Analysis of Motor Functions of Hemiplegic Patients Based on Dual-Mode Signal Fusion

Accurate assessment of mobility is of great significance for disease diagnosis and rehabilitation guidance. In response to the needs of hemiplegic patients (HPs) for accurate quantitative assessment of mobility during disease diagnosis and rehabilitation, this article proposes a gait analysis method based on the fusion of bimodal gait signals from human electrostatic field and Kinect, which can objectively and quantitatively assess the gait abnormalities of HPs. Kinematic data and human electrostatic gait signals were recorded simultaneously during the walking process of the subjects, and ten quantitative indexes of motion ability and symmetry of hip, knee, and ankle joint, muscle force control ability, gait symmetry, gait balance, and gait stability were extracted. The gait index of HPs was quantitatively assessed by an improved principal component analysis method, which was used to quantitatively assess the lower limb motor function of HPs. The results showed that the hemiplegic gait index was effective in differentiating HPs with different Brunnstrom stages and showed a significant negative correlation with the Fugl-Meyer lower extremity motor function scale scores (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${P} \lt 0.05$ </tex-math></inline-formula>), with an absolute value of the correlation coefficient as high as 0.96. This article suggests that the hemiplegic gait index is a reliable mobility assessment tool to better support traditional clinical decision-making and improve the efficiency of rehabilitation therapy.