Topological Inference on Electroencephalography

Yuan Wang ()
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Yuan Wang: University of South Carolina

Chapter Chapter 24 in Research Papers in Statistical Inference for Time Series and Related Models, 2023, pp 539-553 from Springer

Abstract: Abstract Statistical inference of electroencephalography (EEG) from diverse clinical groups often requires considerable technicality and computational power. Motivated by topological data analysis, we now take a new analytical angle on EEG signals by characterizing their shape with persistent homology (PH). This paper reviews our recent studies where novel statistical inference procedures are developed for PH features of EEG signals to address clinical questions in brain disorders.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-99-0803-5_24

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DOI: 10.1007/978-981-99-0803-5_24

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