1338930 University of Texas at Arlington (UTA); Makedon 1338932 University of Texas at Dallas (UTD); Daescu
The proposed I/UCRC will focus on assistive technologies to enhance human performance by removing or helping to overcome physical, cognitive or operational domain obstacles and help the human reach his or her potential as much as possible. The research efforts will be anchored by the University of Texas at Arlington (UTA) as the lead institution, partnered with the University of Texas at Dallas (UTD).
Assistive technologies (AT) use computer tools and methods to increase, maintain, or improve the functional capabilities of people with disabilities, as well as to enhance the productivity of well-bodied people. ATs can improve work efficiency, identify safety risks, shorten the learning curve or worker training through simulations, improve resource allocation, creativity and communication. In healthcare environments, AT tools can enhance sensory and cognitive capabilities, improve training & delivery, enable remote monitoring, delay physical and cognitive decline in chronic conditions, personalize rehabilitation, predict risks for the elderly who live alone, monitor sleep disorders, design better prosthetics or drugs, design better robotic assistants, smart wheelchairs, therapy games and tools to monitor mental/physiological conditions, such as depression, epilepsy, or heart problems.
The center will promote the development of AT research infrastructure in industry, research centers and academia. It will help generate new jobs and new types of products and services. The proposed center will help prepare a future generation of competitive employees-scientists, and will provide new opportunities to engage students early, before graduation, in internship or research projects related to the company's interests. Both UTA and UTD, have a strong track record in training students in AT areas and have ongoing research that ranges from better ways to identify software errors, to analysis of facial expressions to identify arthritic pain, or efficient multimodal database searches.
PI: Ovidiu Daescu, Co-PI Dinesh Bhatia Awardees: University of Texas at Dallas Program Officer Email Address: rmontell@nsf.gov (703)292-2421 Introduction The objective of the iPerform center is to research and develop Assistive Technologies (AT) that focus on overcoming physical, cognitive and operational obstacles that prevent humans from reaching full potential or achieving best performance. Assistive technologies (AT) within the scope of this proposal are computer aided tools and methods to increase, maintain, or improve the functional capabilities of people with disabilities, as well as to enhance the productivity of well-bodied people. Motivation ATs have become the focus of attention of both academia and industry. The proposed I/UCRC center has the goal to bring together the two of them while performing a dual role. The first role is to support academic AT research that leads to innovation driven by industrial need. The second role is to attract industries interested in the development and commercialization of AT and to stimulate new research to help industries maintain their competitiveness. Summary of Planning Activities During the planning period, the center principal investigators identified companies interested in AT research and development. Together with the collaborating site at UTA they organized a planning workshop meeting where many of these companies were invited. A center website (iPerform.uta.edu) and center poster were developed to inform the public of the planning activities and to help new companies become members. The PIs made the planning activities known in many conferences and meetings they attended, such the Petra conference (www.petrae.org), ICCABS 2014, and PDPTA 2014. Project Outcomes and Findings Industrial contacts were established through the UTD and UTA respective Industrial Advisory Boards, as well as directly with national and international companies. Following the planning workshop, many individual meetings with companies took place in order to identify opportunities for research, development and commercialization. Following these activities, 14 companies sent commitment letters (six of them to UTD) and a full proposal was then submitted to NSF. The opportunities that were identified were connected to the strengths and track record residing in the two universities, UTA and UTD, which include: NSF-funded research on disabilities, in-place aging, rehabilitation; therapy tools for depression, arthritis, to enable assimilation into changing work environments, algorithm development and optimization, cyberphysical systems, cybersecurity, machine learning, data mining, big data analysis, software engineering, and embedded systems. Intellectual Merit The center will promote innovation in academia that is driven by industrial needs. Research and development will be conducted that improves work efficiency, shortens the learning curve of training, improves resource allocation, creativity and communication, enhances human sensory and cognitive capabilities, designs better therapies, advances research in robotics, big data analytics, cybersecurity, machine learning, user interface design and databases. Broader Impacts The planning grant helped identify critical areas of research that can greatly impact the quality of human life, reduce healthcare and productivity costs and enhance industrial and academic innovation in many areas. Example application areas that illustrate the center’s broader impacts are given below: Manufacturing: can develop tools towards improving work efficiency in the workplace, identifying risks of safety, shortening the learning curve through training simulations, improving resource allocation, smart tools to identify security leaks, computer-aided tools to accelerate the training of new workers, improving both individual and group creativity through highly effective communication methods and other. Healthcare: development of software and hardware to enhance individual sensory and cognitive capabilities; improve healthcare training and delivery; remote monitoring of persons while at home; slowing down the physical and cognitive decline associated with aging; personalized computer-enabled rehabilitation; tools to predict risks for the elderly who live at home alone; design of better prosthetics; sensors for smart skin; prosthetics, new sensors that identify location of a person or robotic assistant; smart wheelchairs; smart therapy games; tools to diagnose and treat sleep disorders; tools to correlate facial expressions with emotions, pain, sleepiness or neglect; gesture recognition; speech recognition; natural language dialogue systems; brain activity analysis, and other AT products. Learning and training: tools to improve and shorten the learning curve of individuals in different contexts. 4. Data analytics and Big Data related to human performance analysis: Software to improve the analysis of data collected during applications as described above. Cybersecurity and privacy: Tools to ensure that information and data sharing remains secure.
