A Sonomyography-Based Muscle Computer Interface for Individuals With Spinal Cord Injury

Impairment of hand functions in individuals with spinal cord injury (SCI) severely disrupts activities of daily living. Recent advances have enabled rehabilitation assisted by robotic devices to augment the residual function of the muscles. Traditionally, electromyography-based muscle activity sensing interfaces have been utilized to sense volitional motor intent to drive robotic assistive devices. However, the dexterity and fidelity of control that can be achieved with electromyography-based control have been limited due to inherent limitations in signal quality. We have developed and tested a muscle-computer interface (MCI) utilizing sonomyography to provide control of a virtual cursor for individuals with motor-incomplete spinal cord injury. We demonstrate that individuals with SCI successfully gained control of a virtual cursor by utilizing contractions of muscles of the wrist joint. The sonomyography-based interface enabled control of the cursor at multiple graded levels demonstrating the ability to achieve accurate and stable endpoint control. Our sonomyography-based muscle-computer interface can enable dexterous control of upper-extremity assistive devices for individuals with motor-incomplete SCI.

Analysis of Motor Control and Learning in Human-Robot Interaction during Game Guided Movements

Robotic devices can be used in upper limb rehabilitation in order to help the total or partial functional recovery. Robots can perform repetitive activities for a long period of time, which may be beneficial for rehabilitation processes. In this context, this study uses a bi-manual robotic device to investigate motor learning and control for the upper limbs among different game guided tasks, and inspect the user's grip force exerted in response to perturbations. The robotic device resembles a bicycle handlebar, instrumented with load cells to measure torques and grip forces. It is equipped with a DC motor to apply external torques to the guiding system. A game was developed containing in-game and physical perturbations to the natural movement of the handlebar. Tests were carried out with 16 healthy subjects that were instructed to move the handlebar guiding a character displayed on the screen with the objective of collecting tokens to get the higher score in the game. During the trials, corresponding data from the game and the load cells were collected and used to infer the learning process, the mean error in the trajectory and the variations in the force applied to the handles of the handlebar. Analyses showed that there was learning in the first repetitions, and the learning was retained further. The higher values of the grip force occurred when there was a physical perturbation to the handlebar's natural movement. The larger errors in the trajectories occurred immediately after the perturbations ended. In conclusion, there was a performance improvement, probably related to learning. The increase of the mean error at the transitions of the perturbations indicates the need for adaptation to the new conditions of the task.

Will Your Next Therapist Be a Robot?-A Review of the Advancements in Robotic Upper Extremity Rehabilitation

Several recent studies have indicated that upper extremity injuries are classified as a top common workplace injury. Therefore, upper extremity rehabilitation has become a leading research area in the last few decades. However, this high number of upper extremity injuries is viewed as a challenging problem due to the insufficient number of physiotherapists. With the recent advancements in technology, robots have been widely involved in upper extremity rehabilitation exercises. Although robotic technology and its involvement in the rehabilitation field are rapidly evolving, the literature lacks a recent review that addresses the updates in the robotic upper extremity rehabilitation field. Thus, this paper presents a comprehensive review of state-of-the-art robotic upper extremity rehabilitation solutions, with a detailed classification of various rehabilitative robots. The paper also reports some experimental robotic trials and their outcomes in clinics.

Two-Dof Upper Limb Rehabilitation Robot Driven by Straight Fibers Pneumatic Muscles

In this paper, the design of a 2-dof (degrees of freedom) rehabilitation robot for upper limbs driven by pneumatic muscle actuators is presented. This paper includes the different aspects of the mechanical design and the control system and the results of the first experimental tests. The robot prototype is constructed and at this preliminary step a position and trajectory control by fuzzy logic is implemented. The pneumatic muscle actuators used in this arm are designed and constructed by the authors’ research group.

Design and Prototyping of an Underactuated Hand Exoskeleton With Fingers Coupled by a Gear-Based Differential

Exoskeletons and more in general wearable mechatronic devices represent a promising opportunity for rehabilitation and assistance to people presenting with temporary and/or permanent diseases. However, there are still some limits in the diffusion of robotic technologies for neuro-rehabilitation, notwithstanding their technological developments and evidence of clinical effectiveness. One of the main bottlenecks that constrain the complexity, weight, and costs of exoskeletons is represented by the actuators. This problem is particularly evident in devices designed for the upper limb, and in particular for the hand, in which dimension limits and kinematics complexity are particularly challenging. This study presents the design and prototyping of a hand finger exoskeleton. In particular, we focus on the design of a gear-based differential mechanism aimed at coupling the motion of two adjacent fingers and limiting the complexity and costs of the system. The exoskeleton is able to actuate the flexion/extension motion of the fingers and apply bidirectional forces, that is, it is able to both open and close the fingers. The kinematic structure of the finger actuation system has the peculiarity to present three DoFs when the exoskeleton is not worn and one DoF when it is worn, allowing better adaptability and higher wearability. The design of the gear-based differential is inspired by the mechanism widely used in the automotive field; it allows actuating two fingers with one actuator only, keeping their movements independent.

Development of Wrist Interface Based on Fully Actuated Coaxial Spherical Parallel Mechanism for Force Interaction

To develop a wrist robotic exoskeleton-type interface (REI) for force interaction, it should have a suitable range of motion similar to human wrist activities of daily living, large torque output performance, and low moving parts inertia for dynamic motion response to cover the human behavior frequency. In this paper, a wrist REI based on a fully actuated coaxial spherical parallel mechanism (CSPM) is proposed to satisfy the aforementioned features. The fully actuated CSPM-based wrist REI (FC-WREI) has the characteristics of pure rotation similar to the human wrist, high torque output by parallel torque synthesis, and low moving parts inertia due to the base arrangement of the actuators. Due to the mechanical advantages and design optimization, the FC-WREI maximally provides torque as much as 56.49–130.43% of the maximum isometric torque of the human wrist, while providing a consistent range of motion to the human wrist without interference problem. Moreover, it is confirmed that the inertia of the FC-WREI is up to 5.35 times lower than similar devices. These advantages of the FC-WREI mean that the device is applicable to various fields of REIs for force interaction.

