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Robot-Assisted Posture Emulation for Visually Impaired Children

Fang‐Lin Chao, Hung‐Chi Chu, Liza Lee

Year
2019
Citations
1
Access
Open access

Abstract

This study proposes robot-assisted posture emulation for visually impaired children. The motor of a small robot (low torque) can be controlled using our palms. A user does not risk injury when the robotic hand is directly touched. The dimensions of the body of a commercially available small robot are different from those of a person. We adjusted the length of the upper arm to easily distinguish the movements of the upper and lower limbs. Adults and children were requested to perceive the robot's movements through touch and imitate its action. The study demonstrated that visually impaired subjects enjoyed playing with the robot and the frequency of body movements increased in robot-assisted guidance. The majority of the children could identify the main posture and imitate it. The scoring of continuous movement is medium. A stand-alone concept design was proposed. The design can present the main actions of the upper body and prevent body dumping when touched. Main torso and hand movements can reveal the body language of most users.

Keywords

EmulationVisually impairedPhysical medicine and rehabilitationPsychologyComputer scienceHuman–computer interactionRobotComputer visionArtificial intelligenceMedicine

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