title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð½ÐµÐ¸Ð½Ð²Ð°Ð·Ð¸Ð²Ð½Ð¾Ð³Ð¾ Ð¸Ð½ÑÐµÑÑÐµÐ¹ÑÐ° Â«Ð¼Ð¾Ð·Ð³-ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÂ» Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð²Ð¾Ð¾Ð±ÑÐ°Ð¶Ð°ÐµÐ¼ÑÑ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ð¹ Ð½Ð¸Ð¶Ð½Ð¸Ñ ÐºÐ¾Ð½ÐµÑÐ½Ð¾ÑÑÐµÐ¹ ÑÐµÐ»Ð¾Ð²ÐµÐºÐ°
title: Application of a non-invasive interface Â«brain-computerÂ» for classification of imaginary movements of the lower limbs
Creators: name: ÐÑÑÐ°Ð²ÑÐºÐ°Ñ, ÐÐ½Ð¶ÐµÐ»Ð¸ÐºÐ°
name: Ð¡ÑÐ°Ð½ÐºÐµÐ²Ð¸Ñ, ÐÐµÐ²
name: "Ð¡Ð¸ÑÑÐµÐ¼Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð² Ð¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ Ð¸ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ð¸", Ð¼ÐµÐ¶Ð´ÑÐ½Ð°ÑÐ¾Ð´Ð½Ð°Ñ Ð½Ð°ÑÑÐ½Ð°Ñ Ð¸ ÑÑÐµÐ±Ð½Ð¾-Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ°Ñ ÐºÐ¾Ð½ÑÐµÑÐµÐ½ÑÐ¸Ñ (25; 2021; Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³)
Publisher: name: ÐÐÐÐÐ¢ÐÐ¥-ÐÐ ÐÐ¡Ð¡
Year: 2021
Subjects: Ð¡Ð¸ÑÑÐµÐ¼Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð·
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description: This paper discusses the problem of classifying human lower-limb movements based on brain activity signals perceived and decoded using the brain-computer interface (BCI). The structure of a non-invasive BCI is presented, focused on the recognition of imaginary motor commands by electroencelographic (EEG) signals. An analytical review of scientific works related to the classification of arm and leg movements has been carried out, as a result of which the most effective type of classifier based on Riemannian geometry has been determined. A mathematical description of the method for classifying multichannel EEG signals using Riemannian geometry is given. Initial experiments have been carried out on the use of BCIs of this type for recognizing imaginary commands for movements of the feet. The accuracy of recognition of leg movements in real time is about 65%. It is proposed to develop these studies with the aim of increasing the accuracy and speed of recognition, which will make it possible to use this method in systems of neurorehabilitation and control of lower limb exoskeletons.