Multi Degree of Freedom Hybrid FES and Robotic Control of the Upper Limb.

Individuals who have suffered a spinal cord injury often require assistance to complete daily activities, and for individuals with tetraplegia, recovery of upper-limb function is among their top priorities. Hybrid functional electrical stimulation (FES) and exoskeleton systems have emerged as a potential solution to provide upper limb movement assistance. These systems leverage the user's own muscles via FES and provide additional movement support via an assistive exoskeleton. To date, these systems have focused on single joint movements, limiting their utility for the complex movements necessary for independence. In this paper, we extend our prior work on model predictive control (MPC) of hybrid FES-exo systems and present a multi degree of freedom (DOF) hybrid controller that uses the controller's cost function to achieve desired behavior. In studies with neurologically intact individuals, the hybrid controller is compared to an exoskeleton acting alone for movement assistance scenarios incorporating multiple degrees-of-freedom of the limb to explore the potential for exoskeleton power consumption reduction and impacts on tracking accuracy. Additionally, each scenario is explored in simulation using the models required to generate the MPC formulation. The two DOF hybrid controller implementation saw reductions in power consumption and satisfactory trajectory tracking in both the physical and simulated systems. In the four DOF implementation, the experimental results showed minor improvements for some joints of the upper limb. In simulation, we observed comparable performance as in the two DOF implementation.

Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements.

Introduction: Individuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system. Methods: In this paper, we present a hybrid controller using a model predictive control (MPC) formulation that combines the actuation of both an exoskeleton and an FES system. The MPC cost function is designed to distribute actuation on a single degree of freedom to favor FES control effort, reducing exoskeleton power consumption, while ensuring smooth movements along different trajectories. Our controller was tested with nine able-bodied participants using FES surface stimulation paired with an upper limb powered exoskeleton. The hybrid controller was compared to an exoskeleton alone controller, and we measured trajectory error and torque while moving the participant through two elbow flexion/extension trajectories, and separately through two wrist flexion/extension trajectories. Results: The MPC-based hybrid controller showed a reduction in sum of squared torques by an average of 48.7 and 57.9% on the elbow flexion/extension and wrist flexion/extension joints respectively, with only small differences in tracking accuracy compared to the exoskeleton alone. Discussion: To realize practical implementation of hybrid FES-exoskeleton systems, the control strategy requires translation to multi-DOF movements, achieving more consistent improvement across participants, and balancing control to more fully leverage the muscles' capabilities.

Measuring Torque Production with a Robotic Exoskeleton during Cervical Transcutaneous Spinal Stimulation.

Spinal cord injury (SCI) affects a large number of individuals in the United States. Unfortunately, traditional neurorehabilitation therapy leaves out clinical populations with limited motor function, such as severe stroke or spinal cord injury, as they are incapable of engaging in movement therapy. To increase the numbers of individuals who may be able to participate in robotic therapy, our long-term goal is to combine two validated interventions, transcutaneous spinal stimulation (TSS) and robotics, to elicit upper limb movements during rehabilitation following SCI. To achieve this goal, it is necessary to quantify the contributions of each intervention to realizing arm movements. Electromyography is typically used to assess the response to TSS, but the robot itself offers an additional source of data since the available sensors on the robot can be used to directly assess resultant actions of the upper limb after stimulation. We explore this approach in this paper. We showed that the effects of cutaneous TSS can be observed by measuring the holding torque required by the exoskeleton to keep a user's arm in a neutral position. Further, we can identify differences in resultant action based on the location of the stimulation electrodes with respect to the dorsal roots of the spinal cord. In the future, we can use measurements from the robot to guide the action of the robot and TSS intervention.

Shared Control of Elbow Movements with Functional Electrical Stimulation and Exoskeleton Assistance.

Individuals who suffer from paralysis as a result of a spinal cord injury list restoration of arm and hand function as a top priority. FES helps restore movement using the user's own muscles, but does not produce accurate and repeatable movements necessary for many functional tasks. Robots can assist users in achieving accurate and repeatable movements, but often require bulky hardware to generate the necessary torques. We propose sharing torque requirements between a robot and FES to reduce robot torque output compared to a robot acting alone, yet maintain high accuracy. Cooperative PD and model predictive control algorithms were designed to share the control between these two torque sources. Corresponding PD and MPC algorithms that do not use FES were also designed. The control algorithms were tested with 10 able-bodied subjects. Torque and position tracking accuracy were compared when the system was commanded to follow a functional elbow flexion/extension trajectory. The robot torque required to achieve these movements was reduced for the shared control cases compared to the algorithms acting without FES. We observed a reduction in position accuracy with the MPC shared controller compared to the PD shared controller, while the MPC shared controller resulted in greater reductions in torque requirements. Both of these shared algorithms showed improvements over existing options, and can be used on any given trajectory, allowing for better transferability to functional tasks.

