A Study on Gait Analysis for Cerebral Palsy Using Auto-Encoder

Abstract

This study aims to establish a method for analyzing patients’ gait without special equipment (such as a motion capture system). Routine and quantitative gait analysis is crucial for diseases with gait disorders (e.g., Cerebral Palsy). Unfortunately, gait analysis requires expensive motion capture systems and highly trained personnel. This paper addressed the challenge of estimating the deviation of patients’ gait from standard case, employing the two-dimensional positions of joints estimated by off-the-shelf human pose estimation with Auto-Encoder (AE). The authors calculated the correlation coefficient between the reconstruction error and GDI to evaluate the method and obtained the result that the correlation coefficient r is -0.395. The experimental results suggest the proposed method could capture the patients’ gait deviation from normality.