The Personalised Digital Human: Personalising Computational Models to Manage Neuromusculoskeletal Conditions Event as iCalendar

(Seminars)

17 October 2017

4 - 5pm

Venue: Ground floor seminar room (G10)

Location: 70 Symonds St, Auckland Central

Professor David Lloyd

A Bioengineering seminar by Prof. David Lloyd, Professor of Neuromusculoskeletal Biomechanics in the School of Allied Health Sciences and leader of Core Group in Innovations in Health Technology, Menzies Health Institute Queensland at Griffith University.

Abstract

In the near future the Personalised Digital Human, a hybrid of personalised big data and machine learning, rigid body neuromusculoskeletal and finite element computational models, will have many uses. These uses include the refined diagnosis and prognosis of neuromusculoskeletal conditions, design, development and virtual testing of patient-specific medical implants, or personalised real-time rehabilitation devices to manage neuromusculoskeletal conditions. The Personalised Digital Human are simulation models that are built by fusing motion capture and medical imaging, and we have shown that predictive accuracy of these models requires personalised representations of various characteristics of the neuromusculoskeletal system; including three-dimensional musculoskeletal geometry, joint articulations, muscle and tendon physiological properties, movement patterns, and neural solutions for movement. Moreover, the personalised characteristics resulting from pathology (e.g. anterior cruciate ligament reconstruction, total knee replacement, or Achilles tendinopathy; cerebral palsy) have considerable effects on movement and musculoskeletal tissue loading. We are currently developing, validating and building high-fidelity personalised representations of an individual, and this process is being currently streamlined and automated. Nevertheless, the process of building the models can be a very expensive and time-consuming. To rapidly build the Personalised Digital Human we need to create databases with high-fidelity neuromusculoskeletal characteristics from normal healthy individuals across the life span and different ethnic groups, but also from patient’s in different pathological populations. These databases, combined with different data mining techniques, can be used with sparse data collected from individuals to reconstruct their personalised computational model. We propose that teams of researchers are required to build the databases using the current medical imaging and new computational methods to create the Personalised Digital Human.

About the Speaker

David Lloyd is Professor of Neuromusculoskeletal Biomechanics in the School of Allied Health Sciences and leader of Core Group in Innovations in Health Technology, Menzies Health Institute Queensland at Griffith University. David chairs the Gold Coast Orthopaedic Research and Education (GCORE) alliance, between Griffith University, Gold Coast University Hospital and other private hospitals on the Gold Coast, is an Adjunct Professor at the University of Western Australia in Human Science and in Mechanical Engineering, and a Fellow of the International Society of Biomechanics. He is mechanical engineer who first worked in the aeronautical industry, but went on to complete a PhD and post-doctoral training in biomechanical engineering and neurophysiology. David is an internationally renowned biomechanical engineer, and with his research team they have developed motion analysis and computer simulation methods to study the causes, prevention and rehabilitation of musculoskeletal injury and disease. Their procedures to study sport injuries are copied the world over, as are their computer simulation methods that are being adopted for orthopaedics and neurorehabilitation applications. From this research they have developed highly effective training programs proven to prevent knee injuries in community sport. David’s team is currently developing accurate personalised digital models of humans with real-time computational technologies by combining data from laboratory-based instrumentation, multimodal medical imaging and wireless wearable devices. David works with hospitals and sporting organisations, and medical imaging, orthopaedic, and wearable device companies. He has over 190 publications in scientific journals, with a Google H index of 49, and has attracted more than $AUD16.7Million in funding from over 70 grants.