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In this paper, a double compact elastic module is designed and implemented in\udthe lower extremity exoskeleton. The double compact elastic module is\udcomposed of two parts, i.e., physical human robot interaction (pHRI)\udmeasurement and the elastic actuation system (EAS), which are called proximal\udelastic module (PEM) and distal elastic module (DEM) respectively. The PEM is\udused as the pHRI information collection device while the DEM is used as the\udcompliance device. A novel compact parallelogram-like structure based\udtorsional spring is designed and developed. An iterative finite element\udanalysis (FEA) based optimization process was conducted to find the optimal\udparameters in the search space. In the PEM, the designed torsional spring has\udan outer circle with a diameter of 60 mm and an inner hole with a diameter\udof 12 mm, while in the DEM, the torsional spring has the outer circle with a\uddiameter of 80 mm and the inner circle with a diameter of 16 mm. The\udtorsional spring in the PEM has a thickness of 5 mm and a weight of 60 g,\udwhile that in the DEM has a thickness of 10 mm and a weight of 80 g. The\uddouble compact elastic module prototype is embedded in the mechanical joint\uddirectly. Calibration experiments were conducted on those two elastic modules\udto obtain the linear torque versus angle characteristic. The calibration\udexperimental results show that this torsional spring in the PEM has a\udstiffness of 60.2 Nm rad<sup>−1</sup>, which is capable of withstanding a maximum\udtorque of 4 Nm, while that in the DEM has a stiffness of\ud80.2 Nm rad<sup>−1</sup>, which is capable of withstanding a maximum torque of\ud30 Nm. The experimental results and the simulation data show that the\udmaximum resultant errors are 6 % for the PEM and 4 % for the DEM\udrespectively. In this paper, an assumed regression algorithm is used to learn\udthe human motion intent (HMI) based on the pHRI collection. The HMI is\uddefined as the angular position of the human limb joint. A closed-loop\udposition control strategy is utilized to drive the robotic exoskeleton system\udto follow the human limb's movement. To verify the developed system,\udexperiments are performed on healthy human subjects and experimental results\udshow that this novel robotic exoskeleton can help human users walk, which can\udbe extended and applied in the assistive wearable exoskeletons

Development of a lower extremity wearable exoskeleton with double compact elastic module: preliminary experiments