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Design interfaces to support driver interactions with highly automated vehicles.
PI: Dr. H.-Y. Winnie Chen
Our roadways are gradually filled with vehicles with increasing automation capabilities. However, the majority of these highly automated vehicles will continue to rely on drivers taking back vehicle control when the autonomous agent has reached their system boundaries. This research aims to investigate the potential of auditory modality beyond simple alerts by incorporating sonification into the driver-automation interface. Sonification is essentially a mapping of information to sounds, and have the potential to provide drivers with feedback beyond simple alerts. This ongoing research explores the use of continuous sonification as background cues to facilitate the driver's re-engagement in driving tasks in a highly automated vehicle.
Develop training models for drivers of highly automated and autonomous vehicles.
PI: Dr. H.-Y. Winnie Chen
As the future of autonomous vehicles draw near, driver training paradigms must be updated to reflect the new ways drivers interaction with vehicles in both supervisory and manual control roles. This research has the dual objectives of i) develop a training model to address unique drivers challenges in using autonomous vehicles, and ii) design a game-based driver training application.
Support care planning activities across multiple care settings.
Healthcare is amid a shift from consumer care to quality care referred to value based care. Providers are judged on a metric basis resulting in a score on the quality of care. A care plan is a piece of the puzzle which helps to drive a patient to be an active participant in their health as well as to support a holistic awareness in the patients care team. This research focuses on a human-centered design of the care planning process that values the patient as a partner in care. The ongoing research explores the use of care plans/care planning process in the current clinical environment.
Understanding health literacy barriers of Asian Immigrants with limited English proficiency.
PhD Dissertation Co-advised by Dr. H.-Y. Winnie Chen
Asian American Immigrants grew 72% between 2000 and 2015 from 11.9 to 20.4 million and are projected to be the largest foreign-born group by 2055 (Pew Research Center). Several studies reported that inadequate health literacy (HL) is linked to the poor health status of different ethnic groups, including Asian Immigrants, even when education and other health status predictors are controlled. Despite the marked increase in the population, there is limited research addressing HL issues of Asian immigrants. Few studies demonstrated that Limited English Proficiency (LEP) is the major barrier to the HL of Asian Americans and other racial/ethnic groups. LEP people find it difficult to access and navigate through health-care system and to read/understand medical instructions/prescriptions and health information. The objective of this particular project is to investigate the potential health literacy barriers of Asian LEP Immigrants from the perspective of human information processing, learning capacity and decision making process.
© 2020 ACE Lab. All Rights Reserved | Design by W3layouts