A Long short-term Memory Model based on a Robotic Wheelchair as a Rehabilitation Assistant

Abstract

Lately several studies have shown that Autonomous Intelligent Robotic Wheelchairs (AIRW) have offered valuable assistance to people with mobility issues. The assistance offered by these AIRW to these people is categorized according to the needs of each person. One category of such assistance is the rehabilitation exercises. Nosokoma is an AIRW that can offer a set of simple rehabilitation assistances for elderly and people in need. In particular, it can assist a user to perform simple rehab exercises, like “get up”, “turn around”, and “sit down”. Thus, in this paper, we show a rehab method based on the exercises mentioned above and the way that AIRW could collect the data from these exercises. More specifically, pressure sensors are attached on AIRW robotic arms to properly measure the force applied by the human user on the robotic arms, thus AIRW can provide additional lifting assistance to human user for the successful and safe completion of the sequence of get-up and sit-down tasks.