Use of electroencephalogram, gait, and their combined signals for classifying cognitive impairment and normal cognition

• DOI: 10.3389/fnagi.2022.927295
• Publication Date: 2022-09-07T09:36:35Z
• Authors: Jin-Young Min; Sang-Won Ha; Kiwon Lee; Kyoung-Bok Min
• Keywords: 03 medical and health sciences; 0302 clinical medicine; diagnosis; multimodal signals; Neurosciences. Biological psychiatry. Neuropsychiatry; EEG; kinematic gait analysis; cognitive impairment; RC321-571; Neuroscience; 3. Good health

Background Early identification of people at risk for cognitive decline is an important step in delaying the occurrence impairment. This study investigated whether multimodal signals assessed using electroencephalogram (EEG) and gait kinematic parameters could be used to identify individuals Methods The survey was conducted Veterans Medical Research Institute Health Service Center. A total 220 volunteered this provided informed consent enrollment. cap-type wireless EEG device recording, with a linked-ear references based on standard international 10/20 system. Three-dimensional motion capture equipment collect parameters. Mild impairment (MCI) evaluated by Seoul Neuropsychological Screening Battery-Core (SNSB-C). Results mean age participants 73.5 years, 54.7% were male. We found that specific significantly associated status. Individuals decreases high-frequency activity high beta (25–30 Hz) gamma (30–40 bands increased odds ratio MCI. There association between pelvic obliquity angle status, MCI or SNSB-C scores. from ROC analysis revealed combining improved ability discriminate normal controls. Conclusion These findings support prior work status gait, offer new insights into applicability distinguish