Identification of Neurodegenerative Diseases Based on Vertical Ground Reaction Force Classification Using Time–Frequency Spectrogram and Deep Learning Neural Network Features

• Published in: Brain sciences Vol. 11; no. 7; p. 902
• Main Authors: Setiawan, Febryan, Lin, Che-Wei
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08.07.2021; MDPI
• Subjects: Algorithms; Amyotrophic lateral sclerosis; Classification; Deep learning; Discriminant analysis; Gait; gait analysis; Genetic transformation; Motor neurone disease; Nervous system; Neural networks; neuro-degenerative diseases; Neurodegenerative diseases; Parkinson's disease; Patients; Principal components analysis; Sensors; Support vector machines; Time series; time–frequency spectrogram; vertical ground reaction force signal; Wavelet transforms; neuro-degenerative diseases; deep learning; vertical ground reaction force signal; time–frequency spectrogram; gait analysis

A novel identification algorithm using a deep learning approach was developed in this study to classify neurodegenerative diseases (NDDs) based on the vertical ground reaction force (vGRF) signal. The irregularity of NDD vGRF signals caused by gait abnormalities can indicate different force pattern...