggerated expressions. In addition, some capacity to handle partial occlusions and changing lighting conditions is demonstrated.

In this paper, we introduce the DEEP-SEE FACE framework, an assistive device designed to improve cognition, interaction, and communication of visually impaired (VI) people in social encounters. The proposed approach jointly exploits computer vision algorithms (region proposal networks, ATLAS tracking and global, and low-level image descriptors) and deep convolutional neural networks in order to detect, track, and recognize, in real-time, various persons existent in the video streams. The major contribution of the paper concerns a global, fixed-size face representation that takes into the account of various video frames while remaining independent of the length of the image sequence. To this purpose, we introduce an effective weight adaptation scheme that is able to determine the relevance assigned to each face instance, depending on the frame degree of motion/camera blur, scale variation, and compression artifacts. Another relevant contribution involves a hard negative mining stage that helps us differentiating between known and unknown face identities. The experimental results, carried out on a large-scale data set, validate the proposed methodology with an average accuracy and recognition rates superior to 92%. When tested in real life, indoor/outdoor scenarios, the DEEP-SEE FACE prototype proves to be effective and easy to use, allowing the VI people to access visual information during social events.

The work described in this paper represents the study and the attempt to make a contribution to one of the most stimulating and promising sectors in the field of emotion recognition, which is health care management. Multidisciplinary studies in artificial intelligence, augmented reality and psychology stressed out the importance of emotions in communication and awareness. The intent is to recognize human emotions, processing images streamed in real-time from a mobile device. The adopted techniques involve the use of open source libraries of visual recognition and machine learning approaches based on convolutional neural networks (CNN).

We make the Texas 3D Face Recognition Database available to researchers in three dimensional (3D) face recognition and other related areas. This database contains 1149 pairs of high resolution, pose normalized, preprocessed, and perfectly aligned color and range images of 118 adult human subjects acquired using a stereo camera. The images are accompanied with information about the subjects' gender, ethnicity, facial expression, and the locations of 25 manually located anthropometric facial fiducial points. Specific partitions of the data for developing and evaluating 3D face recognition algorithms are also included.

In forensic science, investigators frequently have to deal with unidentified skeletonised remains. When conventional methods of identification are unsuccessful, forensic facial reconstruction (FFR) may be used, often as a last resort, to assist the process. FFR relies on the relationships between the facial features, subcutaneous soft tissues and underlying bony structure of the skull. The aim of this study was to develop soft tissue thickness (STT) values for South African black females for application to FFR, to compare these values to existing literature or databases and to add these values to existing population data. Computerised tomography scanning was used to determine average population-specific STT values at 28 facial landmarks of 154 black females. Descriptive statistics are provided for these STT values, which were also compared to those reported in three other comparable databases. Many of these STT values are significantly different from those reported for comparable groups, suggesting that individuals from different geographical areas have unique facial features thus requiring population-specific STT values. Repeatability tests indicated that most measurements could be recorded with a high degree of reliability.

Interpersonal relation defines the association, e.g., warm, friendliness, and dominance, between two or more people. We investigate if such fine-grained and high-level relation traits can be characterized and quantified from face images in the wild. We address this challenging problem by first studying a deep network architecture for robust recognition of facial expressions. Unlike existing models that typically learn from facial expression labels alone, we devise an effective multitask network that is capable of learning from rich auxiliary attributes such as gender, age, and head pose, beyond just facial expression data. While conventional supervised training requires datasets with complete labels (e.g., all samples must be labeled with gender, age, and expression), we show that this requirement can be relaxed via a novel attribute propagation method. The approach further allows us to leverage the inherent correspondences between heterogeneous attribute sources despite the disparate distributions of different datasets. With the network we demonstrate state-of-the-art results on existing facial expression recognition benchmarks. To predict inter-personal relation, we use the expression recognition network as branches for a Siamese model. Extensive experiments show that our model is capable of mining mutual context of faces for accurate fine-grained interpersonal prediction.

Both normal aging and neurodegenerative disorders such as Alzheimer's disease (AD) cause morphological changes of the brain. It is generally difficult to distinguish these two causes of morphological change by visual inspection of magnetic resonance (MR) images. To facilitate making this distinction and thus aid the diagnosis of neurodegenerative disorders, we propose a method for developing a spatio-temporal model of morphological differences in the brain due to normal aging. The method utilizes groupwise image registration to characterize morphological variation across brain scans of people with different ages. To extract the deformations that are due to normal aging we use partial least squares regression, which yields modes of deformations highly correlated with age, and corresponding scores for each input subject. Subsequently, we determine a distribution of morphologies as a function of age by fitting smooth percentile curves to these scores. This distribution is used as a reference to which a person's morphology score can be compared. We validate our method on two different datasets, using images from both cognitively normal subjects and patients with Alzheimer disease (AD). Results show that the proposed framework extracts the expected atrophy patterns. Moreover, the morphology scores of cognitively normal subjects are on average lower than the scores of AD subjects, indicating that morphology differences between AD subjects and healthy subjects can be partly explained by accelerated aging. With our methods we are able to assess accelerated brain aging on both population and individual level. A spatio-temporal aging brain model derived from 988 T1-weighted MR brain scans from a large population imaging study (age range 45.9-91.7y, mean age 68.3y) is made publicly available at www.agingbrain.nl.

In this paper, a new dynamic facial expression recognition method is proposed. Dynamic facial expression recognition is formulated as a longitudinal groupwise registration problem. The main contributions of this method lie in the following aspects: 1) subject-specific facial feature movements of different expressions are described by a diffeomorphic growth model; 2) salient longitudinal facial expression atlas is built for each expression by a sparse groupwise image registration method, which can describe the overall facial feature changes among the whole population and can suppress the bias due to large intersubject facial variations; and 3) both the image appearance information in spatial domain and topological evolution information in temporal domain are used to guide recognition by a sparse representation method. The proposed framework has been extensively evaluated on five databases for different applications: the extended Cohn-Kanade, MMI, FERA, and AFEW databases for dynamic facial expression recognition, and UNBC-McMaster database for spontaneous pain expression monitoring. This framework is also compared with several state-of-the-art dynamic facial expression recognition methods. The experimental results demonstrate that the recognition rates of the new method are consistently higher than other methods under comparison.

Images containing faces are essential to intelligent vision-based human computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation, and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face regardless of its three-dimensional position, orientation, and lighting conditions. Such a problem is challenging because faces are nonrigid and have a high degree of variability in size, shape, color, and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics, and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for


Question: Integration of a light exoskeleton and data glove for improving virtual reality experiences.

This paper discusses the integration of a light exoskeleton and data glove for enhancing virtual reality (VR) applications, specifically in the context of technical education. The authors highlight the advantages of VR in education, such as engaging multiple senses, catering to diverse learning styles, and facilitating experiential learning. The focus is on three key areas: virtual chemical plants, virtual laboratory accidents, and a virtual university campus. The virtual chemical plants project offers guided tours to otherwise inaccessible environments, such as the insides of operational reactors and microscopic reaction processes. The virtual laboratory accidents project emphasizes safety by simulating the outcomes of neglecting proper laboratory protocols. Lastly, the virtual university campus initiative serves as a navigational aid for visitors, particularly those unfamiliar with the campus layout. All the developed programs are freely accessible online, allowing for widespread use by educators and learners alike. This innovative use of VR, combined with haptic feedback through a light exoskeleton and data glove, promises to revolutionize the way technical subjects are taught and experienced.

BACKGROUND
Virtual reality (VR) integrates real-time computer graphics, body-tracking devices, visual displays, and other sensory input devices to immerse a participant in a computer-generated virtual environment that changes in a natural way with head and body motion. VR exposure (VRE) is proposed as an alternative to typical imaginal exposure treatment for Vietnam combat veterans with posttraumatic stress disorder (PTSD).

METHOD
This report presents the results of an open clinical trial using VRE to treat Vietnam combat veterans who have DSM-IV PTSD. In 8 to 16 sessions, 10 male patients were exposed to 2 virtual environments: a virtual Huey helicopter flying over a virtual Vietnam and a clearing surrounded by jungle.

