This article discusses the pros and cons of compliant actuation for rehabilitation robots on the example of LOPES, focusing on the cons. After illustrating the bandwidth limitations, a new result has been derived: if stability in terms of passivity of the haptic device is desired, the renderable stiffness is bounded by the stiffness of the SEA's elastic component. In practical experiments with the VMC, the aforementioned limitations affected the control performance. Desired gait modifications were not tracked exactly, because the subjects were able to deviate from the prescribed pattern even in the stiffest possible configuration. Despite the limitations, the practical experiments also demonstrated the general effectiveness of the realization. Manipulation of selected gait parameters is possible, whereby other parameters are left unaffected. This high selectivity is made possible by the low level of undesired interaction torques, which is achieved by elastic decoupling of motor mass and a lightweight exoskeleton. The discrepancy between theoretical bounds and rendered stiffness indicated that healthy subjects might represent a stabilizing component of the coupled system, which could be different for patients. In light of the theoretical stability analysis and with the focus on patients, the LOPES actuation was slightly modified. The robot was equipped with stiffer springs to obtain sufficient stiffness and to ensure stability without relying on stabilizing effects of the human. For this application, the disadvantages of compliant actuation can thus be tolerated or dealt with, and they are small compared with the advantages. Given that a rehabilitation robot, in the first place, is supposed to imitate therapist action, the limitations of bandwidth and stiffness do not pose severe problems. In contrast, safety and backdrivability are highly relevant, and they can be ensured easier with a compliant actuator. Therefore, we conclude that compliant actuation and a lightw- - eight exoskeleton provide effective means to accomplish the desired AAN behavior of a rehabilitation robot. The next step is to evaluate the robot behavior, control performance, and therapeutic effectiveness in patient studies.