Touch Technology in Affective Human, Robot, Virtual-Human Interactions: A Survey

Given the importance of affective touch in human interactions, technology designers are increasingly attempting to bring this modality to the core of interactive technology. Advances in haptics and touch-sensing technology have been critical to fostering interest in this area. In this survey, we review how affective touch is investigated to enhance and support the human experience with or through technology. We explore this question across three different research areas to highlight their epistemology, main findings, and the challenges that persist. First, we review affective touch technology through the human–computer interaction literature to understand how it has been applied to the mediation of human–human interaction and its roles in other human interactions particularly with oneself, augmented objects/media, and affect-aware devices. We further highlight the datasets and methods that have been investigated for automatic detection and interpretation of affective touch in this area. In addition, we discuss the modalities of affective touch expressions in both humans and technology in these interactions. Second, we separately review how affective touch has been explored in human–robot and real-human–virtual-human interactions where the technical challenges encountered and the types of experience aimed at are different. We conclude with a discussion of the gaps and challenges that emerge from the review to steer research in directions that are critical for advancing affective touch technology and recognition systems. In our discussion, we also raise ethical issues that should be considered for responsible innovation in this growing area

Design and development of a weight support device for upper limb stroke rehabilitation

Upper limb recovery following a stroke is generally quite poor. Upper limb therapy at clinic is usually limited due to lack of time and resources to accommodate the growing stroke population. Consequently, a small percentage of therapy is spent on improving upper limb movement and is generally limited to range of motion and stretching exercises. As a result, upper limb exercises are prescribed to stroke survivors to perform at home. Subsequently, the potential to facilitate self-practice at home has been realized leading to the development of numerous rehabilitative and assistive devices for the upper limb. However, commercially available devices do not tend to be adopted for home use due to practical and economic factors. This thesis details the design, development, and evaluation of a weight support device for home-based upper limb rehabilitation, driven through a user-designed approach. This was achieved through engaging with stakeholders (i.e. stroke survivors, therapists) throughout the design process via informal interviews, focus groups, and prototype testing, ensuring that their desired requirements were incorporated into the final device. From this process, a low-cost, portable, weight support device was manufactured with supports for both the upper arm and forearm. Furthermore, an external feedback system was created to provide real-time feedback to the user to help motivate and encourage them to engage in independent practice at home with the weight support device. Testing the device and feedback system with participants in their home environment showed that it was acceptable for home use, suggesting that it could be feasible for aiding with the facilitation of self-practice. Further refinements towards range of motion and portability of the device will be required as desired by participants in addition to providing a diverse range of feedback applications to engage with.Upper limb recovery following a stroke is generally quite poor. Upper limb therapy at clinic is usually limited due to lack of time and resources to accommodate the growing stroke population. Consequently, a small percentage of therapy is spent on improving upper limb movement and is generally limited to range of motion and stretching exercises. As a result, upper limb exercises are prescribed to stroke survivors to perform at home. Subsequently, the potential to facilitate self-practice at home has been realized leading to the development of numerous rehabilitative and assistive devices for the upper limb. However, commercially available devices do not tend to be adopted for home use due to practical and economic factors. This thesis details the design, development, and evaluation of a weight support device for home-based upper limb rehabilitation, driven through a user-designed approach. This was achieved through engaging with stakeholders (i.e. stroke survivors, therapists) throughout the design process via informal interviews, focus groups, and prototype testing, ensuring that their desired requirements were incorporated into the final device. From this process, a low-cost, portable, weight support device was manufactured with supports for both the upper arm and forearm. Furthermore, an external feedback system was created to provide real-time feedback to the user to help motivate and encourage them to engage in independent practice at home with the weight support device. Testing the device and feedback system with participants in their home environment showed that it was acceptable for home use, suggesting that it could be feasible for aiding with the facilitation of self-practice. Further refinements towards range of motion and portability of the device will be required as desired by participants in addition to providing a diverse range of feedback applications to engage with

