Development of a parameterised mathematical model for hand/digit motion

Lead Research Organisation: University of Warwick
Department Name: Sch of Engineering


1=Assistive technology, rehabilitation and musculoskeletal biomechanics
2=Healthcare technologies
The 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.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/T51794X/1 30/09/2020 29/09/2025
2536138 Studentship EP/T51794X/1 11/01/2021 10/07/2024 Panagiotis Tsakonas
Description In this project we developed a novel parameterised mathematical model of finger and joint motion in order to simulate the natural finger movement. The main discoveries of the project so far were the novel experimental procedure devised that allowed the determination of the novel mathematical model parameters that form the passive moment generated at each joint of a human finger. These parameters are attributed to the surrounding connective tissue, the synovial fluid, and the tendons that pass through each joint. These have been modelled as a spring and damper system. These parameters have been identified for 23 able-bodied individuals. The proposed experiment was to observe the motion of each finger segment during the unloading phase of the spring like component of the passive moment, by manually moving each finger segment at an arbitrary angle within its range of motion and then releasing it. The results of the study showed that the corresponding movement has an overshoot about its equilibrium state which is indicative of an underdamped motion. This characteristic behaviour has never been observed before in the literature. To facilitate subject specific modelling scaling functions have been created between the determined parameters and finger/ palm dimensions for future use. Furthermore, an investigation on the cylindrical approximation of the fingers and a parallelepiped approximation for the palm was also investigated using the Archimedes' water displacement principal to determine the mass of the hand and compare the results against the theoretical mass of the hand determined from the previous two geometric approximations. The results of the study showed that the geometric approximations used for the fingers and palm are valid, and from a modelling perspective they can be used to determine the mass and moments of inertia of finger segments. Lastly, revised scaling functions that allow the determination of finger segment lengths and radii from palm dimensions have been constructed. These functions can be used to tailor prosthetics to the anthropometry of the individual. The study was granted full approval from the Biomedical and Scientific Research Ethics Committee (BSREC) at the University of Warwick (ref. Number: BSREC 55/21-22).
Exploitation Route The main outcomes of the study to date were that under the assumption that finger segments can be considered as cylindrical objects with a specific density of ?=1.16 gr/cm^3 then the parameterised mathematical model developed can be applied on a subject specific basis to support the design of personalised prosthetic finger design. The scaling functions that determine segment length and radius from palm dimensions can be used by others when trying to create prosthetics that are tailored to the individual. Lastly, the parameter estimation alongside the novel mathematical model can be used by others to replicate the results found during the study and to be used for further exploration of the kinematics of the fingers.
Sectors Healthcare