GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force

GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force

Blog Article

Walking (gait) irregularities and abnormalities are predictors and symptoms of disorder and disability.In the past, elaborate video (camera-based) systems, pressure mats, or a mix of the two has been used in clinical settings to monitor and evaluate gait.This article presents an artificial intelligence-based comprehensive investigation of ground reaction force (GRF) pattern to classify the healthy control and gait disorders AFTER SUN SOOTHER using the large-scale ground reaction force.

The used dataset comprised GRF measurements from different patients.The article includes machine learning- and deep learning-based models to classify healthy and gait disorder patients using ground reaction force.A deep learning-based architecture GaitRec-Net is proposed for this classification.

The classification results were evaluated using various metrics, and each experiment was analysed using a fivefold cross-validation approach.Compared to machine learning classifiers, the proposed deep learning model is found better for feature extraction resulting in high Back accuracy of classification.As a result, the proposed framework presents a promising step in the direction of automatic categorization of abnormal gait pattern.