从血容量脉搏信号识别短期焦虑

2014 IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD14) Pub Date : 2014-05-01 DOI:10.1109/SSD.2014.6808747

Wahida Handouzi, C. Maaoui, A. Pruski, Abdelhak Moussaoui

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引用次数: 13

摘要

在本文中，我们重点研究了虚拟现实暴露系统诱导焦虑和识别策略的开发。我们描述了短期内通过血容量脉搏测量来检测焦虑;详细的数据收集，特征提取和分类。我们使用支持向量机建立了一个焦虑检测模型，并对收集到的数据进行了评估。结果表明，相关特征的选择可以很好地识别焦虑。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Short-term anxiety recognition from blood volume pulse signal

In this paper we focus our attention on the development of a virtual reality exposure system to induce anxiety and a strategy for recognizing it. We describe anxiety detection in short term from blood volume pulse measurement; detailing data collection, features extraction and classification. We built a model of anxiety detection using support vector machines and evaluate it on the collected data. Results show that the choice of relevant features allowed good anxiety recognition.

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来源期刊

2014 IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD14)

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