TruST (Trunk Support Trainer) is a cable-driven robot where a thoracic belt is pulled by wires by actuators mounted on a fixed frame. The wires are controlled to apply a force field on the upper body in response to the body’s motion. The wires provide assist-as-needed forces for rehabilitation, training, and strengthening of the upper body.
Recently, we introduce deep learning into TruST's real-time controller design. We collected 4320 trials of 3D trunk movement data (about 1.5 million data frames) during the postural star sitting test from 45 healthy subjects in two conditions (with or without foot support). It is the largest 3D trunk movement dataset in the literature and might be helpful in other seated postural control research.
The dataset will be available to the research community upon request consistent with the IRB guidelines, please contact with Xupeng Ai ([email protected]).