جست‌وجوی استاد و پژوهشگر

Thurmon Lockhartمشاهده پروفایل

استاد

• Fall risk prediction
• Movement Disorders
• Gait and Posture
• +۷ مورد دیگر

Dr. Thurmon Lockhart serves as the Inaugural MORE Foundation Professor of Life in Motion in the School of Biological and Health Systems Engineering at Arizona State University. He additionally holds positions as Research Affiliate Professor at Mayo Clinic College of Medicine, Division of Endocrinology, and as Adjunct Professor at Barrow Neurological Institute. Dr. Lockhart previously held faculty positions at Virginia Tech from 2000-2014, progressing from Assistant to full Professor in the Industrial and Systems Engineering Department and the Virginia Tech/Wake Forest School of Biomedical Engineering and Science. Dr. Lockhart earned his Ph.D. in Industrial and Systems Engineering from Texas Tech University in 2000, with his dissertation focusing on the Biomechanics of Slips and Falls. His academic journey includes progression through academic ranks at Virginia Tech before joining Arizona State University as a full Professor in 2014. Dr. Lockhart's research primarily centers on identifying injury mechanisms and quantifying sensorimotor deficits related to aging and neurological disorders, with particular emphasis on fall accidents. His expertise spans biomechanical modeling, nonlinear dynamics, human postural control, gait mechanics, and wearable biosensor design. His work bridges engineering and biomedical principles to develop clinical solutions for injury prevention. Current research directions involve collecting real-time physiological data about health behaviors (fall risk, fatigue, frailty) using wearable systems with sensors including PPG, Graphene sensors, EMG, FMG, and ECG, followed by utilizing computational methods based on nonlinear dynamics and chaos theory to extract actionable intelligence and predict behavioral declines using machine learning and deep neural networks. Analysis of Dr. Lockhart's recent publications reveals a strong focus on fall risk prediction technology using wearable systems, with particular attention to applications for elderly populations and those with movement disorders like Parkinson's disease. His work consistently integrates engineering principles with clinical applications, emphasizing nonlinear dynamics approaches to analyze gait and posture. The research shows increasing sophistication in sensor technology and data analysis methods, with growing emphasis on machine learning applications for predictive analytics in fall risk assessment. Alexander C. Williams, Jr., Design Award (Human Factors and Ergonomics Society, 2008) ADA Disability Research Award (2007) Liberty Mutual Best Paper Award (Published in Ergonomics, 2003-2004) (2005) The Whitaker Foundation Biomedical Engineering Grant Investigator (2003) CDC/NIH Special Emphasis Research Career Award (SERCA K01) (2001) ARCS Scholar, Achievement Rewards for College Scientists (1999) Dr. Lockhart has advised numerous students through his teaching of courses including Biomechanics for BME, Honors Directed Study, and Honors Thesis. His research has been supported by substantial funding from diverse sources including the National Science Foundation (NSF), CDC, NIH, National Institute of Occupational Safety and Health (NIOSH), Office of Naval Research (ONR), Department of Labor (DOL), Whitaker Foundation, Los Alamos National Laboratory, UPS, ITT, and others. Current projects include ExoBoot research funded by The Henry M. Jackson Foundation ($224,997), Combat Readiness research with DOD/ARMY ($49,250), Fall Detection Tools development with NSF ($75K), and Adult Bathing Surface Standards Development with CPSC ($340,667). Dr. Lockhart directs the Locomotion Research Laboratory, which focuses on human movement, gait and posture analysis, and wearable sensor development. His laboratory work integrates biomechanical modeling with clinical applications, particularly in fall risk assessment and prevention. The lab collaborates extensively with medical institutions including Mayo Clinic and Barrow Neurological Institute, creating a strong bridge between engineering innovation and clinical practice.

• Cognitive Neuroscience
• Visual Perception
• Perceptual Learning
• +۵ مورد دیگر

Professor Caspar M. Schwiedrzik is a Research Professor in the Department of Cognitive Neurobiology at the Faculty of Biology and Biotechnology, Ruhr University Bochum. He serves as a Principal Investigator at the Research Department of Neuroscience, where he leads a research group investigating the neural basis of learning and cognitive flexibility. His research focuses on understanding how organisms adapt to changing environments through perceptual learning mechanisms, with particular emphasis on the visual system. Professor Schwiedrzik employs a comparative approach across species using multimodal techniques including electrophysiology, neuroimaging, and computational modeling to identify fundamental principles of neural adaptation. His work bridges cognitive neuroscience, vision science, and computational approaches to unravel how the brain detects environmental changes and adjusts behavior accordingly. Analysis of recent publications (2015-2024) reveals a consistent research trajectory focused on visual perception, face processing, and learning mechanisms. The work demonstrates increasing methodological sophistication with a shift toward more complex questions about predictive coding, neural plasticity, and cross-species comparisons. Key trends include growing emphasis on top-down processing mechanisms, the role of statistical learning in visual adaptation, and the neural basis of perceptual generalization. Professor Schwiedrzik has established productive collaborations with leading neuroscience institutions, as evidenced by co-authorships with researchers from institutions including New York University. His research program appears well-funded, supporting multiple high-impact publications annually in top neuroscience journals. The lab maintains strong international connections while being firmly rooted in the neuroscience research ecosystem at Ruhr University Bochum. The lab focuses on understanding the brain's capacity for adaptation to environmental changes, particularly through visual learning mechanisms. Current projects investigate how predictions shape visual processing, how perceptual learning generalizes across different effectors, and how neural representations support flexible decision-making. This research provides fundamental insights into both normal cognitive function and potential pathways to maladaptive states when learning mechanisms fail.