Development of a parameterised mathematical model for hand/digit motion

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1=Assistive technology, rehabilitation and musculoskeletal biomechanics2=Healthcare technologiesThe aim of this project is to develop parameterised mathematical models of upper limb, and in particular hand motion that will support the design, fabrication and validation of an affordable body-powered prosthetic fingertip digit with integrated mechanical haptic feedback. This project will form part of the larger scale PROLIMB collaborative project between the University of Warwick and University College London UCL), funded by the EPSRC. A variety of mathematical models of the hand and its motion have been developed using inverse kinematics to calculate joint angles from the known, or desired, location of the fingertip. Limitations of these techniques include overlaps and collisions in simulation, as well as mismatches between the models and actual human hand joint constraints plus such approaches are typically not designed for the multiple end goals that exist in hand motion. Other models developed to generate dynamic responses incorporating upper limb muscle forces are unsuited to our purpose due mainly to their modelling assumptions, model parameterisations or an impractical trade-off between any errors and computation time. More recently developed musculoskeletal models have also proven to be unstable and thus unsuitable for use as a controller for upper limb Forward modelling approaches have also been adopted but only proved effective for a small number of grasps and have limited validation. The state of the art, then, is substantial but there remains an indisputable need for a novel mechanistic mathematical model that can robustly characterise human hand movements and grasp taxonomies and thus serve as a platform for the design of effective upper limb and digit prostheses. Robustly parameterised and validated to function in a predictive capacity, such a model would transform our ability to design effective hand and digit prostheses. What's more, it would permit their personalisation via individualised parameterisation. These are the aims of this PhD project, to develop such a robust, parameterised mechanistic model of hand motion that can account for modern everyday grasp taxonomies. The project will develop mechanistic models to dynamically characterise and reproduce hand movements and key grasp taxonomies. This model will be developed to permit personalised, simulated predictions that can also integrate haptic feedback. The model will be validated using data collected in Vicon motion capture laboratories at the University of Warwick. An additional outcome of this task will be a corresponding 3D implementation of the model for application within a leading motion capture system for hand motion capture and analysis. In addition, these models will be integrated with signals from fingertip sensors provided by project collaborators at UCL in order to consider physical interaction with the environment when applied to body-powered prostheses, to permit a deeper understanding of the role of sensation in grasp movements and to aid rehabilitation and personalised prostheses operation.