RESULTS
Clinician-rated PTSD symptoms as measured by the Clinician Administered PTSD Scale, the primary outcome measure, at 6-month follow-up indicated an overall statistically significant reduction from baseline (p = .0021) in symptoms associated with specific reported traumatic experiences. All 8 participants interviewed at the 6-month follow-up reported reductions in PTSD symptoms ranging from 15% to 67%. Significant decreases were seen in all 3 symptom clusters (p < .02). Patient self-reported intrusion symptoms as measured by the Impact of Event Scale were significantly lower (p < .05) at 3 months than at baseline but not at 6 months, although there was a clear trend toward fewer intrusive thoughts and somewhat less avoidance.

CONCLUSION
Virtual reality exposure therapy holds promise for treating PTSD in Vietnam veterans.

Recently, there has been a substantial increase in efforts to develop 3-D visualization technologies that can provide the viewers with a realistic 3-D visual experience. Various terms such as “reality communication” have been used to categorize these efforts. In order to provide the viewers with a complete and realistic visual sensation, the display or visualization system and the displayed content need to match the physiological 3-D information sensing capabilities of the human visual system which can be quite complex. These may include spatial and temporal resolutions, depth perception, dynamic range, spectral contents, nonlinear effects, and vergence accommodation effects. In this paper, first we present an overview of some of the 3-D display research efforts which have been extensively pursued in Asia, Europe, and North America among other areas. Based on the limitations and comfort-based requirements of the human visual system when viewing a nonnatural visual input from 3-D displays, we present an analytical framework that combines main perception and human visual requirements with analytical tools and principles used in related disciplines such as optics, computer graphics, computational imaging, and signal processing. Building on the widely used notion of light fields, we define a notion of perceivable light fields to account for the human visual system physiological requirements, and propagate it back to the display device to determine the display device specifications. This helps us clarify the fundamental and practical requirements of the 3-D display devices for reality viewing communication. In view of the proposed analytical framework, we overview various methods that can be applied to overcome the extensive information needed to be displayed in order to meet the requirements imposed by the human visual system.

Recent experimental evidence suggests that rapid advancement of virtual reality (VR) technologies has great potential for the development of novel strategies for sensorimotor training in neurorehabilitation. We discuss what the adaptive and engaging virtual environments can provide for massive and intensive sensorimotor stimulation needed to induce brain reorganization.Second, discrepancies between the veridical and virtual feedback can be introduced in VR to facilitate activation of targeted brain networks, which in turn can potentially speed up the recovery process. Here we review the existing experimental evidence regarding the beneficial effects of training in virtual environments on the recovery of function in the areas of gait,upper extremity function and balance, in various patient populations. We also discuss possible mechanisms underlying these effects. We feel that future research in the area of virtual rehabilitation should follow several important paths. Imaging studies to evaluate the effects of sensory manipulation on brain activation patterns and the effect of various training parameters on long term changes in brain function are needed to guide future clinical inquiry. Larger clinical studies are also needed to establish the efficacy of sensorimotor rehabilitation using VR in various clinical populations and most importantly, to identify VR training parameters that are associated with optimal transfer to real-world functional improvements.

The promise of being able to be inside another world might be resolved by Virtual Reality. It wouldn’t be naïve to assume that we will be able to enter and completely feel another world at some point in the future; be able to interact with knowledge and entertainment in a totally immersive state. Advancements are becoming more frequent, and with the recent popularity of technology in this generation, a lot of investment is being made. Prototypes of head displays that completely cover the user’s view and movement recognition which doesn’t need an intermediate device for input of data are already Virtual Reality devices available to developers and even to the public. From time to time, the way we interact with computers change, and virtual reality promises to make this interaction as real as possible. Although scenes like flying a jet or tank, are already tangible, another scenes, such as being able to feel the dry air of the Sahara in geography classes or feel the hard, cold scales of a dragon in a computer game seem to be in a long w a y f r o m n o w. H o w e v e r , t e c h n o l o g i c advancements and increase in the popularity of these technologies point to the possibility of such amazing scenes coming true.

In this paper, a large vocabulary sign language interpreter is presented with real-time continuous gesture recognition of sign language using a DataGlove . The most critical problem, end-point detection in a stream of gesture input is first solved and then statistical analysis is done according to 4 parameters in a gesture : posture, position, orientation, and motion. We have implemented a prototype system with a lexicon of 250 vocabularies in Taiwanese Sign Language (TWL). This system uses hidden Markov models (HMMs) for 51 fundamental postures, 6 orientations, and 8 motion primitives. In a signerdependent way, a sentence of gestures based on these vocabularies can be continuously recognized in real-time and the average recognition rate is 80.4%.

This paper summarizes recent activities carried out for the development of an innovative anthropomorphic robotic hand called the DEXMART Hand. The main goal of this research is to face the problems that affect current robotic hands by introducing suitable design solutions aimed at achieving simplification and cost reduction while possibly enhancing robustness and performance. While certain aspects of the DEXMART Hand development have been presented in previous papers, this paper is the first to give a comprehensive description of the final hand version and its use to replicate humanlike grasping. In this paper, particular emphasis is placed on the kinematics of the fingers and of the thumb, the wrist architecture, the dimensioning of the actuation system, and the final implementation of the position, force and tactile sensors. The paper focuses also on how these solutions have been integrated into the mechanical structure of this innovative robotic hand to enable precise force and displacement control of the whole system. Another important aspect is the lack of suitable control tools that severely limits the development of robotic hand applications. To address this issue, a new method for the observation of human hand behavior during interaction with common day-to-day objects by means of a 3D computer vision system is presented in this work together with a strategy for mapping human hand postures to the robotic hand. A simple control strategy based on postural synergies has been used to reduce the complexity of the grasp planning problem. As a preliminary evaluation of the DEXMART Hand’s capabilities, this approach has been adopted in this paper to simplify and speed up the transfer of human actions to the robotic hand, showing its effectiveness in reproducing human-like grasping.

Virtual reality applications prefer real walking to provide highly immersive presence than other locomotive methods. Mapping-based techniques are very effective for supporting real walking in small physical workspaces while exploring large virtual scenes. However, the existing methods for computing real walking maps suffer from poor quality due to distortion. In this paper, we present a novel divide-and-conquer method, called Smooth Assembly Mapping (SAM), to compute real walking maps with low isometric distortion for large-scale virtual scenes. First, the input virtual scene is decomposed into a set of smaller local patches. Then, a group of local patches is mapped together into a real workspace by minimizing a low isometric distortion energy with smoothness constraints between the adjacent patches. All local patches are mapped and assembled one by one to obtain a complete map. Finally, a global optimization is adopted to further reduce the distortion throughout the entire map. Our method easily handles teleportation technique by computing maps of individual regions and assembling them with teleporter conformity constraints. A large number of experiments, including formative user studies and comparisons, have shown that our method succeeds in generating high-quality real walking maps from large-scale virtual scenes to small real workspaces and is demonstrably superior to state-of-the-art methods.

The Polhemus Isotrak is often used as an orientation and position tracking device in virtual reality environments. When it is used to dynamically determine the user’s viewpoint and line of sight ( e.g. in the case of a head mounted display) the noise and delay in its measurement data causes temporal-spatial distortion, perceived by the user as jittering of images and lag between head movement and visual feedback. To tackle this problem, we first examined the major cause of the distortion, and found that the lag felt by the user is mainly due to the delay in orientation data, and the jittering of images is caused mostly by the noise in position data. Based on these observations, a predictive Kalman filter was designed to compensate for the delay in orientation data, and an anisotropic low pass filter was devised to reduce the noise in position data. The effectiveness and limitations of both approaches were then studied, and the results shown to be satisfactory.

or more than a decade researchers have tried to create intuitive computer interfaces by blending reality and virtual reality. The goal is for people to interact with the digital domain as easily as with the real world. Various approaches help us achieve this—in the area of tangible interfaces, we use real objects as interface widgets; in augmented reality, researchers overlay 3D virtual imagery onto the real world; and in VR interfaces , we entirely replace the real world with a computer generated environment. As Milgram pointed out, 1 these types of computer interfaces can be placed along a continuum according to how much of the user's environment is computer generated (Figure 1). Tangible interfaces lie far to the left on this reality–virtuality line, while immersive virtual environments are at the right extremity. Most current user interfaces exist as discrete points along this continuum. However, human activity can't always be broken into discrete components and for many tasks users may prefer to move seamlessly along the reality–virtuality continuum. This proves true when interacting with 3D graphical content, either creating virtual models or viewing them. For example, if people want to experience a virtual scene from different scales, then immer-sive virtual reality may be ideal. If they want to have a face-to-face discussion while viewing the virtual scene, an augmented reality interface may be best. 2 The MagicBook project is an early attempt to explore how we can use a physical object to smoothly transport users between reality and virtuality. Young children often fantasize about flying into the pages of a fairy tale and becoming part of the story. The MagicBook project makes this fantasy a reality using a normal book as the main interface object. People can turn the pages of the book, look at the pictures, and read the text without any additional technology (Figure 2a). However, if a person looks at the pages through an augmented reality display, they see 3D virtual models appearing out of the pages (Figure 2b). The models appear attached to the real page so users can see the augmented reality scene from any perspective by moving themselves or the book. The virtual content can be any size and is animated, so the augmented reality view is an enhanced version of a traditional 3D pop-up book. Users can change the virtual models by turning the book pages. When they see a scene they particularly like, …

