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Most existing methods of motion assessment system used the contact sensor, infrared sensor, and depth sensor, and few works provided the solution of digital camera. To solve this problem, the authors propose a new motion assessment system based on light camera. In this work, the motion assessment was regarded as pattern regression problem of skeleton joint trajectory. Firstly, the system uses the camera to capture the image sequences. The pose estimation method is used to obtain body skeleton from image. Secondly, due to the difference of motion frequency of each person, the length of the image sequences is different and the length of each joint trajectory also will be different. Fourier transform is applied to normalise the trajectory and use the coefficients of Fourier transform as the joint trajectory feature. Finally, the regression model is built to assess the motion quality. Some experimental results and discussion on action video data are used to verify the effectiveness of the system.

Most existing methods of motion assessment system used the contact sensor, infrared sensor, and depth sensor, and few works provided the solution of digital camera. To solve this problem, the authors propose a new motion assessment system based on light camera. In this work, the motion assessment was regarded as pattern regression problem of skeleton joint trajectory. Firstly, the system uses the camera to capture the image sequences. The pose estimation method is used to obtain body skeleton from image. Secondly, due to the difference of motion frequency of each person, the length of the image sequences is different and the length of each joint trajectory also will be different. Fourier transform is applied to normalise the trajectory and use the coefficients of Fourier transform as the joint trajectory feature. Finally, the regression model is built to assess the motion quality. Some experimental results and discussion on action video data are used to verify the effectiveness of the system. [ABSTRACT FROM AUTHOR]

Formation of wear particles within total hip replacement is one of the main causes of its failure. In addition to improving the lubrication and wear resistance of materials used as bearing surfaces, understanding of wear particle distribution patterns within lubricants inside an implant gap could be used to improve design parameters and implants’ lifespan. In this study, the behaviours of biolubricants (with compositions similar to human joint synovial fluid) and suspended particles were investigated by micro-particle image velocimetry in curved mini channels under oscillatory Couette flow conditions. The studied biolubricants had shear-thinning viscoelastic characteristics. The authors found that increasing shear-thinning, elasticity or motion frequency levels did not affect the trend behaviours of biolubricant flows due to the low strain values of the experimental conditions applied. However, suspended particles formed strings along flow directions and exhibited cross-stream migration to channel walls. Motion frequency, fluid shear thinning and elasticity characteristics and channel dimensions strongly affected particle behaviours.