DOI: https://doi.org/10.31071/kit2019.15.01

Опис-посилання

ISSN 1812-7231 Klin.inform.telemed. Volume 14, Issue 15, 2019, Pages 13-34

Автор(и)

І. В. Редька

Установа(ви)

Харківська медична академія післядипломної освіти МОЗ України

Харківський національний університет імені В. Н. Каразіна МОН України

Назва статті

Сучасні підходи до виявлення і видалення артефактів з ЕЕГ-сигналів. Огляд

Анотація (резюме)

Вступ. Виявлення артефактів з подальшим їх видаленням з даних ЕЕГ є важливою проблемою в нейрофізіології, оскільки характеристики артефактних фрагментів прекриваются з характеристиками істинної активності головного мозку.

Мета — огляд існуючих математичних підходів до розпізнавання і видалення артефактів з ЕЕГ-сигналів.

Результати. Існують методи, засновані на статистичному відхиленні артефактів, адаптивної фільтрації, регресії, сліпому розділення джерел, емпіричної модової декомпозиції, вейвлет-перетворення та їх комбінації, кожен з яких має свої переваги і недоліки. Тим не менш, не існує універсального алгоритму для всіх типів артефактів. Першочерговими критеріями у виборі алгоритму видалення артефактів є наявність опорного каналу, спосіб (автоматизований або експертний) і режим (потоковий або пакетний) виявлення/видалення артефактів. Досить складно порівнювати різні методи відхилення артефактів через використання різних метрик, заснованих на здатності видаляти артефакти та ступені спотворення вихідного сигналу.

Висновок. Аналіз незалежних компонентів є найбільш часто використовуваним в нейрофізіологічних дослідженнях. Пріоритетним напрямком є розробка гібридних методів видалення фізіологічних артефактів. Доцільною є триетапна перевірка ефективності нового алгоритму виявлення/видалення артефактів.

Ключові слова

ЕЕГ, артефакт, регресія, адаптивна фільтрація, сліпе розділення джерел, емпірична модова декомпозиція, вейвлет-перетворення

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