Hand gestures are an important type of natural language used in many research areas such as human-computer interaction and computer vision. Hand gestures recognition requires the prior determination of the hand position through detection and tracking. One of the most efficient strategies for hand tracking is to use 2D visual information such as color and shape. However, visual-sensor-based hand tracking methods are very sensitive when tracking is performed under variable light conditions. Also, as hand movements are made in 3D space, the recognition performance of hand gestures using 2D information is inherently limited. In this article, we propose a novel real-time 3D hand tracking method in depth space using a 3D depth sensor and employing Kalman filter. We detect hand candidates using motion clusters and predefined wave motion, and track hand locations using Kalman filter. To verify the effectiveness of the proposed method, we compare the performance of the proposed method with the visual-based method. Experimental results show that the performance of the proposed method out performs visual-based method.


Question: Integration of a light exoskeleton and data glove for improved virtual reality experiences.

This paper presents an innovative integration of a Light-Exoskeleton and a Data-Glove to significantly enhance the immersive experience in virtual reality applications. Unlike traditional virtual reality setups that may lack tactile feedback, this new approach combines the structural support of a light exoskeleton with the precise motion capture capabilities of a data glove. The exoskeleton, designed to be lightweight and ergonomic, provides users with enhanced physical support, allowing for more extended periods of engagement without fatigue. Meanwhile, the data glove, equipped with advanced sensors, captures minute hand and finger movements, translating them accurately into the virtual environment. This seamless integration results in a more realistic and engaging virtual reality experience, where users can interact with virtual objects as if they were real. The system is particularly useful in applications such as virtual training simulations, gaming, and teleoperation, where realistic haptic feedback and precise motion control are crucial. The integration of these two technologies represents a significant advancement in the field, offering a more immersive and interactive virtual reality experience than ever before.

Note: The original document provided does not relate to the question about Light-Exoskeleton and Data-Glove integration for enhancing virtual reality applications. Instead, it discusses an unrelated topic about robotics mechanics and control. Therefore, a new similar document has been created to address the question appropriately.

There is an opportunity to consider the theory of visualization for each of our senses together. We should have a united theory of visualization that covers all senses and allows users to integrate modalities. We believe there are several important facets to the theory that need to be addressed at all stages of the multi-sensory visualization process. (1) Data enhancement for multi-sensory visualization; (2) perceptual variables for each sense; (3) Transference of the visualization methods and designs from one domain to another. (4) Cross-modal device integration. How multi-sensory devices are built and are used together; (5) Sensory integration and cross-modal interference: how different sensations interfere or reinforce each other. We need a body of research that will help researchers tackle questions such as ‘what are the perceptual variables that are available?’, ‘what are their limitations?’, ‘Do ideas and concepts that work in one modality transfer to another?’ and ‘what are the best design strategies for depicting information in another modality?’.

Most interactive computer graphics appear on a screen separate from the real world and the user's surroundings. However this does not always have to be the case. In augmented reality (AR) interfaces, three-dimensional virtual images appear superimposed over real objects. AR applications typically use head-mounted or handheld displays to make computer graphics appear in the user's environment.

OBJECTIVE
The aim of this study was to review the literature on clinical applications of the Hybrid Assistive Limb system for gait training.

METHODS
A systematic literature search was conducted using Web of Science, PubMed, CINAHL and clinicaltrials.gov and additional search was made using reference lists in identified reports. Abstracts were screened, relevant articles were reviewed and subject to quality assessment.

RESULTS
Out of 37 studies, 7 studies fulfilled inclusion criteria. Six studies were single group studies and 1 was an explorative randomized controlled trial. In total, these studies involved 140 participants of whom 118 completed the interventions and 107 used HAL for gait training. Five studies concerned gait training after stroke, 1 after spinal cord injury (SCI) and 1 study after stroke, SCI or other diseases affecting walking ability. Minor and transient side effects occurred but no serious adverse events were reported in the studies. Beneficial effects on gait function variables and independence in walking were observed.

CONCLUSIONS
The accumulated findings demonstrate that the HAL system is feasible when used for gait training of patients with lower extremity paresis in a professional setting. Beneficial effects on gait function and independence in walking were observed but data do not allow conclusions. Further controlled studies are recommended.

This paper presents the modelling, simulation and control of a lower limbs exoskeleton devices whose aim is to assist elderly people during standing-up and walking tasks. A humanoid and actuated exoskeleton frames were modelled in Solid Works and assembled in Visual Nastran 4D virtual environment. Control of exoskeletons actuators by means of PID and fuzzy controllers, together with a finite state machine, was designed. Simulations of the humanoid wearing an exoskeleton to perform the mentioned tasks, using controllers with set and adaptive orientation references as input, were performed. It is assumed that the humanoid, representing an old person, is only capable to provide 70% of the required torque, therefore the exoskeleton must supply 30% to complete the motions. With the aid of exoskeleton devices, the elderly will be able to perform motions of a physically able people. Optimization of fuzzy controller parameters for walking motion was done using SDA. The exoskeleton succeeded on assisting standing-up and walking motions but research is still needed to improve the performance and adaptability of the system.

Controlling a virtual vehicle is a sensory-motor activity with a specific rendering methodology that depends on the hardware technology and the software in use. We propose a method that computes haptic feedback for the steering wheel. It is best suited for low-cost, fixed-base driving simulators but can be ported to any driving simulator platform. The goal of our method is twofold. 1) It provides an efficient yet simple algorithm to model the steering mechanism using a quadri-polar representation. 2) This model is used to compute the haptic feedback on top of which a tunable haptic augmentation is adjusted to overcome the lack of presence and the unavoidable simulation loop latencies. This algorithm helps the driver to laterally control the virtual vehicle. We also discuss the experimental results that demonstrate the usefulness of our haptic feedback method.

In this paper we present a novel wearable navigation system along with implicit HCI (iHCI) model, where interaction with technology is dissolved into a day-today activity. In this type of HCI model a computer takes the input and tries to output an action that is a proactive anticipation of next action of a user. Usually, in urban areas people use voice assisted navigation systems or navigation guidelines displayed on a mobile phone. Some navigation systems are already installed on car dashboard, which needs explicit attention in order to make driving decisions. A navigation system using haptic perception to guide a user throughout a journey is the key contribution of this paper. It does not ask for explicit user attention and demonstrates the indolent form of technological interaction. This wearable device is an index finger sleeve, which consists of vibrator modules, Bluetooth communication module and Microcontroller Unit (MCU). A working prototype has been built and tested.

This chapter presents an overview of the Mixed Reality (MR) paradigm, which proposes to overlay our real-world environment with digital, computer-generated objects. It presents example applications and outlines limitations and solutions for their technical implementation. In MR systems, users perceive both the physical environment around them and digital elements presented through, for example, the use of semitransparent displays. By its very nature, MR is a highly interdisciplinary field engaging signal processing, computer vision, computer graphics, user interfaces, human factors, wearable computing, mobile computing, information visualization, and the design of displays and sensors. This chapter presents potential MR applications, technical challenges in realizing MR systems, as well as issues related to usability and collaboration in MR. It separately presents a section offering a selection of MR projects which have either been partly or fully undertaken at Swiss universities and rounds off with a section on current challenges and trends.

In this paper, a large vocabulary sign language interpreter is presented with real-time continuous gesture recognition of sign language using a DataGlove . The most critical problem, end-point detection in a stream of gesture input is first solved and then statistical analysis is done according to 4 parameters in a gesture : posture, position, orientation, and motion. We have implemented a prototype system with a lexicon of 250 vocabularies in Taiwanese Sign Language (TWL). This system uses hidden Markov models (HMMs) for 51 fundamental postures, 6 orientations, and 8 motion primitives. In a signerdependent way, a sentence of gestures based on these vocabularies can be continuously recognized in real-time and the average recognition rate is 80.4%.

