Multimodal Gait Abnormality Recognition Using a Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN-BiLSTM) Network Based on Multi-Sensor Data Fusion

Multimodal Gait Abnormality Recognition Using a Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN-BiLSTM) Network Based on Multi-Sensor Data Fusion

Global aging leads to a surge in neurological diseases. Quantitative gait analysis for the early detection of neurological diseases can effectively reduce the impact of the diseases. Recently, extensive research has focused on gait-abnormality-recognition algorithms using a single type of portable s...

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Bibliographic Details
Main Authors: Jing Li, Weisheng Liang, Xiyan Yin, Jun Li, Weizheng Guan
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Sensors
Subjects:
neurodegenerative diseases
gait abnormality recognition
multi-sensor
time–frequency plots
CNN-BiLSTM network
Online Access:https://www.mdpi.com/1424-8220/23/22/9101

Internet

https://www.mdpi.com/1424-8220/23/22/9101

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