担任《Mechanical System and Signal Processing》《中国电机工程学报》等期刊审稿专家,擅长领域:信号滤波/降噪,机器学习/深度学习,时间序列预分析/预测,设备故障诊断/缺陷检测/异常检测。 一维神经网络的特征可视化分析-以心电信号为例(Python,Jupyter Notebook) 包括Occlusion sensitivity方法,Saliency map方法,Grad-CAM方法...
Signal processing measures of instantaneous energy typically include only amplitude information. But measures that include both amplitude and frequency do better at assessing the energy required by the system to generate the signal, making them more sensitive measures to include in electroencephalogram (EE...
Signal processing measures of instantaneous energy typically include only amplitude information. But measures that include both amplitude and frequency do better at assessing the energy required by the system to generate the signal, making them more sensitive measures to include in electroencephalogram (EE...
该软件背后有一个不断发展的社区,并且已经开发了多个python软件包来添加图形用户界面,自动不良通道检测和插值,独立成分分析(ICA),连通性分析,MEG / EEG信号的通用统计分析或预处理管道(PREP)的python实现,适用于EEG数据。 参考 Akhtar, M. T., Mitsuhashi, W., & James, C. J. (2012). Employing spatially ...
Rose小哥今天介绍动态脑电图及其工作原理和注意事项。 关于脑电图EEG,Rose小哥分享过很多,可以查看《什么是EEG以及如何解释EEG?》《EEG数据、伪影的查看与清洗》等。 介绍动态脑电图前,先简要介绍一下脑电图。更加详细的介绍可以查看《什么是EEG以及如何解释EEG?》 ...
Python (deep learning and machine learning) for EEG signal processing on the example of recognizing the disease of alcoholism arXiv:2010.11667 [eess.SP] 来自 arXiv.org 喜欢 0 阅读量: 125 作者: I Rakhmatulin 摘要: Alcoholism is one of the most common diseases in the world. This type of...
在之前的文章《系统梳理EEG中常用的功能连接指标—系列1》中,笔者对皮尔森相关系数(Pearson correlation coefficient)、波谱相干(Spectral coherence)、互信息(Mutual information,MI)、相锁值(Phase Locking Value, PLV)4个功能连接指标的计算方法、优缺点进行了介绍。本文为系列2,继续对相关的功能连接指标进行梳理。
Sörnmo, L., & Laguna, P. (2005). Bioelectrical Signal Processing in Cardiac and Neurological Applications (Vol. 1). Elsevier. Sweeney, K. T., Member, S., Ward, E., Member, S., Mcloone, F., & Member, S. (2012). Artifact Removal in Physiological Signals — Practices and Possibi...
The python programming language and some of its associated scientific and numeric libraries are then used to preprocess the data. The popular TensorFlow and Keras machine learning libraries are used to train a convolutional neural network to classify the EEG data into four different commands: forward...
EEG signal processing and classification EEG data were recorded at 500 Hz. The reference electrode was chosen on the vertex and the ground electrode was located on the forehead. Data were processed with special designed Jupyter notebooks in Python using both gumpy35 and MNE22,36 toolboxes. For ...