Nonlinear time delay estimation based model reference adaptive impedance control for an upper-limb human-robot interaction

A nonlinear Time Delay Estimation (TDE) based model reference adaptive impedance controller was developed for Tarbiat Modares University Upper Limbs Rehabilitation Robot (TUERR). The proposed controller uses a stable reference impedance model, which produces desired dynamic relationship between applied force and position error for the robot End-effector to track the desired trajectory. TDE based model reference adaptive controller estimates unknown system dynamics and uncertainties, and the adaption law modifies the controller gains. Using a Lyapunov function was shown trajectory tracking errors in the overall system are bounded. In addition, a performance-based velocity profile proposed to modify the pace of trajectory planning considering the deviation from the desired path. Finally, the performance of the presented controller and rehabilitation process is experimentally investigated for TUERR.

A novel wrist rehabilitation exoskeleton using 3D-printed multi-segment mechanism

Wrist rehabilitation exoskeleton can effectively assist wrist recovery from stroke. However, current wrist rehabilitation devices have shortcomings such as heavy weight, uncertain motion trajectory, etc. This paper proposes a wrist rehabilitation robot driven by 3D-printed multi-segment mechanism to realize wrist rehabilitation in three degrees of freedom. We conducted three tests including bearing force, rehabilitation trajectory, range of motion tests. The results prove this exoskeleton can provide enough force and torque, and it can achieve larger range of motion within the same motor displacement, that makes it more compact and lighter in hardware and less expensive in cost. Moreover, its motion trajectory can be controlled and stable, that makes it more applicable for real application in human rehabilitation.Clinical Relevance- Stroke is the leading cause of hemiplegia, and this symptom usually degrades patients' living standard and flexibility. This device can offer patients stable wrist rehabilitation training in three degrees of freedom with compact and lightweight characteristics.

Real-Time Identification of Wrist Kinematics via Sparsity-Promoting Extended Kalman Filter Based on Ellipsoidal Joint Formulation

This paper proposes a novel method for real-time wrist kinematics identification. Method: We design the wrist kinematics regression model following a novel ellipsoidal joint formulation, which features a quaternion-based rotation constraint and 2-dimensional Fourier linear combiners (FLC) to approximate the coupled rotations and translational displacements of the wrist. Extended Kalman Filter (EKF) is then implemented to update the model in real-time. However, unlike previous studies, here we introduce a sparsity-promoting feature in the model regression through the optimality of EKF by designing a smooth 1-minimization observation function. This is done to ensure the best identification of key parameters, and to improve the robustness of regression under noisy conditions. Results: Simulations employ multiple reference models to evaluate the performance of the proposed approach. Experiments are later carried out on motion data collected by a lab-developed wrist kinematics measurement tool. Both simulation and experiment show that the proposed approach can robustly identify the wrist kinematics in real-time. Conclusion: The findings confirm that the proposed regression model combined with the sparsity-promoting EKF is reliable in the real-time modeling of wrist kinematics. Significance: The proposed method can be applied to generic wrist kinematics modeling problems, and utilized in the control system of wearable wrist exoskeletons. The framework of the proposed method may also be applied to real-time identification of other joints for exoskeleton control.

A wearable wrist haptic display for motion tracking and force feedback in the operational space

Force feedback is often beneficial for robotic teleoperation, as it enhances the user's remote perception. Over the years, many kinesthetic haptic displays (KHDs) have been proposed for this purpose, which have different types of interaction and feedback, depending on their kinematics and their interface with the operator, including, for example, grounded and wearable devices acting either at the joint or operational space (OS) level. Most KHDs in the literature are for the upper limb, with a majority acting at the shoulder/elbow level, and others focusing on hand movements. A minority exists which addresses wrist motions. In this paper, we present the Wearable Delta (W), a proof-of-concept wearable wrist interface with hybrid parallel-serial kinematics acting in the OS, able to render a desired force directly to the hand involving just the forearm-hand subsystem. It has six degrees of freedom (DoFs), three of which are actuated, and is designed to reduce the obstruction of the range of the user's wrist. Integrated with positions/inertial sensors at the elbow and upper arm, the W allows the remote control of a full articulated robotic arm. The paper covers the whole designing process, from the concept to the validation, as well as a multisubject experimental campaign that investigates its usability. Finally, it presents a section that, starting from the experimental results, aims to discuss and summarize the W advantages and limitations and look for possible future improvements and research directions.

A review: A Comprehensive Review of Soft and Rigid Wearable Rehabilitation and Assistive Devices with a Focus on the Shoulder Joint

The importance of the human upper limb role in performing daily life and personal activities is significant. Improper functioning of this organ due to neurological disorders or surgeries can greatly affect the daily activities performed by patients. This paper aims to comprehensively review soft and rigid wearable robotic devices provided for rehabilitation and assistance focusing on the shoulder joint. In the last two decades, many devices have been proposed in this regard, however, there have been a few groups whose devices have had effective therapeutic capability with acceptable clinical evidence. Also, there were not many portable, lightweight and user-friendly devices. Therefore, this comprehensive study could pave the way for achieving optimal future devices, given the growing need for these devices. According to the results, the most commonly used plan was Exoskeleton, the most commonly used actuators were electrical, and most devices were considered to be stationary and rigid. By doing these studies, the advantages and disadvantages of each method are also presented. The presented devices each have a new idea and attitude in a specific field to solve the problems of movement disorders and rehabilitation, which were in the form of prototypes, initial clinical studies and sometimes comprehensive clinical and commercial studies. These plans need more comprehensive clinical trials to become a complete and efficient plan. This article could be used by researchers to identify and evaluate the important features and strengths and weaknesses of the plans to lead to the presentation of more optimal plans in the future.

