Classifying Unstable and Stable Walking Patterns Using Electroencephalography Signals and Machine Learning Algorithms

Classifying Unstable and Stable Walking Patterns Using Electroencephalography Signals and Machine Learning Algorithms

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 s...

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Bibliographic Details
Main Authors: Rahul Soangra, Jo Armour Smith, Sivakumar Rajagopal, Sai Viswanth Reddy Yedavalli, Erandumveetil Ramadas Anirudh
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Sensors
Subjects:
unstable gait
fall risk
EEG
machine learning
ChronoNet
recurrent neural networks
Online Access:https://www.mdpi.com/1424-8220/23/13/6005

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