The ability to predict the onset of labour is seen to be an important
tool in a clinical setting. Magnetomyography has shown promise in the
area of labour imminency prediction, but its clinical application
remains limited due to high resource consumption associated with its
broad number of channels. In this study, five electrode channels, which
account for 3.3% of the total, are used alongside a novel signal
decomposition algorithm and low complexity classifiers (logistic
regression and linear-SVM) to classify between labour imminency due
within 0–48hrs and >48hrs. The results suggest that the
parsimonious representation comprising of five electrode channels and
novel signal decomposition method alongside the candidate classifiers
could allow for greater affordability and hence clinical viability of
the magnetomyography-based prediction model, which carries a good degree
of model interpretability.
Low-complexity frequency-domain GSC for broadband beamforming