A Multisensory Approach to Present Phonemes as Language Through a Wearable Haptic Device.

Communication is an important part of our daily interactions; however, communication can be hindered, either through visual or auditory impairment, or because usual communication channels are overloaded. When standard communication channels are not available, our sense of touch offers an alternative sensory modality for transmitting messages. Multi-sensory haptic cues that combine multiple types of haptic sensations have shown promise for applications, such as haptic communication, that require large discrete cue sets while maintaining a small, wearable form factor. This article presents language transmission using a multi-sensory haptic device that occupies a small footprint on the upper arm. In our approach, phonemes are encoded as multisensory haptic cues consisting of vibration, radial squeeze, and lateral skin stretch components. Participants learned to identify haptically transmitted phonemes and words after training across a four day training period. A subset of our participants continued their training to extend word recognition free response. Participants were able to identify words after four days using multiple choice with an accuracy of 89% and after eight days using free response with an accuracy of 70%. These results show promise for the use of multisensory haptics for haptic communication, demonstrating high word recognition performance with a small, wearable device.

A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance.

Individuals with tetraplegia, typically attributed to spinal cord injuries (SCI) at the cervical level, experience significant health care costs and loss of independence due to their limited reaching and grasping capabilities. Neuromuscular electrical stimulation (NMES) is a promising intervention to restore arm and hand function because it activates a person's own paralyzed muscles; however, NMES sometimes lacks the accuracy and repeatability necessary to position the limb for functional tasks, and repeated muscle stimulation can lead to fatigue. Robotic devices have the potential to restore function when used as assistive devices to supplement or replace limited or lost function of the upper limb following SCI. Unfortunately, most robotic solutions are bulky or require significant power to operate, limiting their applicability to restore functional independence in a home environment. Combining NMES and robotic support systems into a single hybrid neuroprosthesis is compelling, since the robotic device can supplement the action of the muscles and improve repeatability and accuracy. Research groups have begun to explore applications of movement assistance for individuals with spinal cord injury using these technologies in concert. In this review, we present the state of the art in hybrid NMES-orthotic systems for upper limb movement restoration following spinal cord injury, and suggest areas for emphasis necessary to move the field forward. Currently, NMES-robotic systems use either surface or implanted electrodes to stimulate muscles, with rigid robotic supports holding the limb against gravity, or providing assistance in reaching movements. Usability of such systems outside of the lab or clinic is limited due to the complexity of both the mechanical components, stimulation systems, and human-machine interfaces. Assessment of system and participant performance is not reported in a standardized way. Future directions should address wearability through improvements in component technologies and user interfaces. Further, increased integration of the control action between NMES and robotic subsystems to reanimate the limb should be pursued. Standardized reporting of system performance and expanded clinical assessments of these systems are also needed. All of these advancements are critical to facilitate translation from lab to home.

Multi-Sensory Stimuli Improve Distinguishability of Cutaneous Haptic Cues.

Wearable haptic systems offer portable, private tactile communication to a human user. To date, advances in wearable haptic devices have typically focused on the optimization of haptic cue transmission using a single modality, or have combined two types of cutaneous feedbacks, each mapped to a particular parameter of the task. Alternatively, researchers have employed arrays of haptic tactile actuators to maximize information throughput to a user. However, when large cue sets are to be transmitted, such as those required to communicate language, perceptual interference between transmitted cues can decrease the efficacy of single-sensory systems, or require large footprints to ensure salient spatiotemporal cues are rendered to the user. In this paper, we present a wearable, multi-sensory haptic feedback system, MISSIVE (Multi-sensory Interface of Stretch, Squeeze, and Integrated Vibration Elements), that conveys multi-sensory haptic cues to the user's upper arm. We present experimental results that demonstrate that rendering haptic cues with multi-sensory components-specifically, lateral skin stretch, radial squeeze, and vibrotactile stimuli-improved perceptual distinguishability in comparison to similar cues with all-vibrotactile components. These results support the incorporation of diverse stimuli, both vibrotactile and nonvibrotactile, for applications requiring large haptic cue sets.