Classification of gait patterns between patients with Parkinson’s disease and healthy controls using phase space reconstruction (PSR), empirical mode decomposition (EMD) and neural networks

• Published in: Neural networks Vol. 111; pp. 64 - 76
• Main Authors: Zeng, Wei, Yuan, Chengzhi, Wang, Qinghui, Liu, Fenglin, Wang, Ying
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.03.2019
• Subjects: Aged; Empirical mode decomposition (EMD); Empirical Research; Euclidean distance (ED); Female; Gait - physiology; Gait dynamics; Healthy Volunteers; Humans; Male; Middle Aged; Neural networks; Neural Networks (Computer); Parkinson Disease - classification; Parkinson Disease - diagnosis; Parkinson Disease - physiopathology; Parkinson’s diseases; Phase space reconstruction (PSR); Quality of Life; Gait dynamics; Parkinson’s diseases; Euclidean distance (ED); Empirical mode decomposition (EMD); Phase space reconstruction (PSR); Neural networks

Parkinson’s disease (PD) is a common neurodegenerative disorder that affects human’s quality of life, especially leading to locomotor deficits such as postural instability and gait disturbances. Gait signal is one of the best features to characterize and detect movement disorders caused by a malfunc...