LSTM-based Motion Trajectory Prediction in a Perceiving-Acting Cycle System

Theaim of this study is to model the cognitive processes based on a perceiving-acting cycle in patients with unilateral spatial neglect (USN). USN is the inability to perceive features of the environment, body, or objects on one side. To extract the cognitive characteristics of USN patients in a multifaceted manner, we constructed a multimodal sensing system using immersive VR. In this paper, we present a system that predicts movement of a subject while performing a search task using the measurement results and an LSTM neural network.