TY - GEN
T1 - 'Should I Lead?' Feasibility Study of User Perception on Following-Robot for Gait Assessment
AU - Sorrentino, Alessandra
AU - Ferreira, Bruno
AU - Menezes, Paulo
AU - Batista, Jorge
AU - Dias, Jorge
AU - Fiorini, Laura
AU - Benvenuti, Pietro
AU - Cavallo, Filippo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Current techniques of gait assessment rely on wearable sensors, pressure-sensitive walkway systems, and optical motion capture systems. A less invasive and more portable solution could be represented by a mobile robot that follows the user during the gait activity. The main idea behind this work relies on finding the best robot configuration for less invasive gait analysis with high acceptability from the end users. To this aim, two follow-me configurations have been designed: human-leader (i.e. the robot follows the person from behind), and robot-leader (i.e. robot follows the person from the front). We asked 27 young participants to test both modalities and to evaluate their perception of the robot in 5 domains: comfort, expected conformity, safety, trust, and unobtrusiveness. Additionally, we extracted quantitative parameters related to the walking experience from the data recorded by the platform and we analyzed them in tandem with the qualitative results. The results reported that robot-leader configuration tended to be more appreciated in terms of comfort, trust, and safety. On the contrary, the human-leader configuration is perceived as less obtrusive, less invasive, and in line with users' expectations. Considering the gait assessment application, we expect the human-leader configuration to return more promising and accurate results.
AB - Current techniques of gait assessment rely on wearable sensors, pressure-sensitive walkway systems, and optical motion capture systems. A less invasive and more portable solution could be represented by a mobile robot that follows the user during the gait activity. The main idea behind this work relies on finding the best robot configuration for less invasive gait analysis with high acceptability from the end users. To this aim, two follow-me configurations have been designed: human-leader (i.e. the robot follows the person from behind), and robot-leader (i.e. robot follows the person from the front). We asked 27 young participants to test both modalities and to evaluate their perception of the robot in 5 domains: comfort, expected conformity, safety, trust, and unobtrusiveness. Additionally, we extracted quantitative parameters related to the walking experience from the data recorded by the platform and we analyzed them in tandem with the qualitative results. The results reported that robot-leader configuration tended to be more appreciated in terms of comfort, trust, and safety. On the contrary, the human-leader configuration is perceived as less obtrusive, less invasive, and in line with users' expectations. Considering the gait assessment application, we expect the human-leader configuration to return more promising and accurate results.
UR - http://www.scopus.com/inward/record.url?scp=85185827666&partnerID=8YFLogxK
U2 - 10.1109/ICAR58858.2023.10406654
DO - 10.1109/ICAR58858.2023.10406654
M3 - Conference contribution
AN - SCOPUS:85185827666
T3 - 2023 21st International Conference on Advanced Robotics, ICAR 2023
SP - 564
EP - 569
BT - 2023 21st International Conference on Advanced Robotics, ICAR 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International Conference on Advanced Robotics, ICAR 2023
Y2 - 5 December 2023 through 8 December 2023
ER -