Towards a Platform for Robot-Assisted Minimally-Supervised Therapy of Hand Function: Design and Pilot Usability Evaluation

Background

Robot-assisted therapy can increase therapy dose after stroke, which is often considered insufficient in clinical practice and after discharge, especially with respect to hand function. Thus far, there has been a focus on rather complex systems that require therapist supervision. To better exploit the potential of robot-assisted therapy, we propose a platform designed for minimal therapist supervision, and present the preliminary evaluation of its immediate usability, one of the main and frequently neglected challenges for real-world application. Such an approach could help increase therapy dose by allowing the training of multiple patients in parallel by a single therapist, as well as independent training in the clinic or at home.

Methods

We implemented design changes on a hand rehabilitation robot, considering aspects relevant to enabling minimally-supervised therapy, such as new physical/graphical user interfaces and two functional therapy exercises to train hand motor coordination, somatosensation and memory. Ten participants with chronic stroke assessed the usability of the platform and reported the perceived workload during a single therapy session with minimal supervision. The ability to independently use the platform was evaluated with a checklist.

Results

Participants were able to independently perform the therapy session after a short familiarization period, requiring assistance in only 13.46 (7.69–19.23)% of the tasks. They assigned good-to-excellent scores on the System Usability Scale to the user-interface and the exercises [85.00 (75.63–86.88) and 73.75 (63.13–83.75) out of 100, respectively]. Nine participants stated that they would use the platform frequently. Perceived workloads lay within desired workload bands. Object grasping with simultaneous control of forearm pronosupination and stiffness discrimination were identified as the most difficult tasks.

Discussion

Our findings demonstrate that a robot-assisted therapy device can be rendered safely and intuitively usable upon first exposure with minimal supervision through compliance with usability and perceived workload requirements. The preliminary usability evaluation identified usability challenges that should be solved to allow real-world minimally-supervised use. Such a platform could complement conventional therapy, allowing to provide increased dose with the available resources, and establish a continuum of care that progressively increases therapy lead of the patient from the clinic to the home.

3D Scanning of the Forearm for Orthosis and HMI Applications

The rise of rehabilitation robotics has ignited a global investigation into the human machine interface (HMI) between device and user. Previous research on wearable robotics has primarily focused on robotic kinematics and controls but rarely on the actual design of the physical HMI (pHMI). This paper presents a data-driven statistical forearm surface model for designing a forearm orthosis in exoskeleton applications. The forearms of 6 subjects were 3D scanned in a custom-built jig to capture data in extreme pronation and supination poses, creating 3D point clouds of the forearm surface. Resulting data was characterized into a series of ellipses from 20 to 100% of the forearm length. Key ellipse parameters in the model include: normalized major and minor axis length, normalized center point location, tilt angle, and circularity ratio. Single-subject (SS) ellipse parameters were normalized with respect to forearm radiale-stylion (RS) length and circumference and then averaged over the 6 subjects. Averaged parameter profiles were fit with 3rd-order polynomials to create combined-subjects (CS) elliptical models of the forearm. CS models were created in the jig as-is (CS1) and after alignment to ellipse centers at 20 and 100% of the forearm length (CS2). Normalized curve fits of ellipse major and minor axes in model CS2 achieve R² values ranging from 0.898 to 0.980 indicating a high degree of correlation between cross-sectional size and position along the forearm. Most other parameters showed poor correlation with forearm position (0.005 < R² < 0.391) with the exception of tilt angle in pronation (0.877) and circularity in supination (0.657). Normalized RMSE of the CS2 ellipse-fit model ranged from 0.21 to 0.64% of forearm circumference and 0.22 to 0.46% of forearm length. The average and peak surface deviation between the scaled CS2 model and individual scans along the forearm varied from 0.56 to 2.86 mm (subject averages) and 3.86 to 7.16 (subject maximums), with the peak deviation occurring between 45 and 50% RS length. The developed equations allow reconstruction of a scalable 3D model that can be sized based on two user measures, RS length and forearm circumference, or based on generic arm measurements taken from existing anthropometric databases.

A Cable-Driven Three-DOF Wrist Rehabilitation Exoskeleton With Improved Performance

This paper developed a cable-driven three-degree-of-freedom (DOF) wrist rehabilitation exoskeleton actuated by the distributed active semi-active (DASA) system. Compared with the conventional cable-driven robots, the workspace of this robot is increased greatly by adding the rotating compensation mechanism and by optimizing the distribution of the cable attachment points. In the meanwhile, the efficiency of the cable tension is improved, and the parasitic force (the force acting on the joint along the limb) is reduced. Besides, in order to reduce the effects of compliant elements (e.g., cables or Bowden cables) between the actuators and output, and to improve the force bandwidth, we designed the DASA system composed of one geared DC motor and four magnetorheological (MR) clutches, which has low output inertia. A fast unbinding strategy is presented to ensure safety in abnormal conditions. A passive training algorithm and an assist-as-needed (AAN) algorithm were implemented to control the exoskeleton. Several experiments were conducted on both healthy and impaired subjects to test the performance and effectiveness of the proposed system for rehabilitation. The results show that the system can meet the needs of rehabilitation training for workspace and force-feedback, and provide efficient active and passive training.

