Automatic Inference of Rat’s Hindlimb Trajectory to Synchronize with Forelimb Gait Through Phase

Abstract

Synchronous forelimb-hindlimb gait pattern is important to facilitate natural walking behavior of an injured rat with total transection. Since our ultimate research goal is to build a rehabilitation robotic system to simulate the natural walking pattern for spinalized rats, this research aims to address an immediate goal of automating the inference of the rat's hindlimb trajectory from its own forelimb movement. Our proposed method uses unsupervised learning to extract independent forelimb and hinblimb phases. From the phase information, a relationship between forelimb and hindlimb trajectory can then be calculated. Results show that the proposed method has the potential to be used in a rehabilitation robotic system.