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Crowd sensing (CS) is an approach to collecting many samples of a phenomena of interest by distributing the sampling across a large number of individuals. While any one individual may not provide sufficient samples, aggregating samples across many individuals provides high-quality, high-coverage measurements of the phenomena. Thus, for participatory sensing to be successful, one must motivate a large number of individuals to participate. In this work, we review a variety of incentive mechanisms that motivate people to contribute to a CS effort. We then establish a set of design constraints or minimum requirements that any incentive mechanism for CS must have. These design constrains are then used as metrics to evaluate those approaches and determine their advantages and disadvantages. We also contribute a taxonomy of CS incentive mechanisms and show how current systems fit within this taxonomy. We conclude with the identification of new types of incentive mechanisms that require further investigation.

Instructions are an important aspect of virtual reality serious games since they are crucial to understanding what is expected from the user. User friendly instructions can contribute positively to the user experience, while confusing instructions can degrade it. There are various methods of instruction giving. In this study, we examine the effects of four different instruction methods on user experience in virtual reality serious games. The four instruction methods that were explored in our study are 3D animated, pictograph, written and verbal instructions. Eight simple vocational tasks were designed and implemented to be performed in an immersive virtual warehouse environment. A user study was performed with 15 adult participants. Results revealed that animated instructions provided better user experience among the four methods. Pictograph and written instructions shared similar mid-range rankings. Verbal instructions were the least preferred method. In this paper, we present our experiment design, results and discussions of our implications for future virtual reality serious game studies.

Virtual reality systems are seeing growing use for training individuals with Autism Spectrum Disorder ASD. Although the tested systems indicate effective use of virtual reality for training, there is little work in the literature evaluating different virtual reality interaction techniques for this specific group of audience. Individuals with ASD are stated to have different characteristics and perceptions. This requires careful exploration of good design principles in interaction. This paper presents design and preliminary evaluation of interaction techniques for individuals with ASD to be used in a highly immersive virtual reality vocational training system VR4VR [1]. The system includes motion tracking cameras, a head mounted display, real time tracked objects, and several interaction tools such as haptic device and touchscreen. In this system, tangible object manipulation, haptic device interaction, touch and snap technique and touchscreen interaction were implemented for object selection and manipulation; real walking and walk in place techniques were implemented for locomotion. A user study was performed with five individuals with ASD who had no prior VR experience. The preliminary testing results and observations that show the preference of the users with ASD on the implemented interaction techniques are shared in this paper with the aim of contributing to the future studies that utilize VR for individuals with ASD.

This paper provides key insights into the construction and evaluation of interpersonal simulators?systems that enable interpersonal interaction with virtual humans. Using an interpersonal simulator, two studies were conducted that compare interactions with a virtual human to interactions with a similar real human. The specific interpersonal scenario employed was that of a medical interview. Medical students interacted with either a virtual human simulating appendicitis or a real human pretending to have the same symptoms. In Study I (n = 24), medical students elicited the same information from the virtual and real human, indicating that the content of the virtual and real interactions were similar. However, participants appeared less engaged and insincere with the virtual human. These behavioral differences likely stemmed from the virtual human's limited expressive behavior. Study II (n = 58) explored participant behavior using new measures. Nonverbal behavior appeared to communicate lower interest and a poorer attitude toward the virtual human. Some subjective measures of participant behavior yielded contradictory results, highlighting the need for objective, physically-based measures in future studies.

This paper presents a virtual reality for vocational rehabilitation system (VR4VR) that is currently in development at the University of South Florida's Center for Assistive, Rehabilitation, and Robotics Technologies (CARRT). VR4VR utilizes virtual reality to assess and train individuals with severe cognitive and physical disabilities. Using virtual reality offers several advantages such as being inexpensive, safer and easily adjustable to different user needs through customization of environments, content and real time interventions. The system is composed of the following components: a virtual reality training area surrounded by an optical motion tracking system, a curved screen with two projectors, a server computer, a remote control interface on a tablet computer for job coaches, and a virtual assistive robot. This paper focuses on virtual reality training for underserved individuals with cognitive disabilities, such as autism spectrum disorder (ASD) and traumatic brain injury (TBI). We describe six transferrable skill modules and corresponding design considerations. Future work focuses on people with severe mobility impairment, such as spinal cord injury (SCI).

