Precise, fine motor movements that can be trained and learned on Earth are more difficult to perform under microgravity and weightlessness. Using exoskeletons, conditions like those experienced under microgravity are simulated for the arms to evaluate whether exoskeleton technology can be integrated into astronaut training. In addition to classical control approaches, artificial intelligence methods are being developed for calibration. The exoskeleton learns the weight of the wearer’s arm through interaction and compensates for this weight to simulate different types of microgravity such as in space, on Moon or on Mars. It is being investigated whether microgravity simulated using the exoskeleton can be used to simulate effects of microgravity analogous to spaceflight.

Exoskeleton-based training may provide an alternative to analog scenarios such as parabolic flights. Approaches can be transferred to the evaluation of neuromotor learning processes in the context of rehabilitation medicine with liIle effort to optimize specific approaches of “”Assist-as-Needed””. Here the weight of the patient’s arm is compensated to enable movement with low effort. To adjust this support, the exact weight of the arm must be determined here as well. We present results on the extent to which movements under simulated microgravity have an impact on muscle activity measured by electromyogram. A parabolic flight for measurements under real microgravity is planned for next year.