遗传和实用的群体优化算法为患者特定的癫痫检测系统

S. Ammar, Omar Trigui, Senouci Mohamed
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引用次数: 4

摘要

自动癫痫检测系统旨在通过识别寻找的脑电图片段来帮助医生的决策过程。提高系统的灵敏度是许多研究的目标。事实上,改进这一标准可以找到与视觉扫描相同的解释。患者特异性系统能够根据患者设置最佳参数,这使得它比非患者特异性系统更准确。本文介绍了一种具有遗传和实用群优化算法的新型病人特异性系统。结果表明,该系统能够达到可接受的性能。此外,使用遗传算法提高系统灵敏度(95%)超过实际群优化(91%),使其成为更好的系统参数优化方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic and practical swarm optimisation algorithms for patient-specific seizure detection systems
The automatic seizure detection system is designed to aid the physician's decision-making process with recognizing the sought EEG segments. Increasing the system sensitivity is the goal of several studies. In fact, ameliorating this criterion allows to find the same interpretations as found with a visual scanning. A patient-specific system is able to set its optimal parameters according to the patient which makes it more accurate than non-patient-specific system. This paper introduces a new patient-specific system with genetic and practical swarm optimisation algorithms. The results show that the proposed system is able to reach acceptable performances. Moreover, the use of the genetic algorithm improves the system sensitivity (95%) more than the practical swarm optimization (91%) which makes it a better method for the system parameter optimisation.
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