An Assistive Soft Wrist Exosuit for Flexion Movements With an Ergonomic Reinforced Glove

Soft exosuits are a promising solution for the assistance and augmentation of human motor abilities in the industrial field, where the use of more symbiotic wearable robots can avoid excessive worker fatigue and improve the quality of the work. One of the challenges in the design of soft exosuits is the choice of the right amount of softness to balance load transfer, ergonomics, and weight. This article presents a cable-driven based soft wrist exosuit for flexion assistance with the use of an ergonomic reinforced glove. The flexible and highly compliant three-dimensional (3D)-printed plastic structure that is sewn on the glove allows an optimal force transfer from the remotely located motor to the wrist articulation and to preserve a high level of comfort for the user during assistance. The device is shown to reduce fatigue and the muscular effort required for holding and lifting loads in healthy subjects for weights up to 3 kg.

Design and testing of a soft parallel robot based on pneumatic artificial muscles for wrist rehabilitation

Wrist rehabilitation is needed to help post-stroke and post-surgery patients recover from wrist fracture or injury. Traditional rehabilitation training is conducted by a therapist in a hospital, which hinders timely treatment due to the corresponding time and space constraints. This paper presents the design and implementation of a soft parallel robot for automated wrist rehabilitation. The presented wrist rehabilitation robot integrates the advantages of both soft robot and parallel robot structures. Unlike traditional rigid-body based rehabilitation robots, this soft parallel robot exhibits a compact structure, which is highly secure, adaptable, and flexible and thus a low-cost solution for personalized treatment. The proposed soft wrist-rehabilitation robot is driven by six evenly distributed linear actuators using pneumatic artificial muscles and one central linear electric motor. The introduced parallel-kinematic mechanism design enables the enhancement of the output stiffness of the soft robot for practical use. An electromyography sensor is adopted to provide feedback signals for evaluating the rehabilitation training process. A kinematic model of the designed robot is derived, and a prototype is fabricated for experimental testing. The results demonstrate that the developed soft rehabilitation robot can assist the wrist to realize all the required training motions, including abduction-adduction, flexion-extension, and supination-pronation. The compact and lightweight structure of this novel robot makes it convenient to use, and suitable rehabilitation training modes can be chosen for tailored rehabilitation at home or in a hospital.

Multibody Analysis and Control of a Full-Wrist Exoskeleton for Tremor Alleviation

Uncontrollable shaking in the human wrist, caused by pathological tremor, can significantly undermine the power and accuracy in object manipulation. In this paper, the design of a tremor alleviating wrist exoskeleton (TAWE) is introduced. Unlike the works in the literature that only consider the flexion/extension (FE) motion, in this paper, we model the wrist joint as a constrained three-dimensional (3D) rotational joint accounting for the coupled FE and radial/ulnar deviation (RUD) motions. Hence TAWE, which features a six degrees-of-freedom (DOF) rigid linkage structure, aims to accurately monitor, suppress tremors, and provide light-power augmentation in both FE and RUD wrist motions. The presented study focuses on providing a fundamental understanding of the feasibility of TAWE through theoretical analyses. The analytical multibody modeling of the forearm-TAWE assembly provides insight into the necessary conditions for control, which indicates that reliable control conditions in the desired workspace can be acquired by tuning the design parameters. Nonlinear regressions are then implemented to identify the information that is crucial to the controller design from the unknown wrist kinematics. The proposed analytical model is validated numerically with V-REP and the result shows good agreement. Simulations also demonstrate the reliable performance of TAWE under controllers designed for tremor suppression and movement assistance.

Importance of Wrist Movement Direction in Performing Activities of Daily Living Efficiently

The wrist is an essential component in performing the activities of daily living (ADLs) associated with a high quality of life. After a neurological disorder, motor function of the hand and wrist can be affected, reducing quality of life. Many experiments have illustrated that more wrist flexion/extension is required than radial/ulnar deviation when performing ADLs; however, how this result translates to efficiency in performing ADLs has not been investigated. Motivated by clinical assessment during neurorehabilitation, in this paper we investigate with able-bodied participants how performing tasks representative of the Jebsen-Taylor Hand Function Test are impacted when a splint constrains the user to a single rotational degree of freedom of the wrist. Twenty participants enrolled in the study, performing five tasks under five conditions, including constraint to pure flexion/extension and radial/ulnar deviation. The importance of wrist movement direction in performing ADLs efficiently found in this study could shape clinical wrist rehabilitation paradigms and wrist rehabilitation robot designs.

Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke

BACKGROUND

Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orientates and stabilizes the hand before and during grasping, and is therefore of critical importance in activities of daily living (ADL). To improve rehabilitation outcomes, classical therapy could be supplemented by novel therapies that can be applied in unsupervised settings. This would enable more distributed practice and could potentially increase overall training dose. Robotic technology offers new possibilities to address this challenge, but it is critical that devices for independent training are easy and appealing to use. Here, we present the development, characterization and wearability evaluation of a fully portable exoskeleton for active wrist extension/flexion support in stroke rehabilitation.

METHODS

First we defined the requirements, and based on these, constructed the exoskeleton. We then characterized the device with standardized haptic and human-robot interaction metrics. The exoskeleton is composed of two modules placed on the forearm/hand and the upper arm. These modules weigh 238 g and 224 g, respectively. The forearm module actively supports wrist extension and flexion with a torque up to 3.7 Nm and an angular velocity up to 530 deg/s over a range of 154∘. The upper arm module includes the control electronics and battery, which can power the device for about 125 min in normal use. Special emphasis was put on independent donning and doffing of the device, which was tested via a wearability evaluation in 15 healthy participants and 2 stroke survivors using both qualitative and quantitative methods.

