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Soft wearable robots are a promising new design paradigm for rehabilitationand active assistance applications. Their compliant nature makes them ideal forcomplex joints like the shoulder, but intuitive control of these robots requirerobust and compliant sensing mechanisms. In this work, we introduce the sensingframework for a multi-DoF shoulder exosuit capable of sensing the kinematics ofthe shoulder joint. The proposed tendon-based sensing system is inspired by theconcept of muscle synergies, the body's sense of proprioception, and finds itsbasis in the organization of the muscles responsible for shoulder movements. Amotion-capture-based evaluation of the developed sensing system showedconformance to the behaviour exhibited by the muscles that inspired its routingand validates the hypothesis of the tendon-routing to be extended to theactuation framework of the exosuit in the future. The mapping from multi-sensorspace to joint space is a multivariate multiple regression problem and wasderived using an Artificial Neural Network (ANN). The sensing framework wastested with a motion-tracking system and achieved performance with root meansquare error (RMSE) of approximately 5.43 degrees and 3.65 degrees for theazimuth and elevation joint angles, respectively, measured over 29000 frames(4+ minutes) of motion-capture data.

Design and Prototyping of a Bio-inspired Kinematic Sensing Suit for the Shoulder Joint: Precursor to a Multi-DoF Shoulder Exosuit