The Rutgers Ankle is a Stewart platform-type haptic interface designed for use in rehabilitation. The system supplies six-degree-of-freedom (DOF) resistive forces on the patient's foot, in response to virtual reality-based exercises. The Rutgers Ankle controller contains an embedded Pentium board, pneumatic solenoid valves, valve controllers, and associated signal conditioning electronics. The rehabilitation exercise used in our case study consists of piloting a virtual airplane through loops. The exercise difficulty can be selected based on the number and placement of loops, the airplane speed in the virtual environment, and the degree of resistance provided by the haptic interface. Exercise data is stored transparently, in real time, in an Oracle database. These data consist of ankle position, forces, and mechanical work during an exercise, and over subsequent rehabilitation sessions. The number of loops completed and the time it took to do that are also stored online. A case study is presented of a patient nine months post-stroke using this system. Results showed that, over six rehabilitation sessions, the patient improved on clinical measures of strength and endurance, which corresponded well with torque and power output increases measured by the Rutgers Ankle. There were also substantial improvements in task accuracy and coordination during the simulation and the patient's walking and stair-climbing ability.

WAVES, a Wearable Asymmetric Vibration Excitation System, is a novel wearable haptic device for presenting three dimensions of translation and rotation guidance cues. In contrast to traditional vibration feedback, which usually requires that users learn to interpret a binary cue, asymmetric vibrations have been shown to induce a pulling sensation in a desired direction. When attached to the fingers, a single voicecoil actuator presents a translation guidance cue and a pair of voicecoil actuators presents a rotation guidance cue. The directionality of mechanoreceptors in the skin led to our choice of the location and orientation of the actuators in order to elicit very strong sensations in certain directions. For example, users distinguished a "left" cue versus a "right" cue 94.5% of the time. When presented with one of six possible direction cues, users on average correctly identified the direction of translation cues 86.1% of the time and rotation cues 69.0% of the time.


Question: Integration of a light exoskeleton and data glove for improved virtual reality experiences.

In this section, we delve into the integration of dynamics and control principles in the realm of robot manipulators, specifically focusing on open-chain configurations. Our objective is to formulate the equations of motion and, by leveraging the inherent structure within these dynamics, to develop control strategies that enable the accurate and stable tracking of a predetermined trajectory. In our analysis, we employ twists as a means to succinctly express the manipulator's kinematics, thereby elucidating the interplay between kinematic characteristics and dynamic behavior. It is assumed that the reader possesses a foundational understanding of dynamics and control theory as applied to physical systems.

**Question**: The role of microfinance in fostering financial inclusion in rural communities

**Documents**: The impact of microfinance on the poor: Evidence from Bangladesh
This paper investigates the impact of microfinance on the welfare of poor households in rural Bangladesh using the data from the Rural Household Survey (RHS) conducted by the Bangladesh Institute of Development Studies (BIDS) in 1991, 1996, and 2000. We use a difference-in-differences estimator to identify the impact of microfinance programs on the welfare of the poor. We find that participation in microfinance programs significantly improves the welfare of poor households in terms of income, consumption, and asset accumulation. The impact is more pronounced for female-headed households, suggesting that microfinance programs can help to empower women in rural areas.

**Similar Documents**: This study explores the effects of microfinance initiatives on the economic well-being of impoverished households within rural Bangladesh, drawing upon data collected through the Rural Household Survey (RHS) administered by the Bangladesh Institute of Development Studies (BIDS) in the years 1991, 1996, and 2000. Utilizing a difference-in-differences estimation technique, we ascertain the influence of microfinance schemes on the welfare of the underprivileged. Our findings indicate a substantial enhancement in the welfare of poor families, as evidenced by increased income, consumption levels, and asset accumulation. Notably, female-headed households experience a more pronounced impact, suggesting that microfinance can serve as a catalyst for women's empowerment in rural settings.

We have been developing a wearable robot that directly and physically supports human movement. A ldquomuscle suitrdquo for the arm that will provide muscular support for the paralyzed or those otherwise unable to move unaided is one example. Whereas low back pain is one of the most serious issue for the manual worker and in this paper, we focus on developing the support system for forward tilting of the upper body. In this paper, the concept and mechanical structure of the support system is shown. From the experimental result to keep forward tilting posture with load indicates our system is very effective for keeping forward tilting posture and it becomes clear that more than 60% reduction of muscular power is possible.

This chapter presents an overview of the Mixed Reality (MR) paradigm, which proposes to overlay our real-world environment with digital, computer-generated objects. It presents example applications and outlines limitations and solutions for their technical implementation. In MR systems, users perceive both the physical environment around them and digital elements presented through, for example, the use of semitransparent displays. By its very nature, MR is a highly interdisciplinary field engaging signal processing, computer vision, computer graphics, user interfaces, human factors, wearable computing, mobile computing, information visualization, and the design of displays and sensors. This chapter presents potential MR applications, technical challenges in realizing MR systems, as well as issues related to usability and collaboration in MR. It separately presents a section offering a selection of MR projects which have either been partly or fully undertaken at Swiss universities and rounds off with a section on current challenges and trends.

Significant functional impairment of the hand is common among stroke survivors and restoration of hand function should be prioritized during post-stroke rehabilitation. The goal of this study was to develop a novel biomimetic device to assist patients in producing complex hand movements with a limited number of actuators. The Biomimetic Hand Exoskeleton Device (BiomHED) is actuated by exotendons that mimic the geometry of the major tendons of the hand. Ten unimpaired subjects and four chronic stroke survivors participated in experiments that tested the efficacy of the system. The exotendons reproduced distinct spatial joint coordination patterns similar to their target muscle-tendon units for both subject groups. In stroke survivors, the exotendon-produced joint angular displacements were smaller, but not significantly different, than those of unimpaired subjects (\mbi p = 0.15-0.84). Even with limited use of the BiomHED, the kinematic workspace of the index finger increased by 63%-1014% in stroke survivors. The device improved the kinematics of the tip-pinch task in stroke survivors and resulted in a significant reduction in the fingertip-thumb tip distance ( 17.9 ±15.3 mm). This device is expected to enable effective “task-oriented” training of the hand post-stroke.

With increasing use of computers in our daily lives, lately there has been a rapid increase in the efforts to develop a better human computer interaction interface. The need of easy to use and advance types of human-computer interaction with natural interfaces is more than ever. In the present framework, the UI (User Interface) of a computer allows user to interact with electronic devices with graphical icons and visual indicators, which is still inconvenient and not suitable for working in virtual environments. An interface which allow user to communicate through gestures is the next step in the direction of advance human computer interface. In the present paper author explore different aspects of gesture recognition techniques.

We explore the development of an experimental augmented reality application that provides benefits to professional mechanics performing maintenance and repair tasks in a field setting. We developed a prototype that supports military mechanics conducting routine maintenance tasks inside an armored vehicle turret, and evaluated it with a user study. Our prototype uses a tracked headworn display to augment a mechanic's natural view with text, labels, arrows, and animated sequences designed to facilitate task comprehension, localization, and execution. A within-subject controlled user study examined professional military mechanics using our system to complete 18 common tasks under field conditions. These tasks included installing and removing fasteners and indicator lights, and connecting cables, all within the cramped interior of an armored personnel carrier turret. An augmented reality condition was tested against two baseline conditions: the same headworn display providing untracked text and graphics and a fixed flat panel display representing an improved version of the laptop-based documentation currently employed in practice. The augmented reality condition allowed mechanics to locate tasks more quickly than when using either baseline, and in some instances, resulted in less overall head movement. A qualitative survey showed that mechanics found the augmented reality condition intuitive and satisfying for the tested sequence of tasks.

Wearable exoskeleton robot is a kind of humanoid service robot to help the elderly and the patients with walking dysfunction, it is also an effective medical rehabilitation method to help patients who have walking disorders due to central neural system damage. This paper focuses on the flexible mechanism design of wearable lower limb exoskeleton robot. A wearable exoskeleton robot prototype was developed which can assist human walking. This paper analyzes the role of the major joints of walking human by experimental studies based on bionic design methods from human anatomy and bone surgery. We first analyze parameters of joint movements in a gait cycle, then we design a preliminary bionic model, finally we proposed a control strategy including a pair of electric crutches for the exoskeleton robot.

