Electroencephalography (EEG) is an important neurophysiological modality for
understanding brain functions and disorders. Topological signal processing allows us to …

Electroencephalography (EEG) is an important neurophysiological modality for
understanding brain functions and disorders. Topological data analysis (TDA) can decode …

Electroencephalography (EEG) is an important neuroimaging tool for understanding network
disorders caused by neuroanatomical malformation or damage such as epilepsy and post …

Automated seizure detection is a fundamental problem in computational neuroscience
towards diagnosis and treatment's improvement of epileptic disease. We propose a real-time …

Electroencephalography (EEG) is a widely used cerebral activity measuring device for both
clinical and everyday life applications. In addition to denoising and potential classification, a …

Topological data analysis (TDA) has proven to be a potent approach for extracting intricate
topological structures from complex and high-dimensional data. In this paper, we propose a …

Electroencephalography (EEG) is among the most widely diffused, inexpensive, and
adopted neuroimaging techniques. Nonetheless, EEG requires measurements against a …

Topological Data Analysis is a fast-growing and promising approach that recently gains
popularity in the data science field. It utilizes topological and geometric measurements to …

Epilepsy is a neurological disorder that can negatively affect the visual, audial and motor
functions of the human brain. Statistical analysis of neurophysiological recordings, such as …

This work introduces geometric and topological data analysis (TDA) tools that can be used
in conjunction with sliding window transformations, also known as delay-embeddings, for …