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Understanding eye-hand coordination in object interception - a computational modelling approach

   School of Sport, Exercise and Rehabilitation Sciences

About the Project

This PhD project with Dr Yeo will focus on understanding how we perform interception. Interceptive movements--such as catching a gently thrown ball, quickly grabbing a tilting cup to avoid spilling or even just handshaking someone--feel like trivial everyday tasks for us that seemingly look too simple to study. However, our ability to generate these movements with a high degree of accuracy and flexibility far exceeds any man-made robots, and the brain’s underlying mechanisms remain largely unknown. Furthermore, failure to do so due to neuromotor diseases (such as Parkinson’s or stroke) significantly impairs the quality of life, which all together makes the study of interception an excellent research topic in movement neuroscience. Interceptive movements generally require a close collaboration between two procedures: visual information gathering (eye) and motor control (hand), and therefore scrutinizing the patterns of eye and hand movements during interception can lead us to uncover the hidden strategies of how the brain coordinates these procedures to maintain accuracy and flexibility of the interception. Previous studies, including those from our group, suggested that the eye movement exhibits two distinctive strategies during interception, called catch-up saccades and smooth pursuit, and those strategies are closely synchronised with hand movement strategies consisting of submovements in reactive-proactive phases (check video:

The goal of the project is to further examine the details of this eye-hand coordination pattern in a novel experimental environment. To capture and control the eye and hand movement patterns in three-dimensional space-time, the study will use cutting-edge robotic and VR technologies, which are newly introduced in the field of movement science; The experiment will be conducted in an immersive virtual environment, equipped with a VR head-mounted display with a built-in eye tracker and force-controlled robotic arms (Phantom and vBOT robotic system), by which the participant’s eye and hand movements can be effectively monitored and manipulated during dynamic interceptive movements. Based on our observation, we will seek to build a computational model that will advance our quantitative understanding of the brain’s interception mechanism.

The expected outcome of the study will be highly applicable to many related areas, including sport and coaching science, neuro-motor rehabilitation, and humanoid robotics. We are looking for motivated people to participate in the development of the experimental environment, data collection, and computational modelling / analysis. The ideal candidate will have a background in computer science, robotics, psychology, mathematics, physics, and have some experience (or at least a keen interest) in one or more of the following fields: human movement experiment, motion capture, eye-tracking, computer animation, virtual reality, software development.

To find out more about studying for a PhD at the University of Birmingham, including full details of the research undertaken in the School, the funding opportunities available for your subject, and guidance on making your application, you can order a copy of our Doctoral Research Prospectus, at:

Eligibility requirements: An Undergraduate Honours degree with a minimum classification of a 2.1 science BSc or a MSc or equivalent and a life science, clinical or engineering background. English Language qualification for international students.

Biological Sciences (4) Computer Science (8) Engineering (12) Mathematics (25) Medicine (26) Physics (29) Psychology (31)


Yeo, S. H., Lesmana, M., Neog, D. R., & Pai, D. K. (2012). Eyecatch: Simulating visuomotor coordination for object interception. ACM Transactions on Graphics (TOG), 31(4), 1-10.
Yeo, S. H., Wolpert, D. M., & Franklin, D. W. (2015). Coordinate representations for interference reduction in motor learning. PLoS One, 10(6), e0129388.

Fooken, J., Yeo, S. H., Pai, D. K., & Spering, M. (2016). Eye movement accuracy determines natural interception strategies. Journal of vision, 16(14), 1-1.
Yeo, S. H., Franklin, D. W., & Wolpert, D. M. (2016). When optimal feedback control is not enough: Feedforward strategies are required for optimal control with active sensing. PLoS computational biology, 12(12), e1005190.
Kim, S. Y., Kwon, J. W., Kim, J. M., Park, F. C. W., & Yeo, S. H. (2021). On the encoding capacity of human motor adaptation. Journal of Neurophysiology.

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