Virtual Reality (VR), a new computer technology, has incredible potential in the education field. The reason for this assertion is that education is a field that requires the students to understand complex data, particularly in the study of science (see "Why is science hard to learn?" by Millar) and VR makes that task easier. VR presents information in a 3-dimensional form with the participant viewing the world from inside the world (an immersed viewpoint) with the ability to interact with the information or world. People can enter a VR world that is already created or build their own. VR’s style of presentation mimics the ways that we, as humans, have learned to interact with our physical world. The requirement of learning abstract concepts (such as written language or jargon of a particular field) in order to understand data is dramatically reduced. For example, a chemistry world can show participants how electrons hover around a nucleus depending on the amount of energy involved. The abstractness of the subject would not be eliminated, but metaphors could be employed that were based solidly in reality. For instance, in the electron world the color of the world could represent the amount of energy in the system with red representing more energy than blue. For the students, they would be able to relate to hot things looking red and cold things looking blue without the concept of "joules increasing" getting in the way.

The present study investigated the ability to inter actively locate points in a three dimensional computer environment using a six degree of freedom input device. Four different visu al feedback modes were tested: fixed viewpoint monoscopic persp ective, fixed viewpoint stereoscopic perspective, head-tracked mo noscopic perspective and head-tracked stereoscopic perspecti ve. Targets were located at plus and minus 10cm along the X, Y or Z axes, from a fixed starting location. Data about the time to complete the task and positioning accuracy (error) are gathered for each trial. In addition, subjective feedback regarding the apparat us, visual mode and task difficulty was solicited from subject s. The results indicate that stereoscopic performance is superior to monoscopic performance and that asymmetries exist both across and within axes. Head tracking had no appreciable effect upon performance. Subjective feedback regarding performance is usuall y consistent with objective measures, but some inconsistencies a re present.

Wearable computing moves computation from the desktop to the user. We are forming a community of networked, wearable-computer users to explore, over a long period, the augmented realities that these systems can provide. By adapting its behavior to the user's changing environment, a body-worn computer can assist the user more intelligently, consistently, and continuously than a desktop system. A text-based augmented reality, the Remembrance Agent, is presented to illustrate this approach. Video cameras are used both to warp the visual input (mediated reality) and to sense the user's world for graphical overlay. With a camera, the computer could track the user's finger to act as the system's mouse; perform face recognition; and detect passive objects to overlay 2.5D and 3D graphics onto the real world. Additional apparatus such as audio systems, infrared beacons for sensing location, and biosensors for learning about the wearer's affect are described. With the use of input from these interface devices and sensors, a long-term goal of this project is to model the user's actions, anticipate his or her needs, and perform a seamless interaction between the virtual and physical environments.

An Augmented Virtual Environment (AVE) fuses dynamic imagery with 3D models. The AVE provides a unique approach to visualize and comprehend multiple streams of temporal data or images. Models are used as a 3D substrate for the visualization of temporal imagery, providing improved comprehension of scene activities. The core elements of AVE systems include model construction, sensor tracking, real-time video/image acquisition, and dynamic texture projection for 3D visualization. This paper focuses on the integration of these components and the results that illustrate the utility and benefits of the resulting augmented virtual environment.


Question: Integration of a light exoskeleton and data glove to improve virtual reality experiences.

This article introduces an innovative suite of user interface tools designed for an outdoor wearable augmented reality (AR) system, utilizing a pinch glove for enhanced interaction. Central to the user engagement are hand and head gestures, which form the primary mode of communication between the user and the AR environment. To facilitate intuitive and direct manipulation within this augmented space, we have engineered three distinct selection methods: two-handed framing, line of sight, and a laser beam technique. Additionally, a novel text entry mechanism has been devised, specifically tailored for the glove, to support more complex symbolic manipulation tasks. The practical application of these interaction tools is exemplified through a military logistics scenario, showcasing the system's capability to integrate seamlessly with real-world operations.

This paper is an overview of technologies that fall under the term augmented reality. Augmented reality refers to a system in which the physical surroundings of a person are mixed with real-time computer generated information creating an enhanced perception of surrounding environment. Being partly virtual and real, augmented reality applications have quite extreme requirements to be practical to use. It also has very much potential in numerous different application areas. These issues make augmented reality both an interesting and challenging subject from scientific and business perspectives.

With increasing use of computers in our daily lives, lately there has been a rapid increase in the efforts to develop a better human computer interaction interface. The need of easy to use and advance types of human-computer interaction with natural interfaces is more than ever. In the present framework, the UI (User Interface) of a computer allows user to interact with electronic devices with graphical icons and visual indicators, which is still inconvenient and not suitable for working in virtual environments. An interface which allow user to communicate through gestures is the next step in the direction of advance human computer interface. In the present paper author explore different aspects of gesture recognition techniques.

This paper describes performance evaluation of a wearable augmented reality system for natural outdoor environments. Applied Research Associates (ARA), as prime integrator on the DARPA ULTRA-Vis (Urban Leader Tactical, Response, Awareness, and Visualization) program, is developing a soldier-worn system to provide intuitive ‘heads-up’ visualization of tactically-relevant geo-registered icons. Our system combines a novel pose estimation capability, a helmet-mounted see-through display, and a wearable processing unit to accurately overlay geo-registered iconography (e.g., navigation waypoints, sensor points of interest, blue forces, aircraft) on the soldier’s view of reality. We achieve accurate pose estimation through fusion of inertial, magnetic, GPS, terrain data, and computer-vision inputs. We leverage a helmet-mounted camera and custom computer vision algorithms to provide terrain-based measurements of absolute orientation (i.e., orientation of the helmet with respect to the earth). These orientation measurements, which leverage mountainous terrain horizon geometry and mission planning landmarks, enable our system to operate robustly in the presence of external and body-worn magnetic disturbances. Current field testing activities across a variety of mountainous environments indicate that we can achieve high icon geo-registration accuracy (<10mrad) using these vision-based methods.

This paper describes an investigation into how real-time but low-cost biometric information can be interpreted by computer games to enhance gameplay without fundamentally changing it. We adapted a cheap sensor, (the Lightstone mediation sensor device by Wild Divine), to record and transfer biometric information about the player (via sensors that clip over their fingers) into a commercial game engine, Half-Life 2. During game play, the computer game was dynamically modified by the player’s biometric information to increase the cinematically augmented “horror” affordances. These included dynamic changes in the game shaders, screen shake, and the creation of new spawning points for the game’s non-playing characters (zombies), all these features were driven by the player’s biometric data. To evaluate the usefulness of this biofeedback device, we compared it against a control group of players who also had sensors clipped on their fingers, but for the second group the gameplay was not modified by the biometric information of the players. While the evaluation results indicate biometric data can improve the situated feeling of horror, there are many design issues that will need to be investigated by future research, and the judicious selection of theme and appropriate interaction is vital. Author

In this paper, we present the dynamics, control, and preliminary experiments on a wearable upper arm exoskeleton intended for human users with four degrees-of-freedom (dof), driven by six cables. The control of this cable-driven exoskeleton is complicated because the cables can transmit forces to the arm only under tension. The standard PD controllers or Computed torque controllers perform only moderately since the cables need to be in tension. Future efforts will seek to refine these control strategies and their implementations to improve functionality of a human user.

In immersive virtual environments (IVEs), users can control their virtual viewpoint by moving their tracked head and walking through the real world. Usually, movements in the real world are mapped one-to-one to virtual camera motions. With redirection techniques, the virtual camera is manipulated by applying gains to user motion so that the virtual world moves differently than the real world. Thus, users can walk through large-scale IVEs while physically remaining in a reasonably small workspace. In psychophysical experiments with a two-alternative forced-choice task, we have quantified how much humans can unknowingly be redirected on physical paths that are different from the visually perceived paths. We tested 12 subjects in three different experiments: (E1) discrimination between virtual and physical rotations, (E2) discrimination between virtual and physical straightforward movements, and (E3) discrimination of path curvature. In experiment E1, subjects performed rotations with different gains, and then had to choose whether the visually perceived rotation was smaller or greater than the physical rotation. In experiment E2, subjects chose whether the physical walk was shorter or longer than the visually perceived scaled travel distance. In experiment E3, subjects estimate the path curvature when walking a curved path in the real world while the visual display shows a straight path in the virtual world. Our results show that users can be turned physically about 49 percent more or 20 percent less than the perceived virtual rotation, distances can be downscaled by 14 percent and upscaled by 26 percent, and users can be redirected on a circular arc with a radius greater than 22 m while they believe that they are walking straight.

