Walters Katherine F, Shukla Rohit, Kumar Vivek, Schueren Shannon, Yadav Hariom, Schilaty Nathan D, Jain Shalini
NeuBaC Laboratory, Department of Neurosurgery and Brain Repair, Center for Neuromusculoskeletal Research, University of South Florida, Tampa, FL 33620, USA.
USF Center for Microbiome Research, Microbiomes Institute, Department of Neurosurgery and Brain Repair, University of South Florida Morsani College of Medicine, Tampa, FL 33620, USA.
Brain Sci. 2025 Feb 10;15(2):173. doi: 10.3390/brainsci15020173.
: This study evaluates the potential of electroencephalography (EEG) as a noninvasive tool for distinguishing between healthy individuals ( = 79), those with mild cognitive impairment (MCI; = 36), and dementia patients ( = 7). : Using a 14-channel Emotiv EPOC-X headset, we analyzed power spectral density during a 2-min eyes-closed resting state. : Our results demonstrated that while EEG effectively differentiated dementia patients from healthy controls, it did not show significant differences between MCI and healthy controls. This indicates that EEG holds promise for identifying advanced cognitive decline but faces challenges in early-stage detection. : The study contributes to the growing body of literature by highlighting EEG's potential as a cost-effective alternative to invasive diagnostic methods while also identifying the need for larger sample sizes and task-oriented approaches to improve its diagnostic precision.
本研究评估了脑电图(EEG)作为一种非侵入性工具区分健康个体(n = 79)、轻度认知障碍(MCI;n = 36)患者和痴呆症患者(n = 7)的潜力。使用14通道的Emotiv EPOC-X头戴设备,我们分析了闭眼静息状态下2分钟的功率谱密度。我们的结果表明,虽然EEG能有效区分痴呆症患者与健康对照,但在MCI患者和健康对照之间未显示出显著差异。这表明EEG在识别晚期认知衰退方面具有潜力,但在早期检测中面临挑战。该研究通过强调EEG作为侵入性诊断方法的经济有效替代方案的潜力,同时也指出需要更大样本量和面向任务的方法来提高其诊断精度,为不断增长的文献做出了贡献。