Distinguishing between Parkinson’s disease patients and healthy individuals using a comprehensive set of time, frequency and time-frequency features extracted from vertical ground reaction force data
- 1 September 2020
- journal article
- research article
- Published by Elsevier in Biomedical Signal Processing and Control
- Vol. 62
Abstract
No abstract availableKeywords
Funding Information
- Hamadan University of Medical Sciences (990202532)
This publication has 43 references indexed in Scilit:
- Chi-square distance kernel of the gaits for the diagnosis of Parkinson's diseaseBiomedical Signal Processing and Control, 2013
- Parkinson’s disease classification using gait characteristics and wavelet-based feature extractionExpert Systems with Applications, 2012
- Motor Control Abnormalities in Parkinson's DiseaseCold Spring Harbor Perspectives in Medicine, 2012
- Gait Analysis Using Wearable SensorsSensors, 2012
- A vision-based analysis system for gait recognition in patients with Parkinson’s diseaseExpert Systems with Applications, 2009
- Progression of dysprosody in Parkinson's disease over time—A longitudinal studyMovement Disorders, 2008
- Wavelet filtering before spike detection preserves waveform shape and enhances single-unit discriminationJournal of Neuroscience Methods, 2008
- Rhythmic auditory stimulation modulates gait variability in Parkinson's diseaseEuropean Journal of Neuroscience, 2007
- Dual tasking, gait rhythmicity, and Parkinson's disease: Which aspects of gait are attention demanding?European Journal of Neuroscience, 2005
- Treadmill walking as an external pacemaker to improve gait rhythm and stability in Parkinson's diseaseMovement Disorders, 2005