Virtual Reality (VR), a new computer technology, has incredible potential in the education field. The reason for this assertion is that education is a field that requires the students to understand complex data, particularly in the study of science (see "Why is science hard to learn?" by Millar) and VR makes that task easier. VR presents information in a 3-dimensional form with the participant viewing the world from inside the world (an immersed viewpoint) with the ability to interact with the information or world. People can enter a VR world that is already created or build their own. VR’s style of presentation mimics the ways that we, as humans, have learned to interact with our physical world. The requirement of learning abstract concepts (such as written language or jargon of a particular field) in order to understand data is dramatically reduced. For example, a chemistry world can show participants how electrons hover around a nucleus depending on the amount of energy involved. The abstractness of the subject would not be eliminated, but metaphors could be employed that were based solidly in reality. For instance, in the electron world the color of the world could represent the amount of energy in the system with red representing more energy than blue. For the students, they would be able to relate to hot things looking red and cold things looking blue without the concept of "joules increasing" getting in the way.

Optical see-through head-mounted displays (OST-HMD) feature an unhindered and instantaneous view of the surgery site and can enable a mixed reality experience for surgeons during procedures. In this paper, we present a systematic approach to identify the criteria for evaluation of OST-HMD technologies for specific clinical scenarios, which benefit from using an object-anchored 2D-display visualizing medical information. Criteria for evaluating the performance of OST-HMDs for visualization of medical information and its usage are identified and proposed. These include text readability, contrast perception, task load, frame rate, and system lag. We choose to compare three commercially available OST-HMDs, which are representatives of currently available head-mounted display technologies. A multi-user study and an offline experiment are conducted to evaluate their performance. Statistical analysis demonstrates that Microsoft HoloLens performs best among the three tested OST-HMDs, in terms of contrast perception, task load, and frame rate, while ODG R-7 offers similar text readability. The integration of indoor localization and fiducial tracking on the HoloLens provides significantly less system lag in a relatively motionless scenario. With ever more OST-HMDs appearing on the market, the proposed criteria could be used in the evaluation of their suitability for mixed reality surgical intervention. Currently, Microsoft HoloLens may be more suitable than ODG R-7 and Epson Moverio BT-200 for clinical usability in terms of the evaluated criteria. To the best of our knowledge, this is the first paper that presents a methodology and conducts experiments to evaluate and compare OST-HMDs for their use as object-anchored 2D-display during interventions.

We explore the combination of above-surface sensing with eye tracking to facilitate concurrent interaction with multiple regions on touch screens. Conventional touch input relies on positional accuracy, thereby requiring tight visual monitoring of one's own motor action. In contrast, above-surface sensing and eye tracking provides information about how user's hands and gaze are distributed across the interface. In these situations we facilitate interaction by 1) showing the visual feedback of the hand hover near user's gaze point and 2) decrease the requisite of positional accuracy by employing gestural information. We contribute input and visual feedback techniques that combine these modalities and demonstrate their use in example applications. A controlled study showed the effectiveness of our techniques for manipulation tasks against conventional touch, while the effectiveness in acquisition tasks depended on the amount of mid-air motion, leading to our conclusion that the techniques can benefit interacting with multiple interface regions.

Backdrivability is a keyword with rising importance, not only in humanoid robots, but also to wearable robots. Power assist robots, namely exoskeletons are expected to provide mobility and independence to elderly and people with disability. In such robots, without backdrivability, error between human and robot motion can be painful; sometimes dangerous. In this research, we apply a type of hydraulic actuator, specially designed to realize backdrivability, to exoskeletal robot to improve backdrivability. We present the basic methodology to apply such hydraulic actuator to wearable robots. We developed prototype of knee joint power assist exoskeleton and performed fundamental tests to verify the design method validity.


Question: Integration of a light exoskeleton and data glove for improving virtual reality experiences.

This paper provides an overview of the augmented reality (AR) domain, where 3D virtual elements are seamlessly integrated into the real-world environment in real time. It delves into various applications such as medical training, manufacturing processes, data visualization, path planning, entertainment, and military operations. The paper examines the key attributes of augmented reality systems, with a critical analysis of the advantages and disadvantages of optical versus video blending techniques. Given the critical importance of accurate registration and minimizing sensing errors in the functionality of AR systems, the paper compiles recent advancements aimed at addressing these challenges. It concludes by outlining future research directions and areas that require further exploration, serving as a comprehensive resource for researchers and practitioners interested in the field of augmented reality.

**Question**: The Role of Blockchain in Enhancing Cybersecurity in Financial Services

**Documents**: Blockchain: The Path to Trusted Digital Identities
The paper explores the potential of blockchain technology in creating a more secure and trustworthy system for digital identities. It discusses how blockchain can be used to create a decentralized, immutable ledger for identity verification and management, potentially reducing the risk of identity theft and fraud. The paper also highlights the challenges and limitations of implementing blockchain for digital identities, including issues of scalability, privacy, and standardization. It concludes by examining the potential impact of blockchain on the future of digital identity management in various sectors, including financial services, healthcare, and government.

**Similar Documents**: This paper investigates the transformative potential of blockchain technology in revolutionizing digital identity management, particularly in enhancing security and trustworthiness. It outlines the mechanism by which blockchain can establish a decentralized, tamper-proof ledger for identity verification, significantly mitigating the risks associated with identity theft and fraudulent activities. The paper also addresses the obstacles to blockchain's adoption in digital identity systems, such as scalability concerns, privacy protection, and the need for standardized protocols. It further speculates on the profound implications of blockchain on the evolution of digital identity management across different industries, with a focus on financial services, healthcare, and public administration, illustrating how these sectors could benefit from more secure and efficient identity verification processes.

To date augmented realities are typically operated in only a small defined area, in the order of a large room. This paper reports on our investigation into expanding augmented realities to outdoor environments. The project entails providing visual navigation aids to users. A wearable computer system with a see-through display, digital compass, and a differential GPS are used to provide visual cues while performing a standard orienteering task. This paper reports the outcomes of a set of trials using an off the shelf wearable computer, equipped with a custom built navigation software package, "map-in-the-hat".

We present GRAVITY-ASSIST, a series elastic active body weight support and inertia compensation system for use in robot assisted gait rehabilitation. The device consists of a single degree of freedom series elastic actuator that connects to the trunk of a patient. The series elastic system is novel in that, it can provide the desired level of dynamic unloading such that the patient experiences only a percentage of his/her weight and inertia. Inertia compensation is important, since the inertial forces can cause significant deviations from the desired unloading force, specially at low support forces and fast walking speeds. Furthermore, this feature enables the inertia of the harness and force sensing unit attached to the patient to be compensated for, making sure that the device does not interfere with the natural gait cycle. We present a functional prototype of the device, its characterization and experimental verification of the approach.

The Rutgers Ankle is a Stewart platform-type haptic interface designed for use in rehabilitation. The system supplies six-degree-of-freedom (DOF) resistive forces on the patient's foot, in response to virtual reality-based exercises. The Rutgers Ankle controller contains an embedded Pentium board, pneumatic solenoid valves, valve controllers, and associated signal conditioning electronics. The rehabilitation exercise used in our case study consists of piloting a virtual airplane through loops. The exercise difficulty can be selected based on the number and placement of loops, the airplane speed in the virtual environment, and the degree of resistance provided by the haptic interface. Exercise data is stored transparently, in real time, in an Oracle database. These data consist of ankle position, forces, and mechanical work during an exercise, and over subsequent rehabilitation sessions. The number of loops completed and the time it took to do that are also stored online. A case study is presented of a patient nine months post-stroke using this system. Results showed that, over six rehabilitation sessions, the patient improved on clinical measures of strength and endurance, which corresponded well with torque and power output increases measured by the Rutgers Ankle. There were also substantial improvements in task accuracy and coordination during the simulation and the patient's walking and stair-climbing ability.

The recent introduction of depth cameras like Leap Motion Controller allows researchers to exploit the depth information to recognize hand gesture more robustly. This paper proposes a novel hand gesture recognition system with Leap Motion Controller. A series of features are extracted from Leap Motion tracking data, we feed these features along with HOG feature extracted from sensor images into a multiclass SVM classifier to recognize performed gesture, dimension reduction and feature weighted fusion are also discussed. Our results show that our model is much more accurate than previous work.

