Tangible user interfaces : past, present and future directions

In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

Stay-At-Home Motor Rehabilitation: Optimizing Spatiotemporal Learning on Low-Cost Capacitive Sensor Arrays

Repeated, consistent, and precise gesture performance is a key part of recovery for stroke and other motor-impaired patients. Close professional supervision to these exercises is also essential to ensure proper neuromotor repair, which consumes a large amount of medical resources. Gesture recognition systems are emerging as stay-at-home solutions to this problem, but the best solutions are expensive, and the inexpensive solutions are not universal enough to tackle patient-to-patient variability. While many methods have been studied and implemented, the gesture recognition system designer does not have a strategy to effectively predict the right method to fit the needs of a patient. This thesis establishes such a strategy by outlining the strengths and weaknesses of several spatiotemporal learning architectures combined with deep learning, specifically when low-cost, low-resolution capacitive sensor arrays are used. This is done by testing the immunity and robustness of those architectures to the type of variability that is common among stroke patients, investigating select hyperparameters and their impact on the architectures’ training progressions, and comparing test performance in different applications and scenarios. The models analyzed here are trained on a mixture of high-quality, healthy gestures and personalized, imperfectly performed gestures using a low-cost recognition system

Furthering Service 4.0: Harnessing Intelligent Immersive Environments and Systems

With the increasing complexity of service operations in different industries and more advanced uses of specialized equipment and procedures, the great current challenge for companies is to increase employees' expertise and their ability to maintain and improve service quality. In this regard, Service 4.0 aims to support and promote innovation in service operations using emergent technology. Current technological innovations present a significant opportunity to provide on-site, real-time support for field service professionals in many areas

Disney meets Darwin : an evolution-based interface for exploration and design of expressive animated behavior

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1994.Includes bibliographical references (leaves 68-70).by Jeffrey John Ventrella.M.S

The Roles of Virtual Reality and Augmented Reality During The COVID-19 Pandemic

Abstract:  This paper aims to describe the roles of virtual reality and augmented reality during the COVID-19 pandemic. Method of the study: It is a narrative literature review. Literature was searched in Science Direct and Google Scholar databases. Review and research paper were included. Short notes and commentary were excluded. Results revealed that the invention of Augmented-Reality, Virtual-Reality, and Mixed-Reality technologies gives integrations of virtual and physical objects. Those technologies have many usages in education, experiments, manufacture, and business. Users can have hybrid experiences because the combination of the interactive physical and virtual connections. In business, the interested customers will buy the products. In education, these technologies will help the students in learning process. In healthcare, it can be done to do simulation for preventing the COVID-19 pandemic. In conclusion, the roles of augmented reality and virtual reality are very essential, such as in health, education, business, manufacture, and experiments.Abstrak: Tulisan ini bertujuan untuk mendeskripsikan peran virtual reality dan augmented reality selama pandemi COVID-19. Metode penelitian adalah tinjauan literatur naratif. Literatur dicari di database Science Direct dan Google Scholar. Review dan makalah penelitian merupakan kriteria inklusi. Catatan pendek dan komentar diekslusikan. Hasil penelitian mengungkapkan bahwa penemuan teknologi Augmented-Reality, Virtual-Reality, dan Mixed-Reality memberikan integrasi objek virtual dan fisik. Teknologi tersebut memiliki banyak kegunaan dalam pendidikan, eksperimen, manufaktur, dan bisnis. Pengguna dapat memiliki pengalaman hybrid karena kombinasi koneksi fisik dan virtual interaktif. Dalam bisnis, pelanggan yang tertarik akan membeli produk. Dalam dunia pendidikan, teknologi ini akan membantu siswa dalam proses belajar. Di bidang kesehatan, bisa dilakukan simulasi pencegahan pandemi COVID-19. Hasil penelitian menunjukkan bahwa peran augmented reality dan virtual reality sangat penting, seperti dalam kesehatan, pendidikan, bisnis, manufaktur, dan eksperimen

Human behavior understanding for worker-centered intelligent manufacturing

“In a worker-centered intelligent manufacturing system, sensing and understanding of the worker’s behavior are the primary tasks, which are essential for automatic performance evaluation & optimization, intelligent training & assistance, and human-robot collaboration. In this study, a worker-centered training & assistant system is proposed for intelligent manufacturing, which is featured with self-awareness and active-guidance. To understand the hand behavior, a method is proposed for complex hand gesture recognition using Convolutional Neural Networks (CNN) with multiview augmentation and inference fusion, from depth images captured by Microsoft Kinect. To sense and understand the worker in a more comprehensive way, a multi-modal approach is proposed for worker activity recognition using Inertial Measurement Unit (IMU) signals obtained from a Myo armband and videos from a visual camera. To automatically learn the importance of different sensors, a novel attention-based approach is proposed to human activity recognition using multiple IMU sensors worn at different body locations. To deploy the developed algorithms to the factory floor, a real-time assembly operation recognition system is proposed with fog computing and transfer learning. The proposed worker-centered training & assistant system has been validated and demonstrated the feasibility and great potential for applying to the manufacturing industry for frontline workers. Our developed approaches have been evaluated: 1) the multi-view approach outperforms the state-of-the-arts on two public benchmark datasets, 2) the multi-modal approach achieves an accuracy of 97% on a worker activity dataset including 6 activities and achieves the best performance on a public dataset, 3) the attention-based method outperforms the state-of-the-art methods on five publicly available datasets, and 4) the developed transfer learning model achieves a real-time recognition accuracy of 95% on a dataset including 10 worker operations”--Abstract, page iv