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Communication Dans Un Congrès Année : 2020

Controlling an upper-limb exoskeleton by EMG signal while carrying unknown load

Résumé

Implementing an intuitive control law for an upper-limb exoskeleton dedicated to force augmentation is a challenging issue in the field of human-robot collaboration. The aim of this study is to design an innovative approach to assist carrying an unknown load. The method is based on user's intentions estimated through a wireless EMG armband allowing movement direction and intensity estimation along 1 Degree of Freedom. This control law aimed to behave like a gravity compensation except that the mass of the load does not need to be known. The proposed approach was tested by 10 participants on a lifting task with a single Degree of Freedom upper-limb exoskeleton. Participants performed it in three different conditions : without assistance, with an exact gravity compensation and with the proposed method based on EMG armband (Myo Armband). The evaluation of the efficiency of the assistance was based on EMG signals captured on seven muscles (objective indicator) and a questionnaire (subjective indicator). Results showed a statically significant reduction of mean activity of the biceps, erector spinae and deltoid by 20% ± 14, 18% ± 12 and 25% ± 16 respectively while comparing the proposed method with no assistance. In addition, similar muscle activities were found both in the proposed method and the traditional gravity compensation. Subjective evaluation showed better precision, efficiency and responsiveness of the proposed method compared to the traditional one.
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Dates et versions

hal-02945595 , version 1 (22-09-2020)

Identifiants

Citer

Benjamin Treussart, Franck Geffard, Nicolas Vignais, Frédéric Marin. Controlling an upper-limb exoskeleton by EMG signal while carrying unknown load. 2020 IEEE International Conference on Robotics and Automation (ICRA), May 2020, Paris, France. pp.9107-9113, ⟨10.1109/ICRA40945.2020.9197087⟩. ⟨hal-02945595⟩
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