Real time computation of Centroidal Momentum while human walking in the lower limbs rehabilitation exoskeleton: Preliminary trials.

In EU-funded BALANCE project, developing a stability index which can be employed to estimate actual state of balance of both healthy and neurologically impaired humans' walking in exoskeleton was one of scientific tasks. In the task, Centroidal Momentum (CM), referring to linear and angular momenta at Center of Mass (CoM), has raised as a potential index for such purpose. While our past studies have presented analysis results of CM in offline and online (real time) manners for walking of healthy human and stroke patients, in this study, we present real time computation of CM in exoskeleton-supported walking, specifically with healthy subjects. Experimental setup consists of LOPES II, a treadmill-based robotic gait training exoskeleton for lower limbs rehabilitation developed by Twente University, and commercially available IMUs (Inertial Measurement Units)-based full body motion capture suits from Xsens. CM was computed and demonstrated in two walking conditions: unperturbed walking and walking with unexpected pelvic perturbations in lateral direction. While electromagnetic fields (EMF) from LOPES II exoskeleton affected signals of IMUs in the motion capture suit, the results show the potential applicability of the CM as a sort of stability index for human walking in the exoskeleton.

Virtual Sensors for Advanced Controllers in Rehabilitation Robotics.

In order to properly control rehabilitation robotic devices, the measurement of interaction force and motion between patient and robot is an essential part. Usually, however, this is a complex task that requires the use of accurate sensors which increase the cost and the complexity of the robotic device. In this work, we address the development of virtual sensors that can be used as an alternative of actual force and motion sensors for the Universal Haptic Pantograph (UHP) rehabilitation robot for upper limbs training. These virtual sensors estimate the force and motion at the contact point where the patient interacts with the robot using the mathematical model of the robotic device and measurement through low cost position sensors. To demonstrate the performance of the proposed virtual sensors, they have been implemented in an advanced position/force controller of the UHP rehabilitation robot and experimentally evaluated. The experimental results reveal that the controller based on the virtual sensors has similar performance to the one using direct measurement (less than 0.005 m and 1.5 N difference in mean error). Hence, the developed virtual sensors to estimate interaction force and motion can be adopted to replace actual precise but normally high-priced sensors which are fundamental components for advanced control of rehabilitation robotic devices.

Interaction force and motion estimators facilitating impedance control of the upper limb rehabilitation robot.

In order to enhance the performance of rehabilitation robots, it is imperative to know both force and motion caused by the interaction between user and robot. However, common direct measurement of both signals through force and motion sensors not only increases the complexity of the system but also impedes affordability of the system. As an alternative of the direct measurement, in this work, we present new force and motion estimators for the proper control of the upper-limb rehabilitation Universal Haptic Pantograph (UHP) robot. The estimators are based on the kinematic and dynamic model of the UHP and the use of signals measured by means of common low-cost sensors. In order to demonstrate the effectiveness of the estimators, several experimental tests were carried out. The force and impedance control of the UHP was implemented first by directly measuring the interaction force using accurate extra sensors and the robot performance was compared to the case where the proposed estimators replace the direct measured values. The experimental results reveal that the controller based on the estimators has similar performance to that using direct measurement (less than 1 N difference in root mean square error between two cases), indicating that the proposed force and motion estimators can facilitate implementation of interactive controller for the UHP in robotmediated rehabilitation trainings.

Clinical validation of a novel postural support device for hospitalized sub-acute post-stroke wheelchair users.

PURPOSE: We present a novel wheelchair posture support device (WPSD) and its clinical validation. The device was developed in order to assure correct sitting posture and to reduce the time spent by caregivers for re-positioning of hospitalized, wheelchair-bound, post-acute stroke patients. METHOD: The device was validated with 16 subjects during a period of 5 days in which use of the device was compared with regular care practice. RESULTS: The device was used for the five consecutive days in 69% of patients, while for 6% it was not suitable; 25% did not complete the 5 days for reasons unrelated to the device. Caregivers needed to re-position the patients that used the device for the full 5 days (n = 11) on an average 52% less often when using the device, as compared to regular practice. Furthermore, the device was rated as usable and functional by the caregivers while significantly reducing perception of trunk and shoulder pain in patients during its use. CONCLUSIONS: The newly designed WPSD is a valuable system for the improvement of medical assistance to wheelchair-bound post-stroke patients by reducing pain and number of re-positioning manoeuvres. The WPSD might be applicable to any group of patients who need posture control in either wheelchair or common chair with arms support. IMPLICATIONS FOR REHABILITATION Advanced supports and cushions that can be shaped to individual needs, may help assure correct sitting posture in wheelchair-bound post-acute stroke patients. Advanced supports and cushions that can be shaped to individual needs, may reduce the number of times a caregiver has to re-position a hospitalized wheelchair-bound post-acute stroke patient on overall average by 52%. Advanced personalized supports and cushions may improve sitting comfort and reduce pain complaints for post-acute hospitalized stroke patients using a wheelchair.

Development of a powered mobile module for the ArmAssist home-based telerehabilitation platform.

The ArmAssist, developed by Tecnalia, is a system for at-home telerehabilitation of post-stroke arm impairments. It consists of a wireless mobile base module, a global position and orientation detection mat, a PC with display monitor, and a tele-rehabilitation software platform. This paper presents the recent development results on the mobile module augmenting its functionality by adding actuation components. Three DC servo motors were employed to drive the mobile module and a position control algorithm based on the kinematic model and velocity mode control was implemented such that the module tracks a path defined in the training software. Pilot tests of the powered mobile module were performed in experiments with different load conditions and two unimpaired subjects. Both test results show that the module is able to follow the predefined path within an acceptable error range for reach movement training. Further study and testing of the system in realistic conditions following stroke will be a future topic of research.