基于脑电图的LSTM-RNN机器学习算法情感识别

Reddy Koya Jeevan, SP Venu Madhava Rao, P. Shiva Kumar, Malyala Srivikas
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引用次数: 21

摘要

近年来,脑机接口的知识正在表现为情感识别和分类。有许多研究表明使用脑电图脑电波识别情绪的潜在证据。本文研究并提出了一种新的机器学习技术,通过使用LSTN(长短期记忆)循环神经网络,使用最新的机器学习概念来识别情绪。将采集到的脑电波信号用离散小波变换进行分类处理后,再输入到该算法中进行特定情绪识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EEG-based emotion recognition using LSTM-RNN machine learning algorithm
In recent days the knowledge in the Brain Machine Interface is manifesting emotion recognition and classification. There are many studies indicating potential evidence in identifying emotions using EEG brain waves. This paper investigates and proposes a new machine learning technology in identifying the emotions through the use of latest machine learning concepts using LSTN ( Long short term memory) recurring neural networks. The acquired brain wave signals are processed for classification using discrete wavelet transform and then given to the proposed algorithm for specific emotion recognition.
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