A Spiking Neural Network for Personalised Modelling of Electrogastrography (EGG)
EGG records the resultant body surface potential of gastric slow waves (electrical activity); while slow waves regulate contractions of gastric muscles, it is the electrical activity we are recording, not movement (like ECG records the cardiac electrical
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Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, Auckland, New Zealand {vbreen,nkasabov}@aut.ac.nz 2 Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand {peng.du,scal044}@auckland.ac.nz
Abstract. EGG records the resultant body surface potential of gastric slow waves (electrical activity); while slow waves regulate contractions of gastric muscles, it is the electrical activity we are recording, not movement (like ECG records the cardiac electrical activity, but not the contractions of the heart, even the two are essentially related). Keywords: Spiking neural network Electrogastrography Functional dyspepsia
Personalised modelling Slow wave dysrhythmia
1 Introduction Spiking neural networks have been used successfully to model spatiotemporal data, especially neurological data. The present study utilizes the spiking neural network setup within NeuCube [1] developed at the Knowledge Engineering and Development Research Institute (KEDRI), at Auckland University of Technology. NeuCube has been used to model not just brain data but a number of other types of temporal based data, for example stroke prediction [2], ecological data [3], and seismic data which is currently under investigation by KEDRI researchers. The power within this system lies in the customization available in many aspects of its execution, from the neuron locations, the spike encoding method, the combination of supervised and unsupervised learning, to the visualization of interactions within the network and predictive results. The full capabilities of this type of infrastructure within NeuCube are yet to be realized, with continual development and improvement from the researchers within KEDRI.
2 Background Digestion is facilitated by the motility of the stomach, which in turn is governed by an electrophysiological event called slow waves. Dysrhythmias of slow waves have been associated with a number of digestive diseases, including gastroparesis, unexplained nausea and vomiting, and functional dyspepsia [4]. Electrogastrography (EGG) is a non-invasive method of recording the resultant body surface potential of gastric slow © Springer International Publishing AG 2016 F. Schwenker et al. (Eds.): ANNPR 2016, LNAI 9896, pp. 18–25, 2016. DOI: 10.1007/978-3-319-46182-3_2
A Spiking Neural Network for Personalised Modelling
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wave propagation. EGG has the ability to convey information about gastric slow wave activity in terms of frequency, amplitude and propagation, therefore it holds potential as a routinely deployable tool to aid the diagnosis of gastric functions. The present study investigates the spatiotemporal data recorded by EGG as it relates specifically to functional dyspepsia. Functional dyspepsia is the condition where the gut does not function as it should but this is not caused by biological or bacterial factors. An efficient way of measuring what is occurring in the gut in a non-invasive manner is to utilize EGG, where a patient wears mesh of sensors on around th
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