Reconstructing the Spatial and Temporal Patterns of Daily Life in the 19th Century City: A Historical GIS Approach

In recent years, historians and historical geographers have become interested in the use of GIS to study historical patterns, populations, and phenomena. The result has been the emergence of a new discipline, historical GIS. Despite the growing use of GIS across geography and history, the use of GIS in historical research has been limited largely to visualization of historical records, database management, and simple pattern analysis. This is, in part, due to a lack of accessible research on methodologies and spatial frameworks that outline the integration of both quantitative and qualitative historical sources for use in a GIS environment. The first objective of this dissertation is to develop a comprehensive geospatial research framework for the study of past populations and their environments. The second objective of this dissertation is to apply this framework to the study of daily life in the nineteenth-century city, an important area of scholarship for historical geographers and social historians. Other daily life studies have focused on various experiences of daily life, from domestic duties and child rearing to social norms and the experience of work in early factories. An area that has received little attention in recent years is the daily mobility of individuals as they moved about the ‘walking city’. This dissertation advances our understanding of the diurnal patterns of daily life by recreating the journey to work for thousands of individuals in the city of London, Ontario, and its suburbs in the late nineteenth century. Methodologies are created to capture past populations, their workplaces, and their relationship to the environments they called home. Empirical results outline the relationship between social class, gender, and the journey to work, as well as how social mobility was reflected through the quality of individuals’ residential and neighbourhood environments. The results provide a new perspective on daily mobility, social mobility, and environment in the late nineteenth-century city. Results suggest that individuals who were able to be upwardly socially mobile did so at the expense of substantial increases in their journey to work

The Translocal Event and the Polyrhythmic Diagram

This thesis identifies and analyses the key creative protocols in translocal performance practice, and ends with suggestions for new forms of transversal live and mediated performance practice, informed by theory. It argues that ontologies of emergence in dynamic systems nourish contemporary practice in the digital arts. Feedback in self-organised, recursive systems and organisms elicit change, and change transforms. The arguments trace concepts from chaos and complexity theory to virtual multiplicity, relationality, intuition and individuation (in the work of Bergson, Deleuze, Guattari, Simondon, Massumi, and other process theorists). It then examines the intersection of methodologies in philosophy, science and art and the radical contingencies implicit in the technicity of real-time, collaborative composition. Simultaneous forces or tendencies such as perception/memory, content/ expression and instinct/intellect produce composites (experience, meaning, and intuition- respectively) that affect the sensation of interplay. The translocal event is itself a diagram - an interstice between the forces of the local and the global, between the tendencies of the individual and the collective. The translocal is a point of reference for exploring the distribution of affect, parameters of control and emergent aesthetics. Translocal interplay, enabled by digital technologies and network protocols, is ontogenetic and autopoietic; diagrammatic and synaesthetic; intuitive and transductive. KeyWorx is a software application developed for realtime, distributed, multimodal media processing. As a technological tool created by artists, KeyWorx supports this intuitive type of creative experience: a real-time, translocal “jamming” that transduces the lived experience of a “biogram,” a synaesthetic hinge-dimension. The emerging aesthetics are processual – intuitive, diagrammatic and transversal

