UPM researchers have designed an intelligent robotic system that can improve the recovery of patients with shoulder injuries, a disease that causes a high rate of sick leave.
A team from the Centre for Automation and Robotics (CAR, UPM-CSIC) has developed a robotic exoskeleton that performs more efficiently rehabilitation therapies of patients with shoulder injuries. By using strength and motion sensors, the system assesses the degree of an injury and its evolution as the treatment progresses.
Besides, the use of this system is simple and easily adaptable to any patient. These features represent not only a great advantage for patients, who recover faster, but also a big help for healthcare providers that treat these injuries every day.
Human shoulder is one of the most complex joints in the human body due to its wide variety of motions. The interrelationship among its parts makes rehabilitation complex after an injury if compared to other skeletal-muscle injuries.
Exoskeleton designed by CAR (UPM-CSIC). / UPM.
Rehabilitation therapies performed by intelligent robotic systems have been shown to reduce patients' recovery time. However, there are very few robotic systems for recovery of shoulder injuries. In this context, researchers from CAR have developed a robotic exoskeleton that, apart from lessening the recovery time of an injury, assesses and registers the progress of the entire rehabilitation process.
According to the main researcher, Cecilia García Cena, simulating the skeletal system is not enough to develop this exoskeleton, it is needed to incorporate both the kinematics and dynamics of a complete model that takes into account the skeletal system, muscles, tendons and ligaments. All these elements are included in the new intelligent robotic system.
The exoskeleton developed by researchers is inexpensive, easy to use and adaptable to any patient. This system can help to relieve saturated rehabilitation units, with the consequent saving in the healthcare system.
Learn more: Portfolio of technologies UPM A/W 2015/16.