Analyzing unstable gait patterns from Electroencephalography (EEG) signals is vital to develop real-time brain-computer interface (BCI) systems to prevent falls and associated injuries. This study investigates the feasibility of classification algorithms to detect walking instability utilizing EEG signals. A 64-channel Brain Vision EEG system was used to acquire EEG signals from 13 he... https://www.trendingcustomes.shop/product-category/7-5-x-4-5/
Classifying Unstable and Stable Walking Patterns Using Electroencephalography Signals and Machine Learning Algorithms
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