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>Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis
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Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis
BackgroundThe computer-aided identification of specific gait patterns is an important issue in the assessment of Parkinson's disease (PD). In this study, a computer vision-based gait analysis approach is developed to assist the clinical assessments of PD with kernel-based principal component analysis (KPCA).
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