Rehabilitation of the hands is critical for the restoration of independence in activities of daily living for individuals exhibiting disabilities of the upper extremities. There is initial evidence that robotic devices with force-control-based strategies can help in effective rehabilitation of human limbs. However, to the best of our knowledge, none of the existing hand exoskeletons allow for accurate force or torque control. In this work, we present a novel index finger exoskeleton with Bowden-cable-based series elastic actuation allowing for bidirectional torque control of the device with high backdrivability and low reflected inertia. We present exoskeleton and finger joint torque controllers along with an optimization-based offline parameter estimator. Finally, we carry out tests with the developed prototype to characterize its kinematics, dynamics, and controller performance. Results show that the device preserves the characteristics of natural motion of finger and can be controlled to achieve both exoskeleton and finger joint torque control. Finally, dynamic transparency tests show that the device can be controlled to offer minimal resistance to finger motion. Beyond the present application of the device as a hand rehabilitation exoskeleton, it has the potential to be used as a haptic device for teleoperation.

We present an exoskeleton capable of assisting the human thumb through a large range of motion. Our novel thumb exoskeleton has the following unique features: (i) an underlying kinematic mechanism that is optimized to achieve a large range of motion, (ii) a design that actuates four degrees of freedom of the thumb, and (iii) a series elastic actuation based on a Bowden cable, allowing for bidirectional torque control of each thumb joint individually. We present a kinematic model of the coupled thumb exoskeleton system and use it to maximize the range of motion of the thumb. Finally, we carry out tests with the designed device on four subjects to evaluate its workspace and kinematic transparency using a motion capture system and torque control performance. Results show that the device allows for a large workspace with the thumb, is kinematically transparent to natural thumb motion to a high degree, and is capable of accurate torque control.

Robotic rehabilitation of the hands from a neuromuscular impairment such as stroke requires controllers that could provide subject-specific assistance and result in fastest possible recovery. We present two such assist-as-needed controllers for a hand exoskeleton called Maestro that is designed to provide accurate torque assistance to a subject. Learned force-field control is a novel control technique in which a neural-network-based model of the required torques is learned offline for a specific subject and then used to render a force-field to assist the finger motion to follow a target trajectory. Adaptive assist-as-needed control, on the other hand, estimates the coupled finger-exoskeleton system torque requirement of a subject using a radial basis function (RBF) network and adapts the RBF magnitudes in real-time to provide a feedforward assistance for accurate trajectory tracking. Experiments with a healthy subject on Maestro showed that while the force-field control is nonadaptive and there is less control on the speed of execution of the task, it is safer as it does not apply increased torques if the finger motion is restricted. On the other hand, adaptive assist-as-needed controller adapts to the changing needs of the coupled finger-exoskeleton system and helps in performing the task with a consistent speed, however, applies increased torques in case of restricted motion and is therefore, potentially less safe.

We present a new methodology for designing a nonlinear rotational spring with a desired passive torque profile by using a noncircular pulley-spring mechanism. A synthesis procedure for the shape of the noncircular pulley is presented. The method is based on an infinitesimal calculus approach that leads to an analytical solution, and the method is extended to address practical design issues related to the cable routing. Based on the synthesis method, an antagonistic spring configuration is designed for bilateral torque generation and is designed such that there is no slack in the routing cables. Two design examples are presented, namely, double exponential torque generation and gravity compensation for an inverted pendulum. Experiments with a mechanism for gravity compensation of an inverted pendulum validate our approach. We extend our approach to generate nonlinear torques at two joints by introducing the concept of torque decomposition. Experiments with a two-link robotic arm show that the gravitational forces from the masses on each link are accurately compensated for with our noncircular pulley-spring mechanisms.

Torque control of small-scale robotic devices such as hand exoskeletons is challenging due to the unavailability of miniature and compact bidirectional torque actuators. In this work, we present a miniature Bowden-cable-based series elastic actuator (SEA) using helical torsion springs. The three-dimensional (3D) printed SEA is 38 mm × 38 mm × 24 mm in dimension and weighs 30 g, excluding motor which is located remotely. We carry out a thorough experimental testing of our previously presented linear compression spring SEA (LC-SEA) (Agarwal et al. 2015, “An Index Finger Exoskeleton With Series Elastic Actuation for Rehabilitation: Design, Control and Performance Characterization,” Int. J. Rob. Res., 34(14), pp. 1747–1772) and helical torsion spring SEA (HT-SEA) and compare the performance of the two designs. Performance characterization on a test rig shows that the two SEAs have adequate torque source quality (RMSE < 12% of peak torque) with high torque fidelities (>97% at 0.5 Hz torque sinusoid) and force tracking bandwidths of 2.5 Hz and 4.5 Hz (0.2 N·m), respectively, which make these SEAs suitable for our application of a hand exoskeleton.

The biomechanical complexity of the human shoulder, while critical for functionality, poses a challenge for objective assessment during sensorimotor rehabilitation. With built-in sensing capabilities, robotic exoskeletons have the potential to serve as tools for both intervention and assessment. The bilateral upper-extremity Harmony exoskeleton is capable of full shoulder articulation, forearm flexion-extension, and wrist pronation-supination motions. The goal of this paper is to characterize Harmony's anatomical joint angle tracking accuracy towards its use as an assessment tool. We evaluated the agreement between anatomical joint angles estimated from the robot's sensor data and optical motion capture markers attached to the human user. In 9 healthy participants we examined 6 upper-extremity joint angles, including shoulder girdle angles, across 4 different motions, varying active/passive motion of the user and physical constraint of the trunk. We observed mostly good to excellent levels of agreement between measurement systems with CMC _ip > 0.65 for shoulder and distal joints, magnitudes of average discrepancies varying from 0.43° to 16.03° and width of LoAs ranging between 9.44° and 41.91°. Slopes were between 1.03 and 1.43 with r > 0.9 for shoulder and distal joints. Regression analysis suggested that discrepancies observed between measured robot and human motions were primarily due to relative motion associated with soft tissue deformation. The results suggest that the Harmony exoskeleton is capable of providing accurate measurements of arm and shoulder joint kinematics. These findings may lead to robot-assisted assessment and intervention of one of the most complex joint structures in the human body.