## 5 Conclusions  
Simulation for a LEAD in microgravity was performed using MATLAB and OpenSim. The net joint torques by the muscles calculated from the results of Type 1 and Type 2 (Figures 11 and 12) showed similar results to the net joint torques of a 1 g normal gait. From this, it can be concluded that tracking of the state variables corresponding to the 1 g walking level can be achieved by using the actuation method and control input proposed in the study. It was broadly presumed that the control input for the Type 1 and Type 2 actuators would have a similar tendency with the GRF data in 1 g for the former and the difference in ID results between 0 g and 1 g for the latter. As a result of simulation, we confirmed that control inputs similar to our expectation was obtained. As mentioned in the Introduction section, previous studies have performed data tracking to predict muscle forces in given motion, or predictive simulation to predict motion and corresponding muscle forces to minimize or maximize a given motor task. However, unlike those previous studies, the problem we dealt with in this study was to simultaneously track the joint angles and muscle forces that occur in certain movements (1 g of normal walking). Therefore, we constructed the objective function to include the angle, angular velocity, and muscle activity terms. This made it possible to track kinematics data and muscle forces and get corresponding control inputs. To the best of our knowledge, no previous studies have been conducted on simulations of systems such as Type 1 and Type 2 for resistance training in space. The results of this study provide a control input that can be used as a reference for the design of resistance training devices in microgravity environments. In this study, we used a simplified model with one degree of freedom in each joint of the lower extremities to reduce the simulation time. Therefore, it could be approached by the algebraic method or static optimization method. However, the dynamic optimization method used in this study may contribute more to future works. For example, it is a case of extending the degree of freedom of a model to predict the effect of the degree of freedom occurring in directions other than the sagittal plane. In addition, it also includes a simulation to predict changes in motion due to adaptation when the human body is wearing the device. By using the dynamic simulation code that we distribute with this study, readers will be able to perform simulations for the aforementioned cases. **Supplementary Materials:** The following are available online at [[http://www.mdpi.com/2076-3417/10/3/1160/s1](http://www.mdpi.com/2076-3417/10/3/1160/s1)]([http://www.mdpi.com/2076-3417/10/3/1160/s1](http://www.mdpi.com/2076-3417/10/3/1160/s1)), Figure S1: Tracking results of the generalized coordinates and generalized speeds (Type 1), Figure S2: Tracking results of the muscle activation (Type 1), Figure S3: Results of the fiber length and muscle excitation, Figure S4: Assistive forces and torques of the external actuators (Type 1), Figure S5: Tracking results of the generalized coordinates and generalized speeds (Type 2), Figure S6: Tracking results of the muscle activation (Type 2), Figure S7: Results of the fiber length and muscle excitation (Type 2), Figure S8: Assistive torques of the external actuators (Type 2), Figure S9: Net joint torques by the muscles (Type 1), Figure S10: Net joint torques by the muscles (Type 2), Raw data S1 Simulation results of Type 1 and Type 2, Code S1 Code for regenerating the optimization results. **Author Contributions:** All the authors have read and agree to the published version of the manuscript. Conceptualization, J.I.H., H.S.C., and Y.S.B. ; funding acquisition, J.I.H., H.S.C., and Y.S.B. ; methodology, software, validation, formal analysis, investigation, resources, data curation, writing--original draft preparation, visualization, J.I.H. ; supervision, Y.S.B. ; project administration, Y.S.B. ; writing--review and editing, J.I.H, Y.S.B.