RESULTS

All participants were able to independently don and doff the device after only 4 practice trials. For healthy participants the donning and doffing process took 61 ±15 s and 24 ±6 s, respectively. The two stroke survivors donned and doffed the exoskeleton in 54 s/22 s and 113 s/32 s, respectively. Usability questionnaires revealed that despite minor difficulties, all participants were positive regarding the device.

CONCLUSIONS

This study describes an actuated wrist exoskeleton which weighs less than 500 g, and which is easy and fast to don and doff with one hand. Our design has put special emphasis on the donning aspect of robotic devices which constitutes the first barrier a user will face in unsupervised settings. The proposed device is a first and intermediate step towards wearable rehabilitation technologies that can be used independently by the patient and in unsupervised settings.

Haptics in Teleoperated Medical Interventions: Force Measurement, Haptic Interfaces and Their Influence on User's Performance

OBJECTIVES

Haptics in teleoperated medical interventions enables measurement and transfer of force information to the operator during robot-environment interaction. This paper provides an overview of the current research in this domain and guidelines for future investigations.

METHODS

We review current technologies in force measurement and haptic devices as well as their experimental evaluation and influence on user's performance.

RESULTS

Force sensing is moving away from the conventional proximal measurement methods to distal sensing and contact-less methods. Wearable devices that deliver haptic feedback on different body parts are increasingly playing an important role. Performance and accuracy improvement are the widely reported benefits of haptic feedback, while there is a debate on its effect on task completion time and exerted force.

CONCLUSION

With the surge of new ideas, there is a need for better and more systematic validation of the new sensing and feedback technology, through better user studies and novel methods like validated benchmarks and new taxonomies.

SIGNIFICANCE

This review investigates haptics from sensing to interfaces within the context of user's performance and the validation procedures to highlight salient advances. It provides guidelines to future developments and highlights the shortcomings in the field.

Modeling and analysis of hydraulic piston actuation of McKibben fluidic artificial muscles for hand rehabilitation

Soft robotic actuators are well-suited for interactions with the human body, particularly in rehabilitation applications. The fluidic artificial muscle (FAM), specifically the McKibben FAM, is a type of soft robotic actuator that can be driven either pneumatically or hydraulically, and has potential for use in rehabilitation devices. The force applied by a FAM is well-described by a variety of models, the most common of which is based on the virtual work principle. However, the use of a piston assembly as a hydraulic power source for activation of FAMs has not previously been modeled in detail. This article presents a FAM designed to address the specific needs of a hand rehabilitation device. A syringe pump test bed is used to find and validate a novel volume–strain relationship. The volume–strain relationship remains constant with the coupled piston–FAM system, regardless of load. This confirms a bivariate approach to FAM control which is particularly beneficial in the exoskeleton application as the load varies throughout use. A novel, fixed-end cylindrical model is found to predict the strain of the FAM, given a volume input, regardless of load. For the FAMs tested in this work, the fixed-end cylindrical model improves strain prediction seven-fold when compared with traditional models.

EMG-Based Real-Time Linear-Nonlinear Cascade Regression Decoding of Shoulder, Elbow, and Wrist Movements in Able-Bodied Persons and Stroke Survivors

OBJECTIVE

This study aimed to decode shoulder, elbow and wrist dynamic movements continuously and simultaneously based on multi-channel surface electromyography signals, useful for electromyography controlled exoskeleton robots for upper-limb rehabilitation.

METHODS

Ten able-bodied subjects and ten stroke subjects were instructed to voluntarily move the shoulder, elbow and wrist joints back and forth in a horizontal plane with an exoskeleton robot. The shoulder, elbow and wrist movements and surface electromyography signals from six muscles crossing the joints were recorded. A set of three parallel linear-nonlinear cascade decoders was developed to continuously estimate the selected shoulder, elbow and wrist movements based on a generalized linear model using the anterior deltoid, posterior deltoid, biceps brachii, long head triceps brachii, flexor carpi radialis, and extensor carpi radialis muscle electromyography signals as the model inputs.

RESULTS

The decoder performed well for both healthy and stroke populations. As movement smoothness decreased, decoding performance decreased for the stroke population.

CONCLUSION

The proposed method is capable of simultaneously and continuously estimating multi-joint movements of the human arm in real-time by characterizing the nonlinear mappings between muscle activity and kinematic signals based on linear regression.

SIGNIFICANCE

This may prove useful in developing myoelectric controlled exoskeletons for motor rehabilitation of neurological disorders.

A Robotic Platform for 3D Forelimb Rehabilitation with Rats

In an attempt to promote greater functional recovery after spinal cord injury, researchers have begun exploring combinatorial treatments, such as robotic rehabilitation combined with stem cell transplantation. Since these treatment methods are in their nascent stages, rodent models have been proposed for initial investigations. Robots have been built for locomotion rehabilitation and planar forelimb reach and grasp assessment with rodents; however, a robotic platform suitable for three-dimensional movement rehabilitation of the rodent forelimb has not yet been developed. In this paper, a novel three degree of freedom robotic manipulator for automated forelimb rehabilitation combined with stem cell transplantation after cervical spinal cord injury with rats is proposed. The robot interfaces with a rat in an end-effector manner, measuring and interacting with the forelimb in the 3D Cartesian space. In this work, we trained two rats through behavioral shaping to actively interact with the device during two robot control modes. This work provides preliminary investigations into the feasibility of 3D forelimb rehabilitation with rats, which could be translated as a paradigm for combinatorial treatments after spinal cord injury in a controlled manner.

