Spectral analysis of pathological gait characteristics of patients suffering from Parkinson disease and Strokes
1Department of Mathematics, University of Sri Jayewardenepura, Nugegoda, Sri Lanka.
2District General Hospital, Gampaha, Sri Lanka.
3Institute of Neurology, National Hospital of Sri Lanka.
Research Article
World Journal of Advanced Research and Reviews, 2020, 06(03), 189-196
Article DOI: 10.30574/wjarr.2020.6.3.0177
Publication history:
Received on 28 May 2020; revised on 21 June 2020; accepted on 23 June 2020
Abstract:
Strokes and Parkinson's disease (PD) are the current leading cause of severe, and long-term disability prevailing in Sri Lanka. Detection of gait characteristics has become an interesting field of biomechanics that provides useful information in the management of the above two diseases. The objective of the study presented in this paper is to establish a technique for the gait detection of Stroke and PD patients using Discrete Fourier Transforms (DFT). Twenty four patients with PD and Stroke and five healthy controls were made to perform a series of movements which were measured using Kinect (a motion detection sensor produced by Microsoft). All the participants were recruited from the National Hospital Sri Lanka (NHSL). The Kinect device provided x, y, z coordinates of the ankle, knee, and hip joints. Ankle, knee, and hip joint angle characteristics have been analyzed in the frequency domain, and abnormal gait of Stroke and PD patients has been identified using harmonic coefficients. Experimental results and analysis indicate that both Stroke and PD patients have significant amplitude values for the first few harmonics relative to healthy controls. This result conforms with the shorter stride length property of Stroke and PD patients. For therapeutic interventions to improve gait performances, consideration should be given to both the severity of the disease and the lower limb involvement of the disease. Results conclude that the proposed method can accurately visualize the abnormality in the gait of Stroke and PD patients with sufficient accuracy.
Keywords:
Parkinson's Disease; Stroke; Discrete Fourier transform; Gait analysis; Severity; Lower limb involvement.
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