Multiplayer environments are thought to increase and prolongate active participation in robot-aided rehabilitation. We expect that environments linking patients with their spouses will particularly foster active participation. Thus, we developed two multiplayer games to link the game experience of two players: an Air Hockey game and a Haptic Kitchen game. In the competitive Air Hockey game, differences in skill levels between players were balanced by individualizing haptic guidance or damping forces. In the Haptic Kitchen game, a healthy player could support the patient's movements using a virtual force field. The two players could control the haptic interaction since both the force field and the point of application were visualized. We tested the haptic performance balancing algorithm of the Air Hockey game and the spouse-controlled haptic support of the Kitchen game with patients post-stroke who trained both single- (i.e., alone) and multiplayer training (i.e., with spouse) in eight therapy sessions lasting 45 min each. Mean total rating in Intrinsic Motivation Inventory was 46.9 points (out of 63 points) for multiplayer modes, and 42.7 points for single player modes, respectively. The spouses applied the haptic support in the Haptic Kitchen game during 42 % of the total game duration. We are currently testing more patient-spouse couples to better understand the effects of using these haptic approaches on the behavior and recovery of patients. We foresee this approach can improve the motivation during training and positively influence the at-home behavior of patients, an important goal of rehabilitation training efforts.

Error feedback is critical for supporting motor adaptation in rehabilitation, sports, piloting, and skilled manual tasks. Error augmentation interventions, in which participants' errors are amplified with either visual or haptic feedback during training has shown success over repetitive practice. Here we show that the statistical tendencies arising from free movement exploration can improve error augmentation with customized training forces that vary across the trajectory. We hypothesized that with customized error augmentation participants will adapt faster to learning a visual-motor distortion and have greater improvement than participants receiving standard error augmentation and participants repetitively practicing the task. We tested twenty-one participants using a robotic exoskeleton device restricted to two degrees of freedom. We found that participants receiving customized forces adapted faster and consequently changed with smaller forces. Further, change in error was greatest for participants receiving customized forces. These promising results support the need for customization to target subject specific errors.

Prolonged bed rest in severely paralyzed or intensive care patients is associated with adverse secondary effects on cardiopulmonary function. To counteract these effects of immobility in bed-ridden patients, we aim at controlling and stabilizing the cardiovascular system via multiple mechanical input variables. A challenge in this control problem is to provide an accurate model of the plant to be controlled. As humans are time variant systems and show individual physiological reactions to external stimuli the identification of such a model appears to be challenging. The current work presents a model-free predictive controller which takes into account these challenges. In this paper we present data concerning the control of heart rate, systolic and diastolic blood pressures, and mean arterial blood pressure via body tilting and leg mobilization. The controller was validated in a simulation study and feasibility was tested on two healthy subjects. The experimental results with healthy subjects show that the mean value differed in average less than 1 beat per minute (bpm) from the desired heart rate values and less than 1 mm Hg from the desired blood pressure values. The long term goal of this project is to control also breathing via body tilting, stepping and electrical muscle stimulation.

Intensive rehabilitation training of the arm can improve motor recovery in patients with neurological impairment. Actuated robots are becoming more and more common in this field as they serve to actively assist, enhance and assess neurorehabilitation. However, there is currently no actuated robot available specifically designed for the rehabilitation of children with upper extremity motor impairments. In this paper, we describe a completely new designed exoskeleton-based arm robot, ChARMin, with four degrees of freedom to guide and assist shoulder and elbow movements for young patients with motor impairments. The serial mechanical structure includes parallel kinematics for remote center of rotation actuation. This allows to keep a safe distance between parts of the robot and the patient and it reduces friction, while being highly adaptable to cover the anthropometrics for patients aged 5 to 18 years. Additionally, a novel passive weight support mechanism and 6 degrees of freedom force sensors are installed for a safe and transparent operation of the device.