Patient-Oriented Artificial Intelligence and Behavior Sensing: A New Frontier in Brain Health

ABSTRACT

Over three billion people worldwide suffer from brain health problems, leading to disabilities and death. Significant disparities in neuropsychiatric disease care exist due to clinician biases and limited access to care. For instance, more than 20 states in the United States are identified as dementia neurology deserts, only 9% of individuals with Parkinson’s Disease see movement disorder specialists, and a 20% decrease in mental health workers is expected in the next decade. This situation calls for urgent and innovative solutions to address these disparities and challenges in healthcare access. This talk will showcase Dr. Kwon’s latest research, which integrates multimodal artificial intelligence (AI) and edge and cloud computing platforms to develop scalable and ethical solutions for continuous and passive behavior monitoring systems. These cost-effective systems can effectively quantify motor, cognitive, and mental health in neuropsychiatric disorders such as Alzheimer’s Disease, Parkinson’s Disease, and Depression. Democratizing digital health tools, especially in underserved areas, has great potential to reduce morbidity, disability, and mortality by transforming standard telehealth platforms and community clinics.

BIOGRAPHY

Hyeokhyen Kwon is an Assistant Professor at the Department of Biomedical Informatics at Emory University School of Medicine, a Program Faculty of Computer Science and Informatics at Emory University, a Program Faculty at the Department of Biomedical Engineering at Emory University and Georgia Institute of Technology, and a Program Faculty of Machine Learning Center at Georgia Institute of Technology. He received his Ph.D. in Computer Science at the School of Interactive Computing at Georgia Tech, Atlanta, GA. His research focuses on designing accessible, scalable, secure, and privacy-preserving machine learning systems using distributed on- and off-body sensors to tackle healthcare challenges. His applications lie at the intersection of computer vision, machine learning, ubiquitous computing, and human activity recognition. Dr. Kwon and his team also actively collaborate with stakeholders in healthcare systems to validate the AI-driven clinical decision support systems in real-world clinics or daily living environments. His work has been published in CVPR, ICCV, Ubicomp/ISWC, IMWUT, etc. His research has been accepted for US patents and received multiple support from federal, industry, and philanthropic agencies, including NIH, Oracle, Samsung, and Cox foundations.

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