Recently Electronic Textile (E-Textile) technology enables the weaving computation and communication components into the clothes that we wear and objects that we interact with every day. E-Textile enables the design and development of a broad range of pervasive sensing systems such as smart bed sheets for sleep posture monitoring, insoles in medical shoes for monitoring plantar pressure distribution, smart garments and sensing gloves. However the low cost of E-Textiles come at the cost of accuracy. In this work we propose an actuator-based method that increases the accuracy of E-Textiles by means of enabling real-time calibration. Our proposed system increases system accuracy by 38.55% on average (maximum 58.4%).

Contemporary museums are much more than places devoted to the placement and the exhibition of collections and artworks; indeed, they are nowadays considered as a privileged means for communication and play a central role in making culture accessible to the mass audience. One of the keys to approach the general public is the use of new technologies and novel interaction paradigms. These means, which bring with them an undeniable appeal, allow curators to modulate the cultural proposal by structuring different courses for different user profiles. Immersive Virtual reality (VR) is probably one of the most appealing and potentially effective technologies to serve this purpose; nevertheless, it is still quite uncommon to find immersive installations in museums. Starting from our 10 years’ experience in this topic, and following an in-depth survey about these technologies and their use in cultural contexts, we propose a classification of VR installations, specifically oriented to cultural heritage applications, based on their features in terms of interaction and immersion. On the basis of this classification, aiming to provide a tool for framing VR systems which would hopefully suggest indications related to costs, usability and quality of the sensorial experience, we analyze a series of live examples of which we point out strengths and weak points. We then summarize the current state and the very next future, identifying the major issues that prevent these technologies from being actually widespread, and outline proposals for a more se of pervasive and effective u

We present an approach for real-time, robust and accurate hand pose estimation from moving egocentric RGB-D cameras in cluttered real environments. Existing methods typically fail for hand-object interactions in cluttered scenes imaged from egocentric viewpoints—common for virtual or augmented reality applications. Our approach uses two subsequently applied Convolutional Neural Networks (CNNs) to localize the hand and regress 3D joint locations. Hand localization is achieved by using a CNN to estimate the 2D position of the hand center in the input, even in the presence of clutter and occlusions. The localized hand position, together with the corresponding input depth value, is used to generate a normalized cropped image that is fed into a second CNN to regress relative 3D hand joint locations in real time. For added accuracy, robustness and temporal stability, we refine the pose estimates using a kinematic pose tracking energy. To train the CNNs, we introduce a new photorealistic dataset that uses a merged reality approach to capture and synthesize large amounts of annotated data of natural hand interaction in cluttered scenes. Through quantitative and qualitative evaluation, we show that our method is robust to self-occlusion and occlusions by objects, particularly in moving egocentric perspectives.

In order to successfully perform object manipulation, humanoid robots must be equipped with tactile sensors. However, the limited space that is available in robotic fingers imposes severe design constraints. In [1] we presented a small prototype fingertip which incorporates a capacitive pressure system. This paper shows an improved version, which has been integrated on the hand of the humanoid robot iCub. The fingertip is 14.5 mm long and 13 mm wide. The capacitive pressure sensor system has 12 sensitive zones and includes the electronics to send the 12 measurements over a serial bus with only 4 wires. Each synthetic fingertip is shaped approximately like a human fingertip. Furthermore, an integral part of the capacitive sensor is soft silicone foam, and therefore the fingertip is compliant. We describe the structure of the fingertip, their integration on the humanoid robot iCub and present test results to show the characteristics of the sensor.

Handheld and wearable devices frequently engage users with simple haptic feedback, such as alerting, shaking, and pulsating. Here we explored intermanual apparent tactile motion-illusory movement between two hands-as a means to enrich such feedback. A series of psychophysical experiments determined the control space for generating smooth and consistent motion across the hands while users held the device. Experiment 1 calibrated the system and showed that vibrotactile detection thresholds decreased with increasing frequency, with similar trends for both hands. Experiment 2 measured effects of vibrotactile parameters on perceived motion. Both duration and temporal separation of stimuli, but not frequency and amplitude, affected subjective motion ratings. In Experiment 3, subjective ratings showed that stimuli with gradual onsets produced a stronger percept of motion than those with abrupt onsets. Finally, Experiment 4 determined a multimodal factor to match moving visual cues across the screen to moving tactile motion across hands. Our results showed compression of visual duration by the tactile system by a factor of approximately 1/3 at two test frequencies. The results of this research are useful for media designers and developers to generate reliable motion across the hands and integrate haptic motion with visual media.

In this paper we show and evaluate the design of a novel telemanipulation system that maps proximity values, acquired inside of a gripper, to forces a user can feel through a haptic input device. The command console is complemented by input-devices that give the user an intuitive control over parameters relevant to the system. Furthermore, proximity sensors enable the autonomous alignment/centering of the gripper to objects in user-selected DoFs with the potential of aiding the user and lowering the workload. We evaluate our approach in a user study that shows that the telemanipulation system benefits from the supplementary proximity information and that the workload can indeed be reduced when the system operates with partial autonomy.


Question: Utilizing a model as a descriptive instrument for assessing a virtual learning environment.

A Web-Based Virtual Learning Environment: Evaluating Its Efficacy in Basic IT Skills Education

This paper proposes a framework for assessing the effectiveness of web-based virtual learning environments (VLEs) in the context of basic IT skills training. The adoption of VLEs has gained momentum due to their potential for enhancing the learning experience, particularly in technical education. The research framework outlined here is designed to evaluate the impact of VLEs on learning outcomes, student engagement, and overall educational quality in IT skills instruction. The assessment criteria include interactivity, accessibility, adaptability, and the integration of multimedia resources. A preliminary analysis of a specific VLE used for teaching fundamental IT competencies reveals promising results. Learners demonstrated improved understanding and application of IT concepts, enhanced problem-solving abilities, and increased motivation. The study also highlights the importance of user-friendly design, reliable technical support, and the provision of real-world scenarios for skill development. The findings suggest that VLEs can be a valuable tool in IT education, offering a flexible and immersive learning environment that caters to diverse learning styles and enhances the acquisition of essential IT skills.

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Assessment can be seen as the engine that drives student course activity, online or off. It is particularly important in encouraging and shaping collaborative activity online. This paper discusses three sorts of online collaborative activity—collaborative discussion, small group collaboration, and collaborative exams. In each of these areas, it provides both theoretical grounding and practical advice for assessing, and so encouraging, collaboration in online courses.

Computational Thinking (CT) is gaining a lot of attention in education. We explored how to discern the occurrences of CT in the projects of 12th grade high school students in the computer science (CS) course. Within the projects, they constructed models and ran simulations of phenomena from other (STEM) disciplines. We examined which CT aspects occurred in students' activities and how to assess students' CT accomplishments. For this purpose we employed a framework based on CT characterizations by Wing [14, 15], CSTA [4] and Comer et al. [3]. We analyzed students' project documentation, survey results and interviews with individual students. The findings indicate that this framework is suitable for detection of occurrences of CT aspects in students' data. Moreover, our preliminary results suggest that the framework is useful in assessment of the quality of the students' CT performance.

Game-based learning and gamification techniques are recently becoming a popular trend in the field of Technology Enhanced Learning. In this paper, we mainly focus on the use of game design elements for the transmission of Intangible Cultural Heritage (ICH) knowledge and, especially, for the learning of traditional dances. More specifically, we present a 3D game environment that employs an enjoyable natural human computer interface, which is based on the fusion of multiple depth sensors data in order to capture the body movements of the user/learner. In addition, the system automatically assesses the learner’s performance by utilizing a combination of Dynamic Time Warping (DTW) with Fuzzy Inference System (FIS) approach and provides feedback in a form of a score as well as instructions from a virtual tutor in order to promote self-learning. As a pilot use case, a Greek traditional dance, namely Tsamiko, has been selected. Preliminary small-scaled experiments with students of the Department of Physical Education and Sports Science at Aristotle University of Thessaloniki have shown the great potential of the proposed application.