Ergodicity Reveals Assistance and Learning from Physical Human-Robot Interaction

This paper applies information theoretic principles to the investigation of physical human-robot interaction. Drawing from the study of human perception and neural encoding, information theoretic approaches offer a perspective that enables quantitatively interpreting the body as an information channel, and bodily motion as an information-carrying signal. We show that ergodicity, which can be interpreted as the degree to which a trajectory encodes information about a task, correctly predicts changes due to reduction of a person's existing deficit or the addition of algorithmic assistance. The measure also captures changes from training with robotic assistance. Other common measures for assessment failed to capture at least one of these effects. This information-based interpretation of motion can be applied broadly, in the evaluation and design of human-machine interactions, in learning by demonstration paradigms, or in human motion analysis.

Comparative study of actuation systems for portable upper limb exoskeletons

During the last two decades, a large variety of upper limb exoskeletons have been developed. Out of these, majority are platform based systems which might be the reason for not being widely adopted for post-stroke rehabilitation. Despite the potential benefits of platform-based exoskeletons as being rugged and reliable, stroke patients prefer to have a portable and user-friendly device that they can take home. However, the types of actuator as well as the actuation mechanism used in the exoskeleton are the inhibiting factors why portable exoskeletons are mostly non-existent for patient use. This paper presents a quantitative analysis of the actuation systems available for developing portable upper arm exoskeletons with their specifications. Finally, it has been concluded from this research that there are not many stand-alone arm exoskeletons which can provide all forms of rehabilitation, therefore, a generic solution has been proposed as the rehabilitation strategy to get best out of the portable arm exoskeletons.

Dynamic Modeling and Interactive Performance of PARM: A Parallel Upper-Limb Rehabilitation Robot Using Impedance Control for Patients after Stroke

The robot-assisted therapy has been demonstrated to be effective in the improvements of limb function and even activities of daily living for patients after stroke. This paper presents an interactive upper-limb rehabilitation robot with a parallel mechanism and an isometric screen embedded in the platform to display trajectories. In the dynamic modeling for impedance control, the effects of friction and inertia are reduced by introducing the principle of virtual work and derivative of Jacobian matrix. To achieve the assist-as-needed impedance control for arbitrary trajectories, the strategy based on orthogonal deviations is proposed. Simulations and experiments were performed to validate the dynamic modeling and impedance control. Besides, to investigate the influence of the impedance in practice, a subject participated in experiments and performed two types of movements with the robot, that is, rectilinear and circular movements, under four conditions, that is, with/without resistance or impedance, respectively. The results showed that the impedance and resistance affected both mean absolute error and standard deviation of movements and also demonstrated the significant differences between movements with/without impedance and resistance (p < 0.001). Furthermore, the error patterns were discussed, which suggested that the impedance environment was capable of alleviating movement deviations by compensating the synergetic inadequacy between the shoulder and elbow joints.

EMG-Based Continuous and Simultaneous Estimation of Arm Kinematics in Able-Bodied Individuals and Stroke Survivors

Among the potential biological signals for human-machine interactions (brain, nerve, and muscle signals), electromyography (EMG) widely used in clinical setting can be obtained non-invasively as motor commands to control movements. The aim of this study was to develop a model for continuous and simultaneous decoding of multi-joint dynamic arm movements based on multi-channel surface EMG signals crossing the joints, leading to application of myoelectrically controlled exoskeleton robots for upper-limb rehabilitation. Twenty subjects were recruited for this study including 10 stroke subjects and 10 able-bodied subjects. The subjects performed free arm reaching movements in the horizontal plane with an exoskeleton robot. The shoulder, elbow and wrist movements and surface EMG signals from six muscles crossing the three joints were recorded. A non-linear autoregressive exogenous (NARX) model was developed to continuously decode the shoulder, elbow and wrist movements based solely on the EMG signals. The shoulder, elbow and wrist movements were decoded accurately based only on the EMG inputs in all the subjects, with the variance accounted for (VAF) > 98% for all three joints. The proposed approach is capable of simultaneously and continuously decoding multi-joint movements of the human arm by taking into account the non-linear mappings between the muscle EMGs and joint movements, which may provide less effortful control of robotic exoskeletons for rehabilitation training of individuals with neurological disorders and arm impairment.

Mechanical design of EFW Exo II: A hybrid exoskeleton for elbow-forearm-wrist rehabilitation

The use of rehabilitation exoskeleton has become an important means for the treatment of stroke patients. A hybrid exoskeleton named EFW Exo II is developed for the motor function rehabilitation of elbow, forearm and wrist. The EFW Exo II is based on a parallel 2-URR/RRS mechanism and a serial R mechanism. It could fit both left and right arms for the symmetrical and open structure, and the distance between the elbow and wrist could automatically adjust for different forearm length. Details of the mechanical design are introduced. Brushless DC servo motors with planetary gear reducer are used as the actuators of the exoskeleton. Gear drive and belt drive are used for power transmission. A three dimensional force sensor is mounted in the handle to regulate the interaction between the exoskeleton and patient. The EFW Exo II can realize rehabilitation exercise for each joint and the ranges of motion meet the rehabilitation demands of daily living.

Effects of Assist-As-Needed Upper Extremity Robotic Therapy after Incomplete Spinal Cord Injury: A Parallel-Group Controlled Trial

BACKGROUND

Robotic rehabilitation of the upper limb following neurological injury has been supported through several large clinical studies for individuals with chronic stroke. The application of robotic rehabilitation to the treatment of other neurological injuries is less developed, despite indications that strategies successful for restoration of motor capability following stroke may benefit individuals with incomplete spinal cord injury (SCI) as well. Although recent studies suggest that robot-aided rehabilitation might be beneficial after incomplete SCI, it is still unclear what type of robot-aided intervention contributes to motor recovery.

