622 research outputs found
Usefulness and Usability of a Personal Health Record and Survivorship Care Plan for Colorectal Cancer Survivors: Survey Study
Background: As a result of improvements in cancer screening, treatment, and supportive care, nearly two-thirds of individuals diagnosed with colorectal cancer (CRC) live for 5 years after diagnosis. An ever-increasing population of CRC survivors creates a need for effective survivorship care to help manage and mitigate the impact of CRC and its treatment. Personal health records (PHRs) and survivorship care plans provide a means of supporting the long-term care of cancer survivors.
Objective: The purpose of this study is to characterize the usefulness of a CRC PHR and survivorship care plan and to describe the usability of these technologies in a population of CRC survivors. To our knowledge, this is the first study to assess a PHR and survivorship care plan specifically targeting CRC survivors.
Methods: Twenty-two patients with CRC were recruited from surgery clinics of an academic medical center and Veterans Affairs hospital in Indianapolis and provided access to an online Colorectal Cancer Survivor’s Personal Health Record (CRCS-PHR). Survey data were collected to characterize the usefulness of the CRCS-PHR and describe its usability in a population of CRC survivors. CRC survivors were surveyed 6 months after being provided online access. Means and proportions were used to describe the usefulness and ease of using the CRC website. Open-ended questions were qualitatively coded using the constant comparative method.
Results: CRC survivors perceived features related to their health care (ie, summary of cancer treatment history, follow-up care schedule, description of side effects, and list of community resources) to be more useful than communication features (ie, creating online relationships with family members or caregivers, communicating with doctor, and secure messages). CRC survivors typically described utilizing traditional channels (eg, via telephone or in person) to communicate with their health care provider. Participants had overall positive perceptions with respect to ease of use and overall satisfaction. Major challenges experienced by participants included barriers to system log-in, lack of computer literacy or experience, and difficulty entering their patient information.
Conclusions: For CRC, survivors may find the greater value in a PHR’s medical content than the communication functions, which they have available elsewhere. These findings regarding the usefulness and usability of a PHR for the management of CRC survivorship provide valuable insights into how best to tailor these technologies to patients’ needs. These findings can inform future design and development of PHRs for purposes of both cancer and chronic disease management
MIRIAM: A Multimodal Chat-Based Interface for Autonomous Systems
We present MIRIAM (Multimodal Intelligent inteRactIon for Autonomous
systeMs), a multimodal interface to support situation awareness of autonomous
vehicles through chat-based interaction. The user is able to chat about the
vehicle's plan, objectives, previous activities and mission progress. The
system is mixed initiative in that it pro-actively sends messages about key
events, such as fault warnings. We will demonstrate MIRIAM using SeeByte's
SeeTrack command and control interface and Neptune autonomy simulator.Comment: 2 pages, ICMI'17, 19th ACM International Conference on Multimodal
Interaction, November 13-17 2017, Glasgow, U
Come Closer: The Effects of Robot Personality on Human Proxemics Behaviours
Social Robots in human environments need to be able to reason about their
physical surroundings while interacting with people. Furthermore, human
proxemics behaviours around robots can indicate how people perceive the robots
and can inform robot personality and interaction design. Here, we introduce
Charlie, a situated robot receptionist that can interact with people using
verbal and non-verbal communication in a dynamic environment, where users might
enter or leave the scene at any time. The robot receptionist is stationary and
cannot navigate. Therefore, people have full control over their personal space
as they are the ones approaching the robot. We investigated the influence of
different apparent robot personalities on the proxemics behaviours of the
humans. The results indicate that different types of robot personalities,
specifically introversion and extroversion, can influence human proxemics
behaviours. Participants maintained shorter distances with the introvert robot
receptionist, compared to the extrovert robot. Interestingly, we observed that
human-robot proxemics were not the same as typical human-human interpersonal
distances, as defined in the literature. We therefore propose new proxemics
zones for human-robot interaction.Comment: Author Accepted Manuscript- 8 pages, RO-MAN'23, 32nd IEEE
International Conference on Robot and Human Interactive Communication
