Overview
Our work is driven by the need to find an improved method for estimating the progress of neurological diseases such as amyotrophic lateral sclerosis (ALS), a motor neurone disease (MND). Physicist Stephen Hawking is a well known victim of MND.
Motor units are the nerves that send signals to muscles to work. Each muscle group is served by several motor units, about 100-200 in the Abductor digiti minimi (hand), but these numbers vary from person to person and are only speculative. Our work provides a method to count the number of motor units, known to neurologists as Motor Unit Number Estimation (MUNE). MUNE is an international research program and we work collaboratively with researchers and clinicians in The Netherlands, US, and Australia.
- External collaborators
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Dr Gareth Ridall (QUT and Lanacaster Univeristy, UK)
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Drs Robert Henderson
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Pamela McCombe of the Royal Brisbane and Women's Hospital
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Professor Nial Friel (University College, Dublin)
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Dr Joleen Blok (Erasmus Medical Centre, Rotterdam)
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- Organisational unit
- Lead unit Science and Engineering Faculty
- Research area
- Mathematical Sciences
Details
Our work involves development of a Graphical User Interface (GUI) so that our software can be easily used by hospital staff throughout the world.
Our method is based on an electrophysiological stimulus applied to nerves and the muscular response recorded on the surface of the skin. From the resulting data forming a stimulus response curve we have developed a statistical method to estimate the number of motor units. This uses computational Bayesian statistics and the method known as Markov chain Monte Carlo (developed over 50 years by physicists and statisticians). Our work was presented by invitation at a special discussion meeting of the Royal Statistical Society in November, 2006. Our work involves development of a Graphical User Interface (GUI) so that our software can be easily used by hospital staff throughout the world. Researchers and users of the software also make use of a private collaborative website to share ideas. We are currently improving our statistical methods using recent ideas of Sequential Monte Carlo.
