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Knowing accurate model of a system is always beneficial to design a robust and safe control while allowing reduction of sensors-related cost as the system outputs are predictable using the model. In this context, this paper addresses the kinematical and dynamical model identification of the multipurpose rehabilitation robot, Universal Haptic Pantograph (UHP), and present experimental

Abstract-Numerous haptic devices have been developed for upper-limb neurorehabilitation, but their widespread use has been largely impeded because of complexity and cost. Here, we describe a variable structure pantograph mechanism combined with a spring suspension system that produces a versatile rehabilitation robot, called Universal Haptic Pantograph, for movement training of the shoulder, elbow, and wrist. The variable structure is a 5-degree-of-freedom (DOF) mechanism composed of 7 joints, 11 joint axes, and 3 configurable joint locks that reduce the number of system DOFs to between 0 and 3. The resulting device has eight operational modes: Arm, Wrist, ISO (isometric) 1, ISO 2, Reach, Lift 1, Lift 2, and Steer. The combination of available work spaces (reachable areas) shows a high suitability for movement training of most upperlimb activities of daily living. The mechanism, driven by series elastic actuators, performs similarly in all operational modes, with a single control scheme and set of gains. Thus, a single device with minimal setup changes can be used to treat a variety of upper-limb impairments that commonly afflict veterans with stroke, traumatic brain injury, or other direct trauma to the arm. With appropriately selected design parameters, the developed multimode haptic device significantly reduces the costs of robotic hardware for full-arm rehabilitation while performing similarly to that of single-mode haptic devices. We conducted case studies with three patients with stroke who underwent clinical training using the developed mechanism in Arm, Wrist, and/or Reach operational modes. We assessed outcomes using Fugl-Meyer Motor Assessment and Wolf Motor Function Test scores showing that upper-limb ability improved significantly following training sessions.

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Purpose:We present a novel wheelchair posture support device (WPSD) and its clinical validation. It was developed in order to assure correct sitting posture and to reduce caregiver time spent for repositioning of wheelchair-bound hospitalized post-acute stroke patients. Method:The device was validated with 16 subjects during a period of five 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 five days for reasons unrelated to the device. Caregivers needed to re-position the patients that used the device for the full five days (n=11) on average 52% less times 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 pain in patients during the use of it. Conclusions:The newly designed WPSD is a valuable system for the improvement in medical assistance of hospitalized 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. 2Clinical validation of a novel postural support device for hospitalized sub-acute post-stroke wheelchair users.

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.

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