About the Project
Recently, other methods for solving models of human movement have been described, allowing less complete datasets or data from other sensors to be used to analyse movement, and faster prediction of unmeasured movements that could be used to aid clinical planning (van den Bogert et al. 2011). The majority of work in this area has focussed on the lower limb (e.g. Dorschky et al. 2019), and indeed biomechanical computer models of the lower limb are often used to inform surgical treatment options in children with cerebral palsy. For the upper limb, such models have not reached similar widespread use, but have been shown to help in the understanding of fundamental biomechanical principles.
As a team, we have many years of experience in biomechanics and computer modelling of the upper limb, with more than 40 peer-reviewed publications in related areas (https://scholar.google.com/citations?user=Gf4QzU4AAAAJ&hl=en). Our models have been applied to clinically important problems such as the restoration of arm function in spinal cord injury (Chadwick et al., 2011), estimation of internal loading for prosthesis design, and analysis of upper limb function in manual wheelchair users.
The aim of this project will be to improve biomechanical models of the upper limb, implementing new solution methods involving optimal control, to allow clinically useful data on upper limb movement to be generated from wearable sensors such as inertial measurement units. High quality movement data from wearable sensors could increase the availability of clinical movement analysis to clinics at reduced cost and with reduced initial outlay.
Candidates should have (or expect to achieve) a UK honours degree at 2.1 or above (or equivalent) in Mechanical or Biomedical Engineering, Human Movement Science or related area.
Applicants must have a Interest in medical technology, human movement science or orthopaedics and rehabilitation. Experience of independent project work as well as working in a team along with knowledge of Mathematical modelling, mechanics, computer programming (Matlab or Python).
• Apply for Degree of Doctor of Philosophy in Engineering
• State name of the lead supervisor as the Name of Proposed Supervisor
• State ‘Self-funded’ as Intended Source of Funding
• State the exact project title on the application form
When applying please ensure all required documents are attached:
• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)
• Detailed CV
Informal inquiries can be made to Dr Ed Chadwick ([email protected]), with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ([email protected])
It is possible to undertake this project by distance learning. Interested parties should contact Dr Chadwick to discuss this. Distance Learning Applicants should have access to a good quality computer suitable for running Matlab. For guidelines on system requirements, see https://uk.mathworks.com/support/requirements/matlab-system-requirements.html.
Bolsterlee, Bart, DirkJan H. E. J. Veeger, and Edward K. Chadwick. 2013. ‘Clinical Applications of Musculoskeletal Modelling for the Shoulder and Upper Limb’. Medical & Biological Engineering & Computing 51 (9): 953–63. https://doi.org/10.1007/s11517-013-1099-5.
Ameln, Diederik J. D., Edward K. Chadwick, Dimitra Blana, and Alessio Murgia. 2019. ‘The Stabilizing Function of Superficial Shoulder Muscles Changes Between Single-Plane Elevation and Reaching Tasks’. IEEE Transactions on Biomedical Engineering 66 (2): 564–72. https://doi.org/10.1109/TBME.2018.2850522.
Bogert, Antonie J. van den, Dimitra Blana, and Dieter Heinrich. 2011. ‘Implicit Methods for Efficient Musculoskeletal Simulation and Optimal Control’. Procedia IUTAM, IUTAM Symposium on Human Body Dynamics, 2 (January): 297–316. https://doi.org/10.1016/j.piutam.2011.04.027.
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