EEG diagnosis

  • 文章类型: Journal Article
    轻度认知障碍(MCI)是阿尔茨海默病(AD)的初始阶段。认知能力下降与大脑不同区域之间的异常连接有关。大多数脑网络研究未能考虑大脑模式的变化,也不能反映患者的动态病理特征。因此,本文提出了一种基于微态序列构建脑网络的方法。它还分析了微观状态的时间参数,并引入了一个新的功能,脑稳态系数(Bhc),量化患者大脑连接的稳定性。结果表明,MCI组的微状态B类参数高于HC组。此外,MCI和AD组大多数通道的Bhc值低于HC组,在右额叶观察到最显著的差异。差异均有统计学意义(P<0.05)。研究结果表明,在认知障碍患者中,右额叶的连通性可能受到最严重的破坏。此外,蒙特利尔认知评估评分显示与Bhc有很强的正相关。这表明Bhc可能是评估认知障碍患者认知功能的新型生物标志物。
    Mild cognitive impairment (MCI) is the initial phase of Alzheimer\'s disease (AD). The cognitive decline is linked to abnormal connectivity between different regions of the brain. Most brain network studies fail to consider the changes in brain patterns and do not reflect the dynamic pathological characteristics of patients. Therefore, this paper proposes a method for constructing brain networks based on microstate sequences. It also analyzes the microstate temporal parameters and introduces a new feature, the brain homeostasis coefficient (Bhc), to quantify the stability of patient brain connections. The results showed that microstate class B parameters were higher in the MCI than in the HC group. Additionally, the Bhc values in most channels of the MCI and AD groups were lower than those of the HC group, with the most significant differences observed in the right frontal lobe. These differences were statistically significant (P < 0.05). The findings indicate that connectivity in the right frontal lobe may be most severely disrupted in patients with cognitive impairment. Furthermore, the Montreal Cognitive Assessment score showed a strong positive correlation with Bhc. This suggests that Bhc could be a novel biomarker for evaluating cognitive function in patients with cognitive impairment.
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  • 文章类型: Journal Article
    很早,广泛的,准确,并且具有成本效益的神经认知障碍的临床诊断将对老年人及其家庭具有优势,但也为医疗保健系统的可持续性和性能。BRAINCODE是一种评估老年人认知障碍的技术,区分正常和病理性大脑状况,基于脑电图生物标志物评估。本文将讨论BRAINCODE的试点设计,旨在验证其功效,为未来的研究提供指导,并允许其在SHAPES平台上的整合。预计BRAINCODE会定期进行临床诊断和神经心理测试,以区分“正常”和病理性认知衰退,并区分有/没有主观认知抱怨的老年人的轻度认知损害和痴呆。
    An early, extensive, accurate, and cost-effective clinical diagnosis of neurocognitive disorders will have advantages for older people and their families, but also for the health and care systems sustainability and performance. BRAINCODE is a technology that assesses cognitive impairment in older people, differentiating normal from pathologic brain condition, based in an EEG biomarkers evaluation. This paper will address BRAINCODE\'s pilot design, which intends to validate its efficacy, to provide guidelines for future studies and to allow its integration on the SHAPES platform. It is expected that BRAINCODE confirms a regular clinical diagnosis and neuropsychologic tests to discriminate \'normal\' from pathologic cognitive decline and differentiates mild cognitive impairment from dementia in older adults with/without subjective cognitive complains.
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