2026-04-19T19:58:32Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/85672024-02-03T01:05:44Zcom_10259_7328com_10259_3989com_10259.4_106com_10259_2604col_10259_7329
Repositorio Institucional de la Universidad de Burgos
author
Moncada, Fernando
author
Martín, Sofía
author
González, Víctor M.
author
Álvarez, Víctor M.
author
García López, Beatriz
author
Gómez Menéndez, Ana Isabel
author
Villar, José R.
2024-02-02T15:56:02Z
2024-02-02T15:56:02Z
2022
0941-0643
http://hdl.handle.net/10259/8567
10.1007/S00521-022-06940-Z
1433-3058
Photosensitivity, in relation to epilepsy, is a genetically determined condition in which patients have epileptic seizures of different severity provoked by visual stimuli. It can be diagnosed by detecting epileptiform discharges in their electroencephalogram (EEG), known as photoparoxysmal responses (PPR). The most accepted PPR detection method—a manual method—considered as the standard one, consists in submitting the subject to intermittent photic stimulation (IPS), i.e. a flashing light stimulation at increasing and decreasing flickering frequencies in a hospital room under controlled ambient conditions, while at the same time recording her/his brain response by means of EEG signals. This research focuses on introducing virtual reality (VR) in this context, adding, to the conventional infrastructure a more flexible one that can be programmed and that will allow developing a much wider and richer set of experiments in order to detect neurological illnesses, and to study subjects’ behaviours automatically. The loop includes the subject, the VR device, the EEG infrastructure and a computer to analyse and monitor the EEG signal and, in some cases, provide feedback to the VR. As will be shown, AI modelling will be needed in the automatic detection of PPR, but it would also be used in extending the functionality of this system with more advanced features. This system is currently in study with subjects at Burgos University Hospital, Spain.
eng
Atribución 4.0 Internacional
Electroencefalogram
Virtual reality
Photoparoxysmal response
Machine learning
Virtual reality and machine learning in the automatic photoparoxysmal response detection
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/8567/1/Moncada-nca_2023.pdf
File
MD5
4b6c0a1ff22bba09398917aaa52099b5
2013735
application/pdf
Moncada-nca_2023.pdf