Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training

ABSTRACT: BACKGROUND: Manual body weight supported treadmill training and robot-aided treadmill training are frequently used techniques for the gait rehabilitation of individuals after stroke and spinal cord injury. Current evidence suggests that robot-aided gait training may be improved by making robotic behavior more patient-cooperative. In this study, we have investigated the immediate effects of patient-cooperative versus non-cooperative robot-aided gait training on individuals with incomplete spinal cord injury (iSCI). METHODS: Eleven patients with iSCI participated in a single training session with the gait rehabilitation robot Lokomat. The patients were exposed to four different training modes in random order: During both non-cooperative position control and compliant impedance control, fixed timing of movements was provided. During two variants of the patient-cooperative path control approach, free timing of movements was enabled and the robot provided only spatial guidance. The two variants of the path control approach differed in the amount of additional support, which was either individually adjusted or exaggerated. Joint angles and torques of the robot as well as muscle activity and heart rate of the patients were recorded. Kinematic variability, interaction torques, heart rate and muscle activity were compared between the different conditions. RESULTS: Patients showed more spatial and temporal kinematic variability, reduced interaction torques, a higher increase of heart rate and more muscle activity in the patient-cooperative path control mode with individually adjusted support than in the non-cooperative position control mode. In the compliant impedance control mode, spatial kinematic variability was increased and interaction torques were reduced, but temporal kinematic variability, heart rate and muscle activity were not significantly higher than in the position control mode. CONCLUSIONS: Patient-cooperative robot-aided gait training with free timing of movements made individuals with iSCI participate more actively and with larger kinematic variability than non-cooperative, position-controlled robot-aided gait training

Can Momentum-Based Control Predict Human Balance Recovery Strategies?

Human-like balance controllers are desired for wearable exoskeletons in order to enhance human-robot interaction. Momentum-based controllers (MBC) have been successfully applied in bipeds, however, it is unknown to what degree they are able to mimic human balance responses. In this paper, we investigated the ability of an MBC to generate human-like balance recovery strategies during stance, and compared the results to those obtained with a linear full-state feedback (FSF) law. We used experimental data consisting of balance recovery responses of nine healthy subjects to anteroposterior platform translations of three different amplitudes. The MBC was not able to mimic the combination of trunk, thigh and shank angle trajectories that humans generated to recover from a perturbation. Compared to the FSF, the MBC was better at tracking thigh angles and worse at tracking trunk angles, whereas both controllers performed similarly in tracking shank angles. Although the MBC predicted stable balance responses, the human-likeness of the simulated responses generally decreased with an increased perturbation magnitude. Specifically, the shifts from ankle to hip strategy generated by the MBC were not similar to the ones observed in the human data. Although the MBC was not superior to the FSF in predicting human-like balance, we consider the MBC to be more suitable for implementation in exoskeletons, because of its ability to handle constraints (e.g. ankle torque limits). Additionally, more research into the control of angular momentum and the implementation of constraints could eventually result in the generation of more human-like balance recovery strategies by the MBC.status: publishe

Robot-Aided Gait Training with LOPES (chapter 21)

Robot-aided gait training in stroke survivors and spinal cord injury patients has shown inconclusive effects on walking ability. It is widely acknowledged that the control and design of the robotic devices needs to be further optimized to be able to provide training that fits better into modern insights in neural plasticity, motor learning, and motor recovery and in doing so improves its effectiveness. We will go more deeply into the need and scientific background for improvements on active participation, task specificity, and the facilitation of different recovery mechanisms. Subsequently, we will discuss recent advances that have been made in the control and design of robotic devices to improve on these aspects. Hereby, we will focus on the robotic gait training device LOPES that has been developed within our group. We will discuss how its design and control approach should contribute to improvements on all of the aforementioned aspects. The feasibility of the chosen approach is demonstrated by experimental results in healthy subjects and chronic stroke survivors. Future clinical testing has to demonstrate whether the outcome of robot-aided gait training can indeed be improved by increasing its task specificity, by the active contribution of the patient, and by allowing different movement strategies