首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Real time emotion aware applications: A case study employing emotion evocative pictures and neuro-physiological sensing enhanced by Graphic Processor Units
【24h】

Real time emotion aware applications: A case study employing emotion evocative pictures and neuro-physiological sensing enhanced by Graphic Processor Units

机译:实时情绪感知应用程序:通过图形处理器单元增强情绪情感图片和神经生理感应的案例研究

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper the feasibility of adopting Graphic Processor Units towards real-time emotion aware computing is investigated for boosting the time consuming computations employed in such applications. The proposed methodology was employed in analysis of encephalographic and electrodermal data gathered when participants passively viewed emotional evocative stimuli. The GPU effectiveness when processing electroencephalographic and electrodermal recordings is demonstrated by comparing the execution time of chaos/complexity analysis through nonlinear dynamics (multi-channel correlation dimension/D2) and signal processing algorithms (computation of skin conductance level/SCL) into various popular programming environments. Apart from the beneficial role of parallel programming, the adoption of special design techniques regarding memory management may further enhance the time minimization which approximates a factor of 30 in comparison with ANSI C language (single-core sequential execution). Therefore, the use of GPU parallel capabilities offers a reliable and robust solution for real-time sensing the user's affective state.
机译:在本文中,研究了采用图形处理器单元进行实时情绪感知计算的可行性,以提高此类应用程序中的耗时计算。当参与者被动地观察情绪唤起刺激时,所提议的方法被用于分析收集的脑电图和皮肤电图数据。通过比较非线性动力学(多通道相关维数/ D2)和信号处理算法(皮肤电导水平/ SCL的计算)对混沌/复杂度分析的执行时间,证明了处理脑电图和皮肤电记录时的GPU有效性。环境。除了并行编程的有益作用外,采用有关内存管理的特殊设计技术还可以进一步提高时间最小化,与ANSI C语言(单核顺序执行)相比,时间最小化约为30倍。因此,GPU并行功能的使用为实时感测用户的情感状态提供了可靠而强大的解决方案。

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号