Fig. 1

Overview of the ECO-Lite architecture. Input data were RGB color images, 224 × 224 px in size. Sixteen frames were used from each video. The frames were processed using a two-dimensional convolutional network (2D Net) to yield 96 feature maps, 28 × 28 px in size, for each frame. These feature maps were stacked temporally and fed into a three-dimensional convolutional network (3D Net), which was used to analyze the relationships between different frames. Thus, the size of the stacked feature maps used as input was 96 × 16 × 28 × 28. The final output was a predicted score of the Unified Parkinson’s Disease Rating Scale (UPDRS) part III for each video