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Assessment of Therapeutic Progress After Acquired Brain Injury Employing Electroencephalography and Autoencoder Neural Networks

机译:采用脑电图和自动化器神经网络获得脑损伤后的治疗进展评估

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A method developed for parametrization of EEG signals gathered from participants with acquired brain injuries is shown. Signals were recorded during therapeutic session consisting of a series of computer assisted exercises. Data acquisition was performed in a neurorehabilitation center located in Poland. The presented method may be used for comparing the performance of subjects with acquired brain injuries (ABI) who are involved in concentration training program. It may also allow for an assessment of relative difference in performance of two participants involved to exercises by comparing parameters derived from EEG signals acquired in the course of therapeutic sessions. The parametrization method is based on autoencoder neural networks. The efficiency of parameters extracted employing the algorithm was compared to parameters derived from the spectrum of EEG signal. As it was confirmed by achieved results, the presented autoencoder-based method may be applied to predict ABI subjects' performance in attention training sessions.
机译:显示了为从参与者聚集的脑电图的参数化开发的方法,如有脑损伤。在治疗会议期间记录信号,包括一系列计算机辅助练习。数据采集​​是在位于波兰的神经罗马特中心进行。所提出的方法可用于比较来自参与集中培训计划的受试者对受试者的性能。它还可以通过比较来自治疗性会话过程中获得的EEG信号的参数来评估参与术语的两个参与者的性能的性能。参数化方法基于AutoEncoder神经网络。将采用该算法提取的参数的效率与来自EEG信号频谱导出的参数进行了比较。正如通过达到的结果证实,所呈现的基于自动化的方法可以应用于预测ABI受试者在注意力培训课程中的表现。

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