Transportation Behavioral Data and Climate Change

In 2017, transportation became the largest single source of greenhouse gas emissions from the United States. Globally, the 2014 Intergovernmental Panel on Climate Change report found that, without far more aggressive policies, “transportation emissions could increase at a faster rate than emissions from other energy end use sectors” reaching 12 Gt CO2-eq/year by 2050 (Sims et al., 2014). The overwhelming challenge of combatting these emissions is made far more difficult by the fact that so little is known about transportation behavior. To use a cliché – if we can’t measure it, we can’t manage it. And transportation must be managed if we are to avoid the most catastrophic consequences of climate change. In this dissertation, I propose that better data collection is necessary to achieve reduction of transportation-related emissions. Happily, advances in technology make this more feasible today than at any time in the past. The costs of massive computing resources have gone down, the world is swarming with mobile devices like smartphones and connected cars collecting massive (if messy) amounts of data, and new techniques in data science and machine learning have emerged to help get clean answers out of all that data in a privacy-appropriate manner. In some cases, these new techniques will displace older ones. In other cases, the old ways have inherent advantages. In other cases yet, fusing new and old techniques will yield the most productive results.In Chapter One, I lay out a framework to organize the types of transportation behavioral data that must be collected regularly to adequately measure and manage transportation’s impact on climate. This builds on classic climate impact frameworks, adapting them to the particular measurement challenges presented by transportation. In Chapter Two, I provide a history of US transportation data collection since World War II as well as a review of traditional, modern, and emerging transportation data collection technologies. I then map each technology onto each behavioral data collection need identified in Chapter One, matching each behavior to the best respective data collection technique.Chapters Three and Four provides an example of analysis done using the traditional data collection techniques, notably Household and Commercial Travel Surveys, to explore changes in PMT related to shopping and retail freight since 1969, as well as freight for fuel transportation. They demonstrate and take advantage of the key benefits of traditional techniques: that they go back in history, that they collect clearly stated trip purposes, vehicle occupancies, demographics (including gender, an important demographic but particularly difficult to deduce from the new data collection sources), trip distances, chaining behavior, commodities logged, and more. As it turns out, these benefits are critical: the historical trends of the past 40 years allow behavioral insight that would not have been possible with a shorter term study, and gender dynamics are key to understanding the behaviors at hand. However, the analysis in Chapters Three and Four also highlights some of the key limitations of survey-based analysis. The fact that data was only collected every five to ten years severely limits the analysis, such as limiting the exploration that can be done on the impacts of the Great Recession. In addition, fallibilities in human memory are especially pronounced in short trips, trip chains, and non-work related trips, all of particular importance to this study. Chapters Five lays out theoretically, and then Chapter Six demonstrates via case study in India, how personal GPS diary devices can be used to log detailed data about individual trips. It demonstrates the key benefit of this data – highly individualized characteristics. Taking the example of vehicle electrification, this chapter demonstrates two ways such granular data is important: in one example, such data to give feedback to an individual to influence their car buying behavior. In the second, the granularity found with this new data collection techniques reveals the importance of highly localized policy making and emissions modeling based on driving patterns in different cities.Chapter Seven uses the emerging technology of mass amounts of locational data, collected passively via smart phones, to explore how urban density at home and work interacts with total, work-related, and non-work-related miles driven. This demonstrates the great strength of this type of data – massive sample size combined with high spatial granularity and longitudinal data collection. These strengths enable the analysis at statistically meaningful scale of patterns across many geographies, individuals, and times of year. Thus, this data can shed light on questions about the relationship of density and miles travelled which previously have not been answered conclusively due to data constraints

Human Machine Interfaces for Teleoperators and Virtual Environments

In Mar. 1990, a meeting organized around the general theme of teleoperation research into virtual environment display technology was conducted. This is a collection of conference-related fragments that will give a glimpse of the potential of the following fields and how they interplay: sensorimotor performance; human-machine interfaces; teleoperation; virtual environments; performance measurement and evaluation methods; and design principles and predictive models

Evaluating Human Performance for Image-Guided Surgical Tasks

The following work focuses on the objective evaluation of human performance for two different interventional tasks; targeted prostate biopsy tasks using a tracked biopsy device, and external ventricular drain placement tasks using a mobile-based augmented reality device for visualization and guidance. In both tasks, a human performance methodology was utilized which respects the trade-off between speed and accuracy for users conducting a series of targeting tasks using each device. This work outlines the development and application of performance evaluation methods using these devices, as well as details regarding the implementation of the mobile AR application. It was determined that the Fitts’ Law methodology can be applied for evaluation of tasks performed in each surgical scenario, and was sensitive to differentiate performance across a range which spanned experienced and novice users. This methodology is valuable for future development of training modules for these and other medical devices, and can provide details about the underlying characteristics of the devices, and how they can be optimized with respect to human performance