Powered assistive devices have been playing a major role in gait rehabilitation. This work aims to develop a user-oriented assistive strategy with an EMG-based control using a powered knee orthosis (PKO) to provide assistive commands according to the user's motion intention tracked by electromyography (EMG) signals. To achieve this goal, the work first comprised the development of a wired EMG acquisition system, the study and implementation of a knee joint torque estimation method, and the development of a real-time controller, which uses the estimated torque as the reference actuator's torque to provide user-oriented assistance in walking. We used a proportional gain method to estimate the knee torque, which required a calibration procedure, allowing to determine the relation between the EMG signal and the actuator's torque. The EMG-based control was validated with two subjects walking in a treadmill. The EMG-based control performed as expected since it proved to be functional and time-effective when assisting the user's movements in walking at different walking speeds. Findings show that the developed assistive strategy can effectively follow the user's motion intention and has the potential for gait rehabilitation of patients with residual muscular strength. ; This work has been supported in part by the Fundacao para a Ciencia e Tecnologia (FCT) with the Reference Scholarship under Grant SFRH/BD/108309/2015, the reference project UID/EEA/04436/2019, by FEDER funds through the COMPETE 2020 - Programa Operacional Competitividade e Internacionalizacao (POCI) - with the reference Project POCI-01-0145-FEDER-006941; and the LIACC Project UID/CEC/00027/2019; and with national funds from FCT project SmartOs-under Grant NORTE-01-0145-FEDER-030386.


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    Title :

    EMG-based motion intention recognition for controlling a powered knee orthosis


    Contributors:

    Publication date :

    2019-01-01



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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