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Classification of human emotion from EEG using discrete wavelet transform

Journal of Biomedical Science and Engineering 2010年第4期3卷 390-396页

作者： Murugappan Murugappan Nagarajan Ramachandran yaacob sazali 不详

In this paper, we summarize the human emotion recognition using different set of electroencephalogram (EEG) channels using discrete wavelet transform. An audio-visual induction based protocol has been designed with more dynamic emotional content for inducing discrete emotions (disgust, happy, surprise, fear and neutral). EEG signals are collected using 64 electrodes from 20 subjects and are placed over the entire scalp using International 10-10 system. The raw EEG signals are preprocessed using Surface Laplacian (SL) filtering method and decomposed into three different frequency bands (alpha, beta and gamma) using Discrete Wavelet Transform (DWT). We have used “db4” wavelet function for deriving a set of conventional and modified energy based features from the EEG signals for classifying emotions. Two simple pattern classification methods, K Nearest Neighbor (KNN) and Linear Discriminant Analysis (LDA) methods are used and their performances are compared for emotional states classification. The experimental results indicate that, one of the proposed features (ALREE) gives the maximum average classification rate of 83.26% using KNN and 75.21% using LDA compared to those of conventional features. Finally, we present the average classification rate and subsets of emotions classification rate of these two different classifiers for justifying the performance of our emotion recognition system.

关键词： EEG Human Emotions Discrete Wavelet Transform KNN LDA

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Quantifying of Paraplegic Patient Facial Agitation Based on Fuzzy k-NN

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Computer Technology and Application 2011年第1期2卷 24-28页

作者： Muhammad Naufal Bin Mansor Azrini Binti Idris sazali yaacob Ramachandran Nagaraj an Hariharan Muthusamy Department of Mechatronic Engineering University Malaysia Perlis Perlis 01000 Malaysia Department of Electrical Engineering Politeknik Tuanku Syed Sirajuddin Perlis 02600 Malaysia

A non-specific symptom of one or more physical, or psychological processes in which screaming, shouting, complaining, moaning, cursing, pacing, fidgeting or wandering pose risk or discomfort, become disruptive or unsafe or interfere with the delivery of care are called agitation. Individuals in agitation manifest their condition through "pain behavior", which includes facial expressions. Clinicians regard the patient’s facial expression as a valid indicator for pain and pain intensity. Hence, correct interpretation of the facial agitation of the patient and its correlation with pain is a fundamental step in designing an automated pain assessment system. Computer vision techniques can be used to quantify agitation in sedated patients in Intensive Care Unit (ICU). In particular, such techniques can be used to develop objective agitation measurements from patient motion. In the case of paraplegic patients, whole body movement is not available, and hence, monitoring the whole body motion is not a viable solution. Hence in this case, the author measured head motion and facial grimacing for quantifying facial patient agitation in critical care based on Fuzzy k-NN.

关键词：面部表情截瘫患者搅拌量化模糊计算机视觉技术 k近邻头部运动

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