A two-dimensional clinical gait analysis protocol based on markerless recordings from a single RGB-Depth camera - Balta, Diletta; Salvi, Massimo; Molinari, Filippo; Figari, Giulio; Paolini, Gabriele; Croce, Ugo Della; Cereatti, Andrea (2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2020)
This work presents a two-dimensional markerless clinical gait analysis protocol to estimate the sagittal lower limb joint kinematics from the markerless recordings of a single RGB-Depth camera. The proposed method includes a subject separation from the background, the definition of a multi-segmental model of the lower limb and the estimation of the relevant joint kinematics. The segmentation algorithm performance was assessed by measuring the similarity between the computer-obtained segmentations and manual tracings (ground-truth). The estimated joint angles were compared to those obtained using a reference optoelectronic marker-based clinical protocol. The offset between the mean waveforms and the RMS value of the waveforms difference after removing their offset were computed. The segmentation accuracy resulted to be higher than 0.92 and very repeatable (STD of JI about 0.01). The RMSD values of the ankle kinematics (3.4° on average) are lower than those of other joints (4.9° for the hip joint and 6.2° for the knee joint, on average). Overall, given the good agreement between our results and those of marker-based method, we propose to use it to develop a new generation of low-cost movement analysis systems.