Disentangling action content and style from motion capture sequences of standardised rehabilitation tasks - Tan, Shauna Li-Ting (Nanyang Technological University, 2022)
Physical therapy and rehabilitation will always be a pivotal part in every society as our ability to move is greatly treasured. However, there is no objective way of assessing one’s physical ability. Instead, it is measured subjectively through clinical observation, objective diagnostic procedures and standardised tests. As part of the Towards Data-Driven Ability Gap Modelling project under the aegis of the Rehabilitation Research Institute of Singapore (RRIS), this project aims to explore the use of deep neural networks to predict human motion on a specific physical task.