Please ASTRO, can you follow me? Design of a social assistive robot for monitoring gait parameters

This paper proposes an alternative strategy for the analysis of the gait activity using a socially assistive robot. This solution aims to be less invasive while guaranteeing an accurate evaluation of the rehabilitation performance. In this work, we implemented a follow-me module to enable ASTRO robot to detect, track, and follow the patient during walking, adapting to his/her walking speed. The robot detects the person through a 2D laser sensor and an RGB-D camera. To follow the user at a predetermined distance, the implemented follow-me module integrates two controllers for handling the linear and angular velocities, respectively. The controllers' gains were set according to the maximum speed attainable by the robot. The extracted gait parameters were compared with the parameters extracted by an inertial sensor placed on the feet (SensFoot) and analyzed to characterize the best robot configuration for the task of the gait assessment. Eleven participants were recruited to perform the tests with 3 different values of the robot's maximum speed. For each test, 4 parameters were extracted from the laser and 10 parameters from the wearable sensors. The best configuration was found to be the one with the highest maximum speed, 0.7 m/s, whose gains from the two linear and angular controllers are Kp= 1.0, Kd = 0.4, and Kp = 1.0, respectively. Qualitative results collected at the end of the test also confirm the 0.7 m/s as the optimal perceived maximum velocity.