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Dr. John Buckley,
Reader

Information about Dr. John Buckley at the University of Bradford.

School of Engineering
(Faculty of Eng & Digital Technologies)
Email:
j.buckley@bradford.ac.uk
Telephone:
+44 1274 234641
Photo of Dr. John Buckley

Biography

John is currently a Reader in Movement Biomechanics at the University of Bradford. John has a background in sport science and bioengineering. He joined the university in 2002 as post-doctoral research assistant in the School of Optometry and Vision Science, where he then held two research fellowships; one from the Health Foundation investigating the impact of correctable visual impairment upon balance and mobility in elderly and young subjects; and the other as an RCUK Academic fellow investigating Medical & Healthcare Technology. He moved to the School of Engineering in 2012. John’s interests are in developing and using motion analysis approaches to determine the movement adaptations and/or compensatory mechanisms used for locomotion by individuals with musculoskeletal abnormalities, problems or dysfunction, and/or by those with sensory impairment. John is a registered Clinical Scientist (Health Professions Council, UK), a member of the International Society of Biomechanics and International Society for Posture and Gait Research, and a Fellow of The Higher Education Academy.

Research

John's research interests are in developing and using biomechanical modelling to determine the movement adaptations and/or compensatory mechanisms used for locomotion by individuals with musculo-skeletal abnormalities, problems or dysfunction, and/or by those with sensory impairment. Recent work has determined how correctable visual impairment impacts balance and locomotion in older adults; if features to enhance sensorimotor control are necessary in order to gain full advantage of improved lower-limb prosthetic design; whether manipulating the appearance of steps and stairs will make them safer for older people to negotiate; and whether there is a link between visual processing abilities and elite sporting performance. Current work includes, understanding visual performance under dynamic testing conditions and its association with gait safety and fear of falling; how biomechanical outcomes from simple everyday tasks predict stairs falls risk; and how visual computing can be used to help diagnose the movement disorders associated with Parkinson’s disease.