Yu LiangThe University of Tennessee at Chattanooga, USA
Title: VIGOR: A Versatile, IndiGenerative ORchestrator to motivate the movement of the people with limited Mobility
A major national concern is physical inactivity, especially among people with disabilities or chronic illnesses. To successfully promote physical activity among individuals of all ages who have chronic health issues and/or disabilities, it is vitally important to develop innovative and useful fitness strategies that are based on physical, psychological, and social factors. The goal of this study is to develop the Versatile, Individualized, and Generative ORchestrator modality (VIGOR) with AI and VR capabilities to promote Tai Chi Chuan (TCC), a traditional mind–body wellness and healing art, among individuals with different forms of mobility impairment. VIGOR aims to make participating in physical exercise an affordable, efficient, personally engaging, and joyful experience for people from various socioeconomic strata to advance health equity, openness, and societal harmony. VIGOR consists of the following functional modules: (1) Formulating users’ kinetic pattern using graph analysis; (2) human motion identification and scoring; (3) music-oriented sentimental formulation and analysis about TCC movement; (4) adaptive virtual limb generation and its reconstruction on virtual reality (VR) and/or active-orthosis; and (5) individualized TCC choreography (i.e., creative movement design). VIGOR integrates deep learning with a variety of domain knowledges such as physical therapy, psychological wellbeing, and athletic aesthetics. The resulting VIGOR can be altered to function with various types of movement such as Yoga and dancing.
Dr. Yu Liang is currently working at the Department of Computer Science and Engineering of University of Tennessee at Chattanooga as a Full Professor. His funded research projects cover the following areas: biomedical engineering, big-data and cloud computing, modeling and simulation, machine learning and artificial intelligence, high-performance scientific and engineering computing, numerical linear algebra, the processing and analytics of large-scale sensory data, and computational mechanics. His research work has appeared in various prestigious journals, book or book chapters, and refereed conference, workshop, and symposium proceedings. Dr. Liang is serving in the Machine Learning and Knowledge Extraction (https://www.mdpi.com/journal/make), Frontier in Aging (https://www.frontiersin.org/journals/aging ), International Journal of Smart Sensor Technologies and Applications (IJSSTA), International Journal of Security Technology for Smart Device (IJSTSD), Journal of Mathematical Research and Applications (JMRA), and Current Advances in Mathematics (CAM) as an editorial board member.