Comparison of Human-Robot Interaction Torque Estimation Methods in a Wrist Rehabilitation Exoskeleton

Analysis of Dynamic Behavior of ParReEx Robot Used in Upper Limb Rehabilitation

This paper presents a dynamic analysis of the ParReEx multibody mechanism, which has been designed for human wrist joint rehabilitation. The starting point of the research is a virtual prototype of the ParReEx multibody mechanism. This model is used to simulate the dynamics of the multibody mechanism using ADAMS in three simulation scenarios: (a) rigid kinematic elements without friction in joints, (b) rigid kinematic elements with friction in joints, and (c) kinematic elements as deformable solids with friction in joints. In all three cases, the robot is used by a virtual patient in the form of a mannequin. Results such as the connecting forces in the kinematic joints and the torques necessary to operate the ParReEx robot modules are obtained by dynamic simulation in MSC.ADAMS. The torques obtained by numerical simulation are compared with those obtained experimentally. Finite element structural optimization (FEA) of the flexion/extension multibody mechanism module is performed. The results demonstrate the operational safety of the ParReEx multibody mechanism, which is structurally capable of supporting the external loads to which it is subjected.

Human-Robot Interaction Torque Estimation Methods for a Lower Limb Rehabilitation Robotic System with Uncertainties

Lower limb rehabilitation robot (LLRR) users, to successfully conduct isotonic exercises, require real-time feedback on the torque they exert on the robot to meet the goal of the treatment. Still, direct torque measuring is expensive, and indirect encoder-based estimation strategies, such as inverse dynamics (ID) and Nonlinear Disturbance Observers (NDO), are sensitive to Body Segment Inertial Parameters (BSIPs) uncertainties. We envision a way to minimize such parametric uncertainties. This paper proposes two human–robot interaction torque estimation methods: the Identified ID-based method (IID) and the Identified NDO-based method (INDO). Evaluating in simulation the proposal to apply, in each rehabilitation session, a sequential two-phase method: (1) An initial calibration phase will use an online parameter estimation to reduce sensitivity to BSIPs uncertainties. (2) The torque estimation phase uses the estimated parameters to obtain a better result. We conducted simulations under signal-to-noise ratio (SNR) = 40 dB and 20% BSIPs uncertainties. In addition, we compared the effectiveness with two of the best methods reported in the literature via simulation. Both proposed methods obtained the best Coefficient of Correlation, Mean Absolute Error, and Root Mean Squared Error compared to the benchmarks. Moreover, the IID and INDO fulfilled more than 72.2% and 88.9% of the requirements, respectively. In contrast, both methods reported in the literature only accomplish 27.8% and 33.3% of the requirements when using simulations under noise and BSIPs uncertainties. Therefore, this paper extends two methods reported in the literature and copes with BSIPs uncertainties without using additional sensors.

Development of a Mechatronic System for the Mirror Therapy

This paper fits into the field of research concerning robotic systems for rehabilitation. Robotic systems are going to be increasingly used to assist fragile persons and to perform rehabilitation tasks for persons affected by motion injuries. Among the recovery therapies, the mirror therapy was shown to be effective for the functional recovery of an arm after stroke. In this paper we present a master/slave robotic device based on the mirror therapy paradigm for wrist rehabilitation. The device is designed to orient the affected wrist in real time according to the imposed motion of the healthy wrist. The paper shows the kinematic analysis of the system, the numerical simulations, an experimental mechatronic set-up, and a built 3D-printed prototype.

Design and Assist-as-Needed Control of Flexible Elbow Exoskeleton Actuated by Nonlinear Series Elastic Cable Driven Mechanism

Exoskeletons can assist the daily life activities of the elderly with weakened muscle strength, but traditional rigid exoskeletons bring parasitic torque to the human joints and easily disturbs the natural movement of the wearer’s upper limbs. Flexible exoskeletons have more natural human-machine interaction, lower weight and cost, and have great application potential. Applying assist force according to the patient’s needs can give full play to the wearer’s remaining muscle strength, which is more conducive to muscle strength training and motor function recovery. In this paper, a design scheme of an elbow exoskeleton driven by flexible antagonistic cable actuators is proposed. The cable actuator is driven by a nonlinear series elastic mechanism, in which the elastic elements simulate the passive elastic properties of human skeletal muscle. Based on an improved elbow musculoskeletal model, the assist torque of exoskeleton is predicted. An assist-as-needed (AAN) control algorithm is proposed for the exoskeleton and experiments are carried out. The experimental results on the experimental platform show that the root mean square error between the predicted assist torque and the actual assist torque is 0.00226 Nm. The wearing experimental results also show that the AAN control method designed in this paper can reduce the activation of biceps brachii effectively when the exoskeleton assist level increases.

A Novel 3-RRR Spherical Parallel Instrument for Daily Living Emulation (SPINDLE) for Functional Rehabilitation of Patients with Stroke

Various robotic rehabilitation devices have been developed for acute stroke patients to ease therapist’s efforts and provide high-intensity training, which resulted in improved strength and functional recovery of patients; however, these improvements did not always transfer to the performance of activities of daily living (ADLs). This is because previous robotic training focuses on the proximal joints or training with exoskeleton-type devices, which do not reflect how humans interact with the environment. To improve the training effect of ADLs, a new robotic training paradigm is suggested with a parallel manipulator that mimics rotational ADL tasks. This study presents training of the proximal and distal joints simultaneously while performing manipulation tasks in a device named spherical parallel instrument for daily living emulation (SPINDLE). Six representative ADLs were chosen to show that both proximal and distal joints are trained when performing tasks with SPINDLE, as compared to the natural ADLs. These results show that SPINDLE can train individuals with movements similar to the ADLs while interacting with the manipulator. We envision using this compact tabletop device as a home-training device to increase the performance of ADLs by restoring the impaired motor function of stroke patients, leading to improved quality of life.