Introduction: This work presents the development of a novel robotic knee exoskeleton controlled by motion intention based on sEMG, which uses admittance control to assist people with reduced mobility and improve their locomotion. Clinical research remark that these devices working in constant interaction with the neuromuscular and skeletal human system improves functional compensation and rehabilitation. Hence, the users become an active part of the training/rehabilitation, facilitating their involvement and improving their neural plasticity. For recognition of the lower-limb motion intention and discrimination of knee movements, sEMG from both lower-limb and trunk are used, which implies a new approach to control robotic assistive devices. Methods: A control system that includes a stage for human-motion intention recognition (HMIR), based on techniques to classify motion classes related to knee joint were developed. For translation of the user’s intention to a desired state for the robotic knee exoskeleton, the system also includes a finite state machine and admittance, velocity and trajectory controllers with a function that allows stopping the movement according to the users intention. Results: The proposed HMIR showed an accuracy between 76% to 83% for lower-limb muscles, and 71% to 77% for trunk muscles to classify motor classes of lower-limb movements. Experimental results of the controller showed that the admittance controller proposed here offers knee support in 50% of the gait cycle and assists correctly the motion classes. Conclusion: The robotic knee exoskeleton introduced here is an alternative method to empower knee movements using sEMG signals from lower-limb and trunk muscles. ; Fil: Villa Parra, Ana Cecilia. Universidade Federal do Espírito Santo; Brasil. Universidad Politécnica Salesiana; Ecuador ; Fil: Delisle Rodriguez, Denis. Universidade Federal do Espírito Santo; Brasil. Universidad de Oriente; Cuba ; Fil: Botelho, Thomaz. Universidade Federal do Espírito Santo; Brasil ; Fil: Mayor, John Jairo Villarejo. Universidade Federal do Paraná; Brasil ; Fil: Delis, Alberto López. Universidad de Oriente; Cuba ; Fil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentina ; Fil: Neto, Anselmo Frizera. Universidade Federal do Espírito Santo; Brasil ; Fil: Bastos, Teodiano Freire. Universidade Federal do Espírito Santo; Brasil


    Access

    Download


    Export, share and cite



    Title :

    Control of a robotic knee exoskeleton for assistance and rehabilitation based on motion intention from sEMG



    Remarks:

    CONICET


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




    A Multimodal Knee Exoskeleton for Fracture Rehabilitation

    Kong, Xiangrui / Li, Min / Yang, Zhanshuo et al. | IEEE | 2024


    User intention driven adaptive gait assistance using a wearable exoskeleton

    Rajasekaran, Vijaykumar / Aranda López, Juan / Casals Gelpi, Alicia | BASE | 2016

    Free access



    An EMG-controlled robotic hand exoskeleton for bilateral rehabilitation

    Leonardis, Daniele / Barsotti, Michele / Loconsole, Claudio et al. | BASE | 2015

    Free access