title: ÐÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐµÐ¹ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐ¸Ð¼Ð°Ð½Ð¾Ð²Ð¾Ð¹ Ð³ÐµÐ¾Ð¼ÐµÑÑÐ¸Ð¸
title: Classification of time sequences based on riemann geometry
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Ð½Ð¾-Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ°Ñ ÐºÐ¾Ð½ÑÐµÑÐµÐ½ÑÐ¸Ñ (26; 2022; 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: 2023
Subjects: ÐÐµÐ¾Ð¼ÐµÑÑÐ¸Ñ Ð Ð¸Ð¼Ð°Ð½Ð°
Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÐµ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸
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Ð±ÐµÑÐºÐ¾Ð½ÑÐ°ÐºÑÐ½Ð¾Ðµ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ðµ ÑÐ¾Ð±Ð¾ÑÐ¾Ð¼
time sequences
classification
brain-computer interface
recognition of imaginary movements
non-contact robot control

description: Ð Ð°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¼Ð½Ð¾Ð³Ð¾Ð¼ÐµÑÐ½ÑÑ Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐµÐ¹. ÐÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ñ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ð¹ Ð¿Ð¾ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð¸ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ° Ð²ÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐµÐ¹, Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð½Ð¾Ð³Ð¾ Ð½Ð° ÑÐ¸Ð¼Ð°Ð½Ð¾Ð²Ð¾Ð¹ Ð³ÐµÐ¾Ð¼ÐµÑÑÐ¸Ð¸. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½ÑÐ¹ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾Ñ Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½ Ð½Ð° Ð·Ð°Ð´Ð°ÑÐµ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð²Ð¾Ð¾Ð±ÑÐ°Ð¶Ð°ÐµÐ¼ÑÑ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ð¹ ÑÑÐº Ð¸ Ð½Ð¾Ð³ Ð² Ð¸Ð½ÑÐµÑÑÐµÐ¹ÑÐ°Ñ Â«Ð¼Ð¾Ð·Ð³-ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÂ». ÐÐ¾ÐºÐ°Ð·Ð°Ð½Ð¾, ÑÑÐ¾ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÑ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐ¸Ð¼Ð°Ð½Ð¾Ð²Ð¾Ð¹ Ð³ÐµÐ¾Ð¼ÐµÑÑÐ¸Ð¸ Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑ ÑÑÐ¿ÐµÑÐ½Ð¾ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°ÑÑ Ð¼Ð½Ð¾Ð³Ð¾Ð¼ÐµÑÐ½ÑÐµ Ð¿Ð°ÑÑÐµÑÐ½Ñ ÑÐ»ÐµÐºÑÑÐ¾ÑÐ½ÑÐµÑÐ°Ð»Ð¾Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¸Ñ ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð², ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²ÑÑÑÐ¸Ðµ Ð²Ð¾Ð¾Ð±ÑÐ°Ð¶Ð°ÐµÐ¼ÑÐ¼ ÐºÐ¾Ð¼Ð°Ð½Ð´Ð°Ð¼ Ð¿Ð¾Ð´Ð½ÑÑÐ¸Ñ Ð¿ÑÐ°Ð²Ð¾Ð¹ Ð¸ Ð»ÐµÐ²Ð¾Ð¹ ÑÑÐº, ÑÐ¶Ð°ÑÐ¸Ñ Ð¸Ñ ÐºÐ¸ÑÑÐµÐ¹, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¿Ð¾Ð´Ð½ÑÑÐ¸Ñ Ð¿ÑÐ°Ð²Ð¾Ð¹ Ð¸ Ð»ÐµÐ²Ð¾Ð¹ Ð½Ð¾Ð³Ð¸ Ð¸ Ð½Ð°Ð¶Ð°ÑÐ¸Ñ Ð¸Ñ ÑÑÑÐ¿Ð½ÐµÐ¹. ÐÑÐ¸ ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²ÑÑÑÐµÐ¹ Ð½Ð°ÑÑÑÐ¾Ð¹ÐºÐµ ÑÐ°ÐºÐ¸Ðµ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÑ Ð¼Ð¾Ð³ÑÑ Ð¾Ð±ÐµÑÐ¿ÐµÑÐ¸ÑÑ Ð±Ð¾Ð»ÐµÐµ Ð²ÑÑÐ¾ÐºÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð² Ð½ÐµÐºÐ¾ÑÐ¾ÑÑÑ ÑÐ»ÑÑÐ°ÑÑ, ÑÐµÐ¼ ÑÑÐ°Ð´Ð¸ÑÐ¸Ð¾Ð½Ð½ÑÐµ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÑ Ð½Ð° Ð¼ÐµÑÐ¾Ð´Ðµ Ð¾Ð¿Ð¾ÑÐ½ÑÑ Ð²ÐµÐºÑÐ¾ÑÐ¾Ð² Ð¸Ð»Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÑÑ, Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ Ð¿ÑÐ¸ Ð²Ð°ÑÐ¸Ð°Ð±ÐµÐ»ÑÐ½ÑÑ Ð¸ÑÑÐ¾Ð´Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ. ÐÑÐ¸Ð²ÐµÐ´ÐµÐ½Ñ Ð¿ÑÐµÐ´Ð²Ð°ÑÐ¸ÑÐµÐ»ÑÐ½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ, Ð¿Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÑÑÐ¸Ðµ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÑ Ð±ÐµÑÐºÐ¾Ð½ÑÐ°ÐºÑÐ½Ð¾Ð³Ð¾ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ ÑÐ¾Ð±Ð¾ÑÐ¾Ð¼ Ð¿Ð¾ ÑÑÐ¸Ð¼ ÑÐ¸Ð³Ð½Ð°Ð»Ð°Ð¼. Ð¡ÑÐµÐ´Ð½ÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¼Ð¾ÑÐ¾ÑÐ½ÑÑ Ð²Ð¾Ð¾Ð±ÑÐ°Ð¶Ð°ÐµÐ¼ÑÑ ÐºÐ¾Ð¼Ð°Ð½Ð´ ÑÐ¾ÑÑÐ°Ð²Ð¸Ð»Ð° 71 %.
description: The work is devoted to the recognition of multidimensional time sequences. The results of research are development and testing a classifier based on Riemannian geometry for time series. The developed classifier was tested on the task of recognizing imaginary movements of arms and legs in brain-computer interfaces. It is shown that classifiers based on Riemannian geometry can successfully recognize multidimensional patterns of electroencephalographic signals corresponding to imaginary commands of raising the right and left hands, squeezing their hands, as well as raising the right and left legs and pressing their feet. With appropriate tuning, such classifiers can provide higher accuracy, in some cases, than traditional support vector machine or neural network classifiers, especially with variable input data. Preliminary results are presented showing the possibility of non-contact control of the robot by these signals. The average accuracy of recognition of imaginary motor commands was 71 %.