UGO220

Lower extremity exoskeleton walking rehabilitation device UGO220 is a powered gait rehabilitation exoskeleton by RoboCT.

Description

RoboCT has released the UGO 220, the latest version of their lower-limbs rehabilitation exoskeleton. The product in specifically designed for usage in rehabilitation clinics, offering personalized robotic walking aid to the patients and comprehensive therapy data to the practitioners. The target demographic is individuals with hemiplegia, spinal cord injuries, muscle weakness, or other nervous system diseases.

UGO 220 has powered hip and knee flexion joints and passive ankles. With more than 50 sensors, the exoskeleton is able to detect user intention and adjust gait speed and stride length automatically. Machine learning algorithms are in charge of progressively adapting the system behavior to the user needs and rehabilitation progress. UGO 220 also employs computer vision to recognize obstacles or stairs ahead and adapt the foot trajectories accordingly.

RoboCT has included thoughtful touches to UGO 220 to provide a first-class clinical rehabilitation experience. Patients can log in to the system by swiping their personal card on the control panel, loading their profile onto the exoskeleton. UGO 220 automatically adjusts its legs’ length to match the user ones, loads information regarding walking parameters and rehabilitation progress, and shows relevant information to the physiotherapist through the dashboard. A mobile app is also available to manage all the data effortlessly.


Hangzhou RoboCT Technological Development Co., Ltd., 7 floor, building 2, 1326 West Wen Yi Road, Cang Qian Street, Yuhang District, Hangzhou, China, http://www.roboct.com/en/home

Exoskeleton Report does not endorse one exoskeleton product over another.  The exoskeleton catalog is purely for educational purposes.  The catalog is meant to provide an easily accessible birds-eye view of the exoskeleton industry, and a quick method to sort exoskeletons by type and purpose.  All prices are approximate and are meant to provide a general sense of the cost of the devices.


This entry has been made with the assistance of Stefano Carisi, MS in BioRobotics and Biomechanical Design from the Delft University of Technology an experienced product manager in human-machine collaboration.

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