News > The Glenohumeral Joint Mobilization Robot (Shoulder) was designed
The Glenohumeral Joint Mobilization Robot (Shoulder) was designed
The Glenohumeral Joint Mobilization Robot (Shoulder) was designed and built by Dr. Mohammad Hassan Azarsan, a member of the Ergonomics Department at the University of Social Welfare and Rehabilitation Sciences (USWR), the physiotherapist and the specialist in medical robotics, for the first time in the world.
This robot, which has a patent certificate in Iran and in the United States, is one of the physiotherapy equipment that rehabilitates and treats intra-articular disorder of the shoulder (hypomobility) with joint mobilization techniques.
Dr. Azarsan, a member of the Department of the Ergonomics at the USWR, the physiotherapist and the specialist in medical robotics said: “This robot can execute joint mobilization techniques which the physiotherapist usually perform with his fingers on the shoulder joint for at least 20 minutes, and which will cause fatigue and lead to inaccuracy in the technique. The force sensor and the displacement sensor installed in this robot simulate the movement of the physiotherapist's fingers and is effective in treating the patient's shoulder joint disorder with different movements in different directions.
A physiotherapist with the use of this robot at the beginning, during and after the activity, can use the specialized data shown by the force sensor and the robotic displacement sensor to evaluate the patient's physical condition and be aware of how treatment progression/process is defined based on the principles of "Maitland" (standard treatment method in mobilization techniques).
Dr. Noureddine Karimi, an associate professor in the Department of physiotherapy at the USWR and an advisor professor in this research and technology project said: "Using this robot assists to refine physiotherapy techniques for rehabilitation and movement restoration without joint pain, and it makes the treatment process easier and faster.”
13:34 - 2021/01/12 / 18239 / 83