79,168 research outputs found
Examining the role of smart TVs and VR HMDs in synchronous at-a-distance media consumption
This article examines synchronous at-a-distance media consumption from two perspectives: How it can be facilitated using existing consumer displays (through TVs combined with smartphones), and imminently available consumer displays (through virtual reality (VR) HMDs combined with RGBD sensing). First, we discuss results from an initial evaluation of a synchronous shared at-a-distance smart TV system, CastAway. Through week-long in-home deployments with five couples, we gain formative insights into the adoption and usage of at-a-distance media consumption and how couples communicated during said consumption. We then examine how the imminent availability and potential adoption of consumer VR HMDs could affect preferences toward how synchronous at-a-distance media consumption is conducted, in a laboratory study of 12 pairs, by enhancing media immersion and supporting embodied telepresence for communication. Finally, we discuss the implications these studies have for the near-future of consumer synchronous at-a-distance media consumption. When combined, these studies begin to explore a design space regarding the varying ways in which at-a-distance media consumption can be supported and experienced (through music, TV content, augmenting existing TV content for immersion, and immersive VR content), what factors might influence usage and adoption and the implications for supporting communication and telepresence during media consumption
Linking recorded data with emotive and adaptive computing in an eHealth environment
Telecare, and particularly lifestyle monitoring, currently relies on the ability to detect and respond to changes in individual behaviour using data derived from sensors around the home. This means that a significant aspect of behaviour, that of an individuals emotional state, is not accounted for in reaching a conclusion as to the form of response required. The linked concepts of emotive and adaptive computing offer an opportunity to include information about emotional state and the paper considers how current developments in this area have the potential to be integrated within telecare and other areas of eHealth. In doing so, it looks at the development of and current state of the art of both emotive and adaptive computing, including its conceptual background, and places them into an overall eHealth context for application and development
Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia
Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials
Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges
Today's mobile phones are far from mere communication devices they were ten
years ago. Equipped with sophisticated sensors and advanced computing hardware,
phones can be used to infer users' location, activity, social setting and more.
As devices become increasingly intelligent, their capabilities evolve beyond
inferring context to predicting it, and then reasoning and acting upon the
predicted context. This article provides an overview of the current state of
the art in mobile sensing and context prediction paving the way for
full-fledged anticipatory mobile computing. We present a survey of phenomena
that mobile phones can infer and predict, and offer a description of machine
learning techniques used for such predictions. We then discuss proactive
decision making and decision delivery via the user-device feedback loop.
Finally, we discuss the challenges and opportunities of anticipatory mobile
computing.Comment: 29 pages, 5 figure
Overcoming barriers and increasing independence: service robots for elderly and disabled people
This paper discusses the potential for service robots to overcome barriers and increase independence of
elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly
people and advances in technology which will make new uses possible and provides suggestions for some of these new
applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses
the complementarity of assistive service robots and personal assistance and considers the types of applications and
users for which service robots are and are not suitable
Natural Notation for the Domestic Internet of Things
This study explores the use of natural language to give instructions that
might be interpreted by Internet of Things (IoT) devices in a domestic `smart
home' environment. We start from the proposition that reminders can be
considered as a type of end-user programming, in which the executed actions
might be performed either by an automated agent or by the author of the
reminder. We conducted an experiment in which people wrote sticky notes
specifying future actions in their home. In different conditions, these notes
were addressed to themselves, to others, or to a computer agent.We analyse the
linguistic features and strategies that are used to achieve these tasks,
including the use of graphical resources as an informal visual language. The
findings provide a basis for design guidance related to end-user development
for the Internet of Things.Comment: Proceedings of the 5th International symposium on End-User
Development (IS-EUD), Madrid, Spain, May, 201
Ubiquitous emotion-aware computing
Emotions are a crucial element for personal and ubiquitous computing. What to sense and how to sense it, however, remain a challenge. This study explores the rare combination of speech, electrocardiogram, and a revised Self-Assessment Mannequin to assess people’s emotions. 40 people watched 30 International Affective Picture System pictures in either an office or a living-room environment. Additionally, their personality traits neuroticism and extroversion and demographic information (i.e., gender, nationality, and level of education) were recorded. The resulting data were analyzed using both basic emotion categories and the valence--arousal model, which enabled a comparison between both representations. The combination of heart rate variability and three speech measures (i.e., variability of the fundamental frequency of pitch (F0), intensity, and energy) explained 90% (p < .001) of the participants’ experienced valence--arousal, with 88% for valence and 99% for arousal (ps < .001). The six basic emotions could also be discriminated (p < .001), although the explained variance was much lower: 18–20%. Environment (or context), the personality trait neuroticism, and gender proved to be useful when a nuanced assessment of people’s emotions was needed. Taken together, this study provides a significant leap toward robust, generic, and ubiquitous emotion-aware computing
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