In this work, we propose a method of processing patient input on discomfort level during robot shoulder physiotherapy into discomfort maps. These maps represent the patient's discomfort distribution throughout the range of motion of the shoulder, interpretable by both physiotherapists and robots. This method consists of three parts: the patient can input discomfort with a linear push-button; a collaborative robot arm is used to track the motion of the patient's shoulder; and audiovisual feedback of inputted discomfort is given to the patient and the therapist.
The method was validated in human factors experiments simulating shoulder physiotherapy sessions, where the subject is tasked with recreating a reference discomfort map through an auditory reference signal that emulates this discomfort. Here the robot also acts as the physiotherapist, moving the subject's shoulder. The signal is a beeping sound, whose rate scales with the discomfort intensity at the measured pose in the reference discomfort map.
We performed experiments with a total of 10 participants, demonstrating the viability of our method during patient-robot interaction. The results we collected also highlighted the presence of a time delay between the discomfort signal and the user input, and its effect on discomfort maps.