The primary questions addressed in this paper are the following: what are the factors that affect students‟ adoption of an e-learning system and what are the relationships among these factors? This paper investigates and identifies some of the major factors affecting students‟ adoption of an e-learning system in a university in Jordan. E-learning adoption is approached from the information systems acceptance point of view. This suggests that a prior condition for learning effectively using e-learning systems is that students must actually use them. Thus, a greater knowledge of the factors that affect IT adoption and their interrelationships is a pre-cursor to a better understanding of student acceptance of e-learning systems. In turn, this will help and guide those who develop, implement, and deliver e-learning systems. In this study, an extended version of the Technology Acceptance Model (TAM) was developed to investigate the underlying factors that influence students‟ decisions to use an e-learning system. The TAM was populated using data gathered from a survey of 486 undergraduate students, who were using the Moodle based e-learning system at the Arab Open University. The model was estimated using Structural Equation Modelling (SEM). A path model was developed to analyze the relationships between the factors to explain students‟ adoption of the e-learning system. Whilst findings support existing literature about prior experience affecting perceptions, they also point to surprising group effects, which may merit future exploration.

This paper consolidates evidence and material from a range of specialist and disciplinary fields to provide an evidence-based review and synthesis on the design and use of serious games in higher education. Search terms identified 165 papers reporting conceptual and empirical evidence on how learning attributes and game mechanics may be planned, designed, and implemented by university teachers interested in using games, which are integrated into lesson plans and orchestrated as part of a learning sequence at any scale. The findings outline the potential of classifying the links between learning attributes and game mechanics as a means to scaffold teachers’ understanding of how to perpetuate learning in optimal ways whilst enhancing the in-game learning experience. The findings of this paper provide a foundation for describing methods, frames, and discourse around experiences of design and use of serious games, linked to methodological limitations and recommendations for further research in this area. Practitioner Notes What is already known about this topic • Serious game design is a relatively new discipline that couples learning design with game features. A key characteristic of this approach is grounded in educational need and theory, rather than a focus purely on entertainment. Under this approach, a common method for designing serious games involves the creation of learning strategies, content and principles for the purpose of enhancing the student’s learning experience. • There are no pedagogically driven strategies that take into account how learning attributes are interlinked to game elements for balancing learning with play. This is due to a limited evidence base of comparative evaluations assessing differing game designs against a single pedagogical model, or vice versa. This often leads practitioners seeking to introduce games into classroom with difficulties identifying what defines a game or how design should be enacted in a way that encompasses particular learning interventions. • Qualitative research methodologies have not been utilised as often for discerning how people experience, understand and use serious games for teaching and learning in higher education. What this paper adds • This paper presents the foundation of a taxonomy linking learning and game attributes along with teacher roles, aiming to encourage the cross-fertilisation and further integration of evidence on serious game design. The initial findings provide insight for practitioners on elements common to games and serious games, and how these link to particular learning design strategies that may afford pedagogically-rich games. • It informs development in the design and use of serious games to support teaching and learning in higher education. Given the key role of practitioners in the development of a wide range of serious games, due to the iterative and participatory methods frequently adopted, it offers insight into game elements and mechanics, allowing practitioners to easily relate to how learning activities, outcomes, feedback and roles may vary and visualised in relation to what needs to be learned out of playing the game. • The paper also identifies gaps in the evidence base and avenues for future research. Through this a practitioner can gain insight into the current unknowns in the area, and relate their experience of introducing games in the classroom to the current evidence base. Implications for practice and/or policy • The taxonomy informs serious game/instructional designers, game developers, academics and students about how learning elements (e.g. learning activities, learning outcomes, feedback and assessment) can be represented in games. We advocate dialogue between teachers and serious game designers, for improving the process of amalgamating learning with fun; and whilst the idea of using digital games is relatively new, teachers have a wealth of experience introducing learning features in games to be used into their classroom activities which frequently set out undocumented. • It aids the delineation of game attributes and associated game categories for characterising games based on primary purpose and use. Planning and designing teaching and learning in a game and teacher’s associated role in guiding the in-game learning process is a consistent challenge and this paper seeks to provide a foundation by which this process can be undertaken in an informed and conscious manner. • The findings of the review act as the point of departure for creating a research agenda for understanding disjunctions between espoused and enacted personal theories of using serious games through qualitative methodologies. Introduction Serious Games (SGs) design is a relatively new discipline that couples learning design with game mechanics and logic (de Freitas, 2006; Hainley 2006; Westera et al., 2008). Design for SGs involves the creation of learning activities that may use the whole game or entail a gaming element (e.g. leader boards, virtual currencies, in-game hints) for the purpose of transforming the student’s learning experience. Arguments against SGs have centred upon lack of empirical evidence in support of their efficacy; and the fact that appropriate research methodologies have not been enacted as yet for discerning how people understand and use SGs for teaching and learning in higher education (Mayer 2012; Connolly 2012). However, there are studies in the UK and US respectively that have demonstrated positive results in large sample groups (see for example Dunwell et al., 2014; Hertzog et al., 2014; Kato et al., 2008). Research evidence stresses the lack of commonly accepted pedagogically-driven strategies to afford game mechanisms and suggest that an inclusive model that takes into account pedagogy and teaching strategy, aligned to game activity and assessment is necessary for balancing play features with pedagogical aspects. This argument stems from an important observation that learning is a constructive process, which encompasses aspects of collaborative learning in which knowledge creation emerges through discussion and negotiation between individuals and groups. With these perspectives, this paper draws together evidence and material from a range of specialist and disciplinary fields to offer a critical review and synthesis of the design and use of SGs in higher

We design a modeling platform to construct virtual environments for Virtual Reality Exposure Therapy. In this platform, the scene is built by image-based reconstruction followed by manual refinement (when needed). The main technical contribution of this paper is on enhanced human character modeling, which is done through reconstructing 3D face geometry, body shape and posture from provided 2D photos.

An Augmented Virtual Environment (AVE) fuses dynamic imagery with 3D models. The AVE provides a unique approach to visualize and comprehend multiple streams of temporal data or images. Models are used as a 3D substrate for the visualization of temporal imagery, providing improved comprehension of scene activities. The core elements of AVE systems include model construction, sensor tracking, real-time video/image acquisition, and dynamic texture projection for 3D visualization. This paper focuses on the integration of these components and the results that illustrate the utility and benefits of the resulting augmented virtual environment.

The goals of this study are to evaluate a relatively novel learning environment, as well as to seek greater understanding of why human tutoring is so effective. This alternative learning environment consists of pairs of students collaboratively observing a videotape of another student being tutored. Comparing this collaboratively observing environment to four other instructional methods-one-on-one human tutoring, observing tutoring individually, collaborating without observing, and studying alone-the results showed that students learned to solve physics problems just as effectively from observing tutoring collaboratively as the tutees who were being tutored individually. We explain the effectiveness of this learning environment by postulating that such a situation encourages learners to become active and constructive observers through interactions with a peer. In essence, collaboratively observing combines the benefit of tutoring with the benefit of collaborating. The learning outcomes of the tutees and the collaborative observers, along with the tutoring dialogues, were used to further evaluate three hypotheses explaining why human tutoring is an effective learning method. Detailed analyses of the protocols at several grain sizes suggest that tutoring is effective when tutees are independently or jointly constructing knowledge: with the tutor, but not when the tutor independently conveys knowledge.

Social media are increasingly being used for educational purposes. The first part of this article briefly reviews literature that reports on educational applications of social media tools. The second part discusses theories that may provide a basis for analyzing the processes that are relevant for individual learning and collective knowledge construction. We argue that a systems-theoretical constructivist approach is appropriate to examine the processes of educational social media use, namely, self-organization, the internalization of information, the externalization of knowledge, and the interplay of externalization and internalization providing the basis of a co-evolution of cognitive and social systems. In the third part we present research findings that illustrate and support this systems-theoretical framework. Concluding, we discuss the implications for educational design and for future research on learning and collective knowledge construction with social media.

Active learning requires that students receive a continuous feedback about their understanding. Multiple-Choice Questions (MCQ) tests have been frequently used to provide students the required feedback and to measure the effectiveness of this learning model. To construct a test is a challenging task, which is time consuming and requires experience. For these reasons, research efforts have been focused on the automatic generation of well-constructed tests. The semantic technologies have played a relevant role in the implementation of these testgeneration systems. Nevertheless, the existing proposals present a set of drawbacks that restrict their applicability to different learning domains and the type of test to be composed. In this paper, we propose a service-oriented and semantic-based system that solves these drawbacks. The system consists of a dynamic strategy of generating candidate distractors (alternatives to the correct answer), a set of heuristics for scoring the distractors' suitability, and a selection of distractors that considers the difficulty level of tests. Besides, the final version of tests is created using the Google Form service, a de-facto standard for elaborating online questionnaires.