Robotic Knee Exoskeleton Prototype to Assist Patients in Gait Rehabilitation

This paper presents the design and development of a low cost robotic knee exoskeleton with mobile interface for active assistance of gait rehabilitation of patients who suffer lower limb impairment. Interaction based on electromyography (EMG) is used for detecting motion intention to recognize muscu...

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Bibliographic Details
Published in:Revista IEEE América Latina 2020-09, Vol.18 (9), p.1503-1510
Main Authors: Mora-Tola, Esteban, Loja-Duchi, Juan, Ordonez-Torres, Andres, Vazquez-Rodas, Andres, Astudillo-Salinas, Fabian, Minchala, Luis I.
Format: Article
Language:English
Subjects:
Activity recognition
Actuators
Algorithms
Artificial Neural Network
Artificial neural networks
Discrete wavelet transforms
Electromyography
Electronic devices
emg signal processing
Exoskeletons
Gait
gait rehabilitation
Knee
knee exoskeleton
Medical personnel
motion intention detection
Motion perception
Prototypes
rectus femoris
Rehabilitation
remote supervision
Robot sensing systems
Robotics
Telecommunications
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Summary:This paper presents the design and development of a low cost robotic knee exoskeleton with mobile interface for active assistance of gait rehabilitation of patients who suffer lower limb impairment. Interaction based on electromyography (EMG) is used for detecting motion intention to recognize muscular activity patterns by applying artificial neural network (ANN) algorithms. A comparison of muscular activity between the rectus femoris of each lower limb is made in order to find which offers better results. Once the system identifies a motion intention, it generates a predefined trajectory that mimics the gait cycle pattern of the knee joint. The actuator of the exoskeleton is required to accomplish this movement based on a position control strategy. The exoskeleton’s operation is supervised remotely through a mobile device, which is connected to a database that contains three rehabilitation routines previously set by medical staff. The robotic knee prototype is validated by monitoring its performance while being used, initially by healthy subjects.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2020.9381791