Researchers from Beihang University, Beijing China, and Aalborg University, Denmark, have collaborated to develop a lower-limb exoskeleton that features natural knee movement to improve patient comfort. The wearable robot can be used with patients who have experienced strokes and spinal cord injuries and require gait rehabilitation to regain the ability to walk or to help strengthen their muscles as well as to assist those who need help performing daily activities. The article presenting the researchers’ work was published October 25 in the journal Review of Scientific Instruments.
The team’s approach focused on the knee joint. The knee joint’s motion is actuated by several skeletal muscles along its articular surfaces, and its center of rotation moves. The exoskeleton taps a hybrid serial-parallel kinematic structure consisting of a 1 degree of freedom (DOF) hip joint module and a 2 DOF knee joint module in the sagittal plane. A planar 2 DOF parallel mechanism helps to fully accommodate the motion of the human knee, enabling rotation and relative sliding. This design is the first known use of a parallel mechanism at the knee joint to imitate skeletal muscles.
“Our new design features a parallel knee joint to improve the bio-imitability and adaptability of the exoskeleton,” explained Weihai Chen, a professor at Beihang University’s School of Automation Science and Electrical Engineering. “We studied the structure of the human body, then built our model based on a biometric design of the lower-limb exoskeleton. Unlike most previous exoskeletons, which simplified the knee joint as a pin joint, ours provides 2 DOF to make the exoskeleton’s movement consistent with a patient’s natural movement,” he added.
The team now plans to streamline the exoskeleton to be wearable and comfortable, as well as to develop a virtual reality game to help make the training process more enjoyable. They are also exploring controlling the exoskeleton via EMG signals produced by the patients’ muscles so that the muscles are more active during the training. “We can obtain the movement intention from a patient’s electroencephalogram (EEG)-brain signals-and use it to directly control the exoskeleton,” Chen explained. “These improvements should enable easy control and make the exoskeleton act as part of the human body.”
The next step for the team is to collaborate with hospitals for patient testing.
“We’d also like to commercialize it in the near future, so we’ll be working to make the robot’s appearance fancier and enhancing the user interface to be more user friendly,” Chen noted.
Editor’s note: This story is adapted from materials provided by the American Institute of Physics.