METHODS

We developed a novel assist-as-needed (AAN) robotic controller to adjust challenge and robotic assistance continuously during rehabilitation therapy delivered via an upper extremity exoskeleton, the MAHI Exo-II, to train independent elbow and wrist joint movements. We further enrolled seventeen patients with incomplete spinal cord injury (AIS C and D levels) in a parallel-group balanced controlled trial to test the efficacy of the AAN controller, compared to a subject-triggered (ST) controller that does not adjust assistance or challenge levels continuously during therapy. The conducted study is a stage two, development-of-concept pilot study.

RESULTS

We validated the AAN controller in its capability of modulating assistance and challenge during therapy via analysis of longitudinal robotic metrics. For the selected primary outcome measure, the pre-post difference in ARAT score, no statistically significant change was measured in either group of subjects. Ancillary analysis of secondary outcome measures obtained via robotic testing indicates gradual improvement in movement quality during the therapy program in both groups, with the AAN controller affording greater increases in movement quality over the ST controller.

CONCLUSION

The present study demonstrates feasibility of subject-adaptive robotic therapy after incomplete spinal cord injury, but does not demonstrate gains in arm function occurring as a result of the robot-assisted rehabilitation program, nor differential gains obtained as a result of the developed AAN controller. Further research is warranted to better quantify the recovery potential provided by AAN control strategies for robotic rehabilitation of the upper limb following incomplete SCI. ClinicalTrials.gov registration number: NCT02803255.

A preliminary investigation into the design of pressure cushions and their potential applications for forearm robotic orthoses

BACKGROUND

Load cells are often used in rehabilitation robotics to monitor human-robot interaction. While load cells are accurate and suitable for the stationary end-point robots used in rehabilitation hospitals, their cost and inability to conform to the shape of the body hinder their application in developing affordable and wearable robotic orthoses for assisting individuals in the activities of daily living. This exploratory work investigates the possibility of using an alternative technology, namely compliant polymeric air cushions, to measure interaction forces between the user and a wearable rigid structure.

METHODS

A polymeric air cushion was designed, analyzed using a finite element model (FEM), and tested using a bench-top characterization system. The cushions underwent repeatability testing, and signal delay testing from a step response while increasing the length of the cushion's tubes. Subsequently, a 3D printed wrist brace prototype was integrated with six polymeric air cushions and tested in static conditions where a volunteer exerted isometric pronation/supination torque and forces in vertical and horizontal directions. The load measured by integrating data recorded by the six sensors was compared with force data measured by a high quality load cell and torque sensor.

RESULTS

The FEM and experimental data comparison was within the error bounds of the external differential pressure sensor used to monitor the pressure inside the cushion. The ratio obtained experimentally between the pressure inside the pressure cushion and the 8 N applied load deviated by only 1.28% from the FEM. A drift smaller than 1% was observed over 10 cycles. The rise times of the cushion under an 8 N step response for a 0.46, 1.03, and 2.02 m length tube was 0.45, 0.39, and 0.37 s. Tests with the wrist brace showed a moderate root mean square error (RMSE) between the force estimated by the pressure cushions and the external load cells. Specifically, the RMSE was 13 mNm, 500 mN, and 1.24 N for forearm pronation/supination torque, vertical force, and horizontal force, respectively.

CONCLUSIONS

The use of compliant pressure cushions was shown to be promising for monitoring interaction forces between the forearm and a rigid brace. This work lays the foundation for the future design of an array of pressure cushions for robotic orthoses. Future research should also investigate the compatibility of these polymeric cushions for data acquisition during functional magnetic resonance imaging in shielded rooms.

Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects

Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This paper implements the concept of a modular and reconfigurable robot, reducing its cost and size by adopting different therapeutic end effectors for different training movements using a single robot. The challenge is to increase the robot's portability and identify appropriate kinds of modular tools and configurations. Because literature on the effectiveness of this kind of rehabilitation robot is still scarce, this paper presents the design of a portable and reconfigurable rehabilitation robot and describes its use with a group of post-stroke patients for wrist and forearm training. Seven stroke subjects received training using a reconfigurable robot for 30 sessions, lasting 30 min per session. Post-training, statistical analysis showed significant improvement of 3.29 points (16.20%, p = 0.027) on the Fugl-Meyer assessment scale for forearm and wrist components. Significant improvement of active range of motion was detected in both pronation-supination (75.59%, p = 0.018) and wrist flexion-extension (56.12%, p = 0.018) after the training. These preliminary results demonstrate that the developed reconfigurable robot could improve subjects' wrist and forearm movement.

Robot-assisted assessment of wrist proprioception: does wrist proprioceptive acuity follow Weber's law?

Proprioception is essential for planning and controlling limb posture and movement. In our recent work, we introduced a standardized robot-aided method for measuring proprioceptive discrimination thresholds at the wrist to obtain reliable and accurate measures of proprioceptive acuity. Weber's law defines discrimination thresholds as a constant ratio between the just noticeable difference and the reference or standard stimulus. Reporting Weber's fractions thus provides the possibility of comparing results with the reports of others collected worldwide. This work aims to determine that Weber's Law holds for proprioceptive discrimination thresholds and to provide Weber's fraction for wrist joint proprioception. To this end, eight healthy subjects experienced two passive wrist movements of different amplitude and verbally indicated which was larger. An adaptive psychophysical procedure established the amplitude of the largest stimulus according to participants' responses. This comparison stimulus was then compared to a standard stimulus amplitude of 10°, 20°, 30° or 40°. The discrimination thresholds for each standard stimulus were established at the 75% correct response level. The obtained thresholds followed Weber's Law indicating that larger amplitudes were associated with higher discrimination thresholds. Based on a linear regression function the overall Weber's fraction, defined as the slope of the line, was computed to be 0.09. This result expands the present limited knowledge on wrist proprioception showing that its proprioceptive acuity follows Weber's law.

