Adaptive support for patient-cooperative gait rehabilitation with the Lokomat

Abstract

The rehabilitation robot Lokomat allows automated treadmill training for patients with neurological gait disorders. The basic position control approach for the robot has been extended to patient-cooperative strategies. These strategies provide more freedom and allow patients to actively influence their training. However, patients are likely to need additional support during patient-cooperative training. In this paper, we propose an algorithm based on iterative learning control that shapes a supportive torque field. The torque field is supposed to assist the patient as much as needed in performing the desired task. We evaluated the algorithm in a proof-of-concept experiment with 3 healthy subjects. Results showed that the amount of support was automatically adapted to the activity and the individual needs of the subjects. Furthermore, the support improved the performance of the subjects. Adaptive Support for Patient-Cooperative Gait Rehabilitation with the LokomatAlexander Duschau-Wicke, Thomas Brunsch, Lars Lünenburger, and Robert RienerAbstract-The rehabilitation robot Lokomat allows automated treadmill training for patients with neurological gait disorders. The basic position control approach for the robot has been extended to patient-cooperative strategies. These strategies provide more freedom and allow patients to actively influence their training. However, patients are likely to need additional support during patient-cooperative training. In this paper, we propose an algorithm based on iterative learning control that shapes a supportive torque field. The torque field is supposed to assist the patient as much as needed in performing the desired task. We evaluated the algorithm in a proof-of-concept experiment with 3 healthy subjects. Results showed that the amount of support was automatically adapted to the activity and the individual needs of the subjects. Furthermore, the support improved the performance of the subjects.

Using Sound feedback to counteract visual distractor during robot-assisted movement training

“…Three notable recent efforts in this direction are the "assistas-needed" control proposed by Reinkensemyer for the Pneu-WREX [24], a pneumatic exoskeleton for arm rehabilitation used in the current study, patient-cooperative adaptive control [25], and the "performance-based progressive assistance" proposed by Krebs for the pioneering arm-training robot MIT-MANUS [26], [27], [28], which assists in arm movement in the horizontal plane. The first is a robot control algorithm that allows the effort of the patient to be modulated while maintaining the kinematics of the patient's arm within close bounds to a specified desired movement [24], [29].…”

Using socially assistive robotics to augment motor task performance in individuals post-stroke

“…The general approach in this field has been to create orthoses that physically interact with individuals with motor deficits. Lower extremity (LE) devices such as the LOKOMAT R [11] and ALEX (active leg exoskeleton), designed for gait retraining, apply forces to the leg sections in an attempt to retrain healthy gait patterns [12]. Upper extremity (UE) devices include the ARM Guide, developed by Reinkensmeyer et al, to help individuals target objects using the affected limb [13].…”

Orthotic body-weight support through underactuated potential energy shaping with contact constraints

“…Conventional static and passive training systems usually consist of winches, counterweights, and elastic springs [5], while recently, several robotic BWS devices have been developed to automate the assistance during gait training. For example, the Lokomat exoskeleton system uses motors to drive the patient's lower limbs based on a reference trajectory over a treadmill [6]. The LOPES [7] treadmill system provides BWS via cable-driven series elastic actuators with an impedance controller.…”

“…The Lokomat system uses an impedance controller combined with supportive torques estimated through an adaptation algorithm, which makes the patients follow a specific joint position trajectory [6]. However, studies have shown that for subacute stroke patients, conventional labor-intensive interventions are more effective than robotic-assisted gait training using the Lokomat [8].…”