成人阅读障碍与非阅读障碍真实单词阅读与无意义单词阅读的脑电图信号分析

Harshani Perera, M. F. Shiratuddin, K. Wong, Kelly Fullarton
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引用次数: 6

摘要

随着技术的发展以及技术现在在诊断和识别疾病和困难方面发挥的主要作用,提高诊断系统的准确性至关重要。改进和评估识别和分类结果模式的方式可能有助于发现并不总是显而易见的答案。本文试图利用分类器在被诊断患有阅读障碍的成年人的脑电波信号中发现这种模式。将成人阅读障碍患者在真实单词和无意义单词阅读活动中捕获的脑电图(EEG)信号与正常对照进行比较。采用线性支持向量机(LSVM)和三次支持向量机(CSVM)对不同脑叶进行分类。研究表明,与真实单词分类器相比,无意义单词分类器产生了更高的验证准确性,这证实了阅读障碍患者在语音解码技能上的困难反映在脑电波模式上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EEG Signal Analysis of Real-Word Reading and Nonsense-Word Reading between Adults with Dyslexia and without Dyslexia
With the evolution of technology and the major role that technology now plays in the diagnosis and identification of disorders and difficulties, improving the accuracy of diagnostic systems is paramount. Improving and evaluating the way in which patterns of results are identified and classified may help uncover answers that are not always obvious. This paper attempts to discover such patterns found in brainwave signals in adults who have been diagnosed with dyslexia using classifiers. Electroencephalogram (EEG) signals captured during real-word and nonsense-word reading activities from adults with dyslexia were compared with normal controls. The classification was performed using Linear Support Vector Machine (LSVM) and Cubic Support Vector Machine (CSVM) on different lobes of the brain. The study revealed that the nonsense-words classifiers produced higher validation accuracies compared to real-words classifiers, confirming difficulties in phonological decoding skills seen in individuals with dyslexia are reflected in the brainwave patterns.
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