The aim of
this research is to derive and evaluate an automated identification method that
can be applied generically to detect and evaluate the state of body functions
using coupled Electromyographic, (EMG) signals the in
real time space domain.
research works from the premise that functions of the body are non-linearly
coupled, complex and dynamic. Using this approach, system parameters can be
derived to detect and predict changes and limiting factors. This work is
focusing on the onset of fatigue during lengthy microsurgical procedures. It is
difficult for the individual to assess their relative change in performance over
time and this can be crucial as many procedures conclude following a final,
precise and critical task.
is developing new methodology and algorithms that can be used to analyse and measure the hand tremor and fatigue of surgeons
while performing surgery. Complexity method, Principle Component analysis,
Empirical Mode Decomposition algorithm and non-linear Auto Regressive with
exogenous inputs (NARX) neural networks have been used during development of the