(RO-MAN), August 2023, Busan, South Kore
Challenges in Collaborative HRI for Remote Robot Teams
Collaboration between human supervisors and remote teams of robots is highly
challenging, particularly in high-stakes, distant, hazardous locations, such as
off-shore energy platforms. In order for these teams of robots to truly be
beneficial, they need to be trusted to operate autonomously, performing tasks
such as inspection and emergency response, thus reducing the number of
personnel placed in harm's way. As remote robots are generally trusted less
than robots in close-proximity, we present a solution to instil trust in the
operator through a `mediator robot' that can exhibit social skills, alongside
sophisticated visualisation techniques. In this position paper, we present
general challenges and then take a closer look at one challenge in particular,
discussing an initial study, which investigates the relationship between the
level of control the supervisor hands over to the mediator robot and how this
affects their trust. We show that the supervisor is more likely to have higher
trust overall if their initial experience involves handing over control of the
emergency situation to the robotic assistant. We discuss this result, here, as
well as other challenges and interaction techniques for human-robot
collaboration.Comment: 9 pages. Peer reviewed position paper accepted in the CHI 2019
Workshop: The Challenges of Working on Social Robots that Collaborate with
People (SIRCHI2019), ACM CHI Conference on Human Factors in Computing
Systems, May 2019, Glasgow, U
A framework to estimate cognitive load using physiological data
Cognitive load has been widely studied to help understand human performance. It is desirable to monitor user cognitive load in applications such as automation, robotics, and aerospace to achieve operational safety and to improve user experience. This can allow efficient workload management and can help to avoid or to reduce human error. However, tracking cognitive load in real time with high accuracy remains a challenge. Hence, we propose a framework to detect cognitive load by non-intrusively measuring physiological data from the eyes and heart. We exemplify and evaluate the framework where participants engage in a task that induces different levels of cognitive load. The framework uses a set of classifiers to accurately predict low, medium and high levels of cognitive load. The classifiers achieve high predictive accuracy. In particular, Random Forest and Naive Bayes performed best with accuracies of 91.66% and 85.83% respectively. Furthermore, we found that, while mean pupil diameter change for both right and left eye were the most prominent features, blinking rate also made a moderately important contribution to this highly accurate prediction of low, medium and high cognitive load. The existing results on accuracy considerably outperform prior approaches and demonstrate the applicability of our framework to detect cognitive load
Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista
Studying Human-Robot Interaction over time can provide insights into what
really happens when a robot becomes part of people's everyday lives. "In the
Wild" studies inform the design of social robots, such as for the service
industry, to enable them to remain engaging and useful beyond the novelty
effect and initial adoption. This paper presents an "In the Wild" experiment
where we explored the evolution of interaction between users and a
Robo-Barista. We show that perceived trust and prior attitudes are both
important factors associated with the usefulness, adaptability and likeability
of the Robo-Barista. A combination of interaction features and user attributes
are used to predict user satisfaction. Qualitative insights illuminated users'
Robo-Barista experience and contribute to a number of lessons learned for
future long-term studies.Comment: Author Accepted Manuscript, 8 pages, RO-MAN'23, 32nd IEEE
International Conference on Robot and Human Interactive Communication
(RO-MAN), August 2023, Busan, South Kore
The Use of a Non-Point Source Pollution Self-Assessment for Greenhouse and Nursery Operators in California
Water quality rules adopted in 2001 in San Diego, California, created new requirements for greenhouse and plant nursery growers to manage surface run-off that could potentially affect drinking water, recreational locations, and wildlife habitat. A Run-off and Non-Point Source Pollution Self-Assessment for Greenhouse and Container Nurseries was developed as a series of worksheets that translated technical information for growers to meet legal requirements, maintain their property value, and enhance the quality of their environment. Self-assessment results determined a need for additional training on run-off management and prevention pollution through more site-specific fertilization and pest management techniques based on routine monitoring
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