Advances in pervasive computing, machine learning, and human activity recognition are changing preventive health care. Emerging paradigms, such as Mobile Cyber-Physical System (MCPS) and Just-in-time interventions (JITI), allow patients to take health monitoring, diagnosis, therapy and treatments beyond traditional medical settings. These paradigms empower patients by delivering health care at any place and at any time. MCPS provides the necessary engineering support to enable JITI systems to work in an autonomous way. In this work, we review the recent trends in the design of Mobile Cyber-Physical systems for Just-in-time interventions (MCP-JITI), and the different engineering concepts behind this paradigm. Finally, we discuss a set of necessary requirements or design issues to successfully deploy in real world scenarios. This discussion is driven by the description of the MCP-JITI architecture and the interconnections among its components.

Crowd sensing (CS) is an approach that consists of collecting many samples of a phenomena of interest by distributing the sampling process across a large number of individuals. In this work, we address the effect of cooperation among individuals by modeling a recurrent CS task as a repeated game. In this game, participants are the players of the corresponding game, and every round of the CS task is considered as a single-shot game which is repeated over time. In this model, participants compete and cooperate with each other in order to sell their samples. We represent the participants evolutionary behaviors by a graph network in which all the individuals make utilities in the long run. We show that although a pure competition approach faces problems such as the continuous drop-out of participants and the raise of prices of samples, this hybrid approach keeps the prices of samples low while maintaining the required number of participants.

The purpose of this paper is, first, to summarize a theoretical perspective toward the development of a virtual reality innovation in education. Next, we will describe a virtual character project that is impacting the training of medical students in two institutions. In doing so, we will present a summary of three studies completed over the last 2 years, highlighting specific results from the research. Finally, we conclude with a discussion of the impact of these findings on the development and implementation of virtual reality systems for teaching and learning. It is our hope that through providing this study of a virtual reality scenario—experienced by over 100 end-users—from an educational concepts perspective will help others aiming to apply virtual reality to education.

This paper presents our experiences in evolving the Virtual Objective Structured Clinical Exam (VOSCE) system. This system allows medical students to experience the interaction between a patient and a medical doctor using natural methods of interaction with a high level of immersion. These features enable the system to provide training on medical communication skills. We discuss the experiences of a group of medical and physician assistant students that pilot tested the system. Further, we examine the impact of evolving the system based on their feedback. The VOSCE system's performance in subsequent studies has indicated that end-user feedback improvements have significantly impacted overall performance and efficacy.

Stress can lead to headaches and fatigue, precipitate addictive behaviors (e.g., smoking, alcohol and drug use), and lead to cardiovascular diseases and cancer. Continuous assessment of stress from sensors can be used for timely delivery of a variety of interventions to reduce or avoid stress. We investigate the feasibility of continuous stress measurement via two field studies using wireless physiological sensors --- a four-week study with illicit drug users (n = 40), and a one-week study with daily smokers and social drinkers (n = 30). We find that 11+ hours/day of usable data can be obtained in a 4-week study. Significant learning effect is observed after the first week and data yield is seen to be increasing over time even in the fourth week. We propose a framework to analyze sensor data yield and find that losses in wireless channel is negligible; the main hurdle in further improving data yield is the attachment constraint. We show the feasibility of measuring stress minutes preceding events of interest and observe the sensor-derived stress to be rising prior to self-reported stress and smoking events.