A Simulation Framework for Virtual Prototyping of Robotic Exoskeletons

A number of robotic exoskeletons are being developed to provide rehabilitation interventions for those with movement disabilities. We present a systematic framework that allows for virtual prototyping (i.e., design, control, and experimentation (i.e. design, control, and experimentation) of robotic exoskeletons. The framework merges computational musculoskeletal analyses with simulation-based design techniques which allows for exoskeleton design and control algorithm optimization. We introduce biomechanical, morphological, and controller measures to optimize the exoskeleton performance. A major advantage of the framework is that it provides a platform for carrying out hypothesis-driven virtual experiments to quantify device performance and rehabilitation progress. To illustrate the efficacy of the framework, we present a case study wherein the design and analysis of an index finger exoskeleton is carried out using the proposed framework.

Kinesthetic Feedback During 2DOF Wrist Movements via a Novel MR-Compatible Robot

We demonstrate the interaction control capabilities of the MR-SoftWrist, a novel MR-compatible robot capable of applying accurate kinesthetic feedback to wrist pointing movements executed during fMRI. The MR-SoftWrist, based on a novel design that combines parallel piezoelectric actuation with compliant force feedback, is capable of delivering 1.5 N [Formula: see text] of torque to the wrist of an interacting subject about the flexion/extension and radial/ulnar deviation axes. The robot workspace, defined by admissible wrist rotation angles, fully includes a circle with a 20 deg radius. Via dynamic characterization, we demonstrate capability for transparent operation with low (10% of maximum torque output) backdrivability torques at nominal speeds. Moreover, we demonstrate a 5.5 Hz stiffness control bandwidth for a 14 dB range of virtual stiffness values, corresponding to 25%-125% of the device's physical reflected stiffness in the nominal configuration. We finally validate the possibility of operation during fMRI via a case study involving one healthy subject. Our validation experiment demonstrates the capability of the device to apply kinesthetic feedback to elicit distinguishable kinetic and neural responses without significant degradation of image quality or task-induced head movements. With this study, we demonstrate the feasibility of MR-compatible devices like the MR-SoftWrist to be used in support of motor control experiments investigating wrist pointing under robot-applied force fields. Such future studies may elucidate fundamental neural mechanisms enabling robot-assisted motor skill learning, which is crucial for robot-aided neurorehabilitation.

Development of a four-channel haptic system for remote assessment of patients with impaired hands

Haptic devices have proven effective in stimulating proprioceptive sensing in post-stroke patients. In this work, pre-existing devices were used together in a remote environment for the teleassessment of impaired hands. A four-channel bilateral control system in the presence of large and variable time delay is proposed as a proof of concept. Time delay is managed with a novel communication disturbance observer (CDOB). The system also employed a scaling down compensation value (SDCV) for the CDOB. The proposed control system was tested successfully in bilateral haptic interaction, simulating a remote motor and functional evaluation of patients' hands, guaranteeing safe and stable interaction, even in the presence of large network delays.

A structured overview of trends and technologies used in dynamic hand orthoses

The development of dynamic hand orthoses is a fast-growing field of research and has resulted in many different devices. A large and diverse solution space is formed by the various mechatronic components which are used in these devices. They are the result of making complex design choices within the constraints imposed by the application, the environment and the patient's individual needs. Several review studies exist that cover the details of specific disciplines which play a part in the developmental cycle. However, a general collection of all endeavors around the world and a structured overview of the solution space which integrates these disciplines is missing. In this study, a total of 165 individual dynamic hand orthoses were collected and their mechatronic components were categorized into a framework with a signal, energy and mechanical domain. Its hierarchical structure allows it to reach out towards the different disciplines while connecting them with common properties. Additionally, available arguments behind design choices were collected and related to the trends in the solution space. As a result, a comprehensive overview of the used mechatronic components in dynamic hand orthoses is presented.

In Vivo Estimation of Human Forearm and Wrist Dynamic Properties

It is important to estimate the 3 degree-of-freedom (DOF) impedance of human forearm and wrist (i.e., forearm prono-supination, and wrist flexion-extension and radial-ulnar deviation) in motor control and in the diagnosis of altered mechanical resistance following stroke. There is, however, a lack of methods to characterize 3 DOF impedance. Thus, we developed a reliable and accurate impedance estimation method, the distal internal model based impedance control (dIMBIC)-based method, to characterize the 3 DOF impedance, including cross-coupled terms between DOFs, for the first time. Its accuracy and reliability were experimentally validated using a robot with substantial nonlinear joint friction. The 3 DOF human forearm and wrist impedance of eight healthy subjects was reliably characterized, and its linear behavior was verified. Thus, the dIMBIC-based method can provide us with 3 DOF forearm and wrist impedance regardless of nonlinear robot joint friction. It is expected that, with the proposed method, the 3 DOF impedance estimation can promote motor control studies and complement the diagnosis of altered wrist and forearm resistance post-stroke by providing objective impedance estimates, including cross-coupled terms.

Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors

This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG)-based brain machine interface (BMI). Intent was inferred from movement related cortical potentials (MRCPs) measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II), to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: (1) an adaptive time window was used for extracting features during BMI calibration; (2) training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and (3) BMI predictions