Dynamic optimization of mental workload in fNIRS-BCI system for cognitive rehabilitation

2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) Pub Date : 2017-09-01 DOI:10.1109/ICSIPA.2017.8120629

W. Ung, T. Tang, F. Mériaudeau, Esther Gunaseli M. Ebenezer

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引用次数: 1

Abstract

Cognitive rehabilitation has been proposed as an alternative treatment for Alzheimer's disease (AD) as it helps to preserve brain functionality. However, gains of cognitive training or rehabilitation may be eliminated due to cognitive overload and mental fatigue. This paper reports the development of a functional near-infrared spectroscopy (fNIRS) — brain-computer interface (BCI) that can adjust task difficulty adaptively. The aim is to have participants trained at their optimal level of difficulty and workload to maximize their gains. One patient with mild AD and one healthy control were recruited to test the functionality of proposed fNIRS-BCI system. The fNIRS-BCI system is able to process fNIRS signals in real time and adjust task difficulty accordingly. The healthy control was able to proceed to higher task levels, as compared to the mild AD patient. The fNIRS-BCI system has the potential as a tool to examine the efficacy of cognitive rehabilitation as an alternative treatment for AD.

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认知康复fNIRS-BCI系统中心理负荷的动态优化

认知康复已被提出作为阿尔茨海默病(AD)的替代治疗方法，因为它有助于保持大脑功能。然而，认知训练或康复的收益可能因认知超载和精神疲劳而被消除。本文报道了一种可自适应调节任务难度的功能性近红外光谱(fNIRS) -脑机接口(BCI)。目的是让参与者在他们的最佳难度和工作量水平上进行训练，以最大限度地提高他们的收益。招募了一名轻度AD患者和一名健康对照者来测试所提出的fNIRS-BCI系统的功能。fNIRS- bci系统能够实时处理fNIRS信号，并对任务难度进行相应调整。与轻度AD患者相比，健康对照组能够进入更高的任务水平。fNIRS-BCI系统有潜力作为一种工具来检查认知康复作为AD替代治疗的疗效。

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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2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

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