We present a mobile avatar system designed to provide a constant user-avatar interface for health behavior change therapy. The presented Android application replaces the user's phone background with an animated avatar. The avatar's level of physical activity is made to match the physical activity level of the user. This activity level is inferred using a decision-tree-based frequency analysis of the built-in phone accelerometers. User physical activity data collected is also sent via a mobile analytics platform (Countly) to be stored in a server. Also included in our demo is a simple website which pulls information from this server and places a user's avatar among other people's avatars. In this display a user can see how their avatar's physical activity compares to others', and observe their real-life physical activity behavior directly impacting the performance of their avatar in the virtual world.

The combination of inexpensive wearable sensors, powerful mobile phones, and always-connected cloud computing are enabling new, real-time feedback and coaching via mobile technologies. This paper explores the use of avatars - digital representations of the self - as an ideal user interface for mobile health application. Specifically, a justification for using avatars is provided, both based on empirical studies and the psychology of human body interpretation. We then provide an organized, theoretical description of how an avatar's traits (appearance, behavior, and virtual environment) can be manipulated to convey specific health-related behavior change messages.

A convergence between consumer electronics and virtual reality is occurring. We present an immersive head-mounted-display-based, wearable 3D user interface that is inexpensive (less than $900 USD), robust (sourceless tracking), and portable (lightweight and untethered). While the current display has known deficiencies, the user tracking quality is within the constraints of many existing applications, while the portability and cost offers opportunities for innovative applications that are not currently feasible.

We introduce a new paradigm of collaborative computing called the Ubiquitous Collaborative Activity Virtual Environment (UCAVE). UCAVEs are portable immersive virtual environments that leverage mobile communication platforms, motion trackers and displays to facilitate ad-hoc virtual collaboration. We discuss design criteria and research challenges for UCAVEs, as well as a prototype hardware configuration that enables UCAVE interactions using modern smart phones and head mounted displays.

The effect of psychosocial stress on health has been a central focus area of public health research. However, progress has been limited due a to lack of wearable sensors that can provide robust measures of stress in the field. In this paper, we present a wireless sensor suite called AutoSense that collects and processes cardiovascular, respiratory, and thermoregularity measurements that can inform about the general stress state of test subjects in their natural environment. AutoSense overcomes several challenges in the design of wearable sensor systems for use in the field. First, it is unobtrusively wearable because it integrates six sensors in a small form factor. Second, it demonstrates a low power design; with a lifetime exceeding ten days while continuously sampling and transmitting sensor measurements. Third, sensor measurements are robust to several sources of errors and confounds inherent in field usage. Fourth, it integrates an ANT radio for low power and integrated quality of service guarantees, even in crowded environments. The AutoSense suite is complemented with a software framework on a smart phone that processes sensor measurements received from AutoSense to infer stress and other rich human behaviors. AutoSense was used in a 20+ subject real-life scientific study on stress in both the lab and field, which resulted in the first model of stress that provides 90% accuracy.

Any new tool introduced for education needs to be validated. We developed a virtual human experience called the Virtual Objective Structured Clinical Examination (VOSCE). In the VOSCE, a medical student examines a life-size virtual human who is presenting symptoms of an illness. The student is then graded on interview skills. As part of a medical school class requirement, thirty three second year medical students participated in a user study designed to determine the validity of the VOSCE for testing interview skills. In the study, participant performance in the VOSCE is compared to participant performance in the OSCE, an interview with a trained actor. There was a significant correlation (r(33)=.49, p

This paper presents a system which allows medical students to experience the interaction between a patient and a medical doctor using natural methods of interaction with a high level of immersion. We also present our experiences with a pilot group of medical and physician assistant students at various levels of training. They interacted with projector-based life-sized virtual characters using gestures and speech. We believe that natural interaction and a high level of immersion facilitates the education of communication skills. We present the system details as well as the participants' performance and opinions. The study confirmed that the level of immersion contributed significantly to the experience, and participants reported that the system is a powerful tool for teaching and training. Applying the system to formal communication skills evaluation and further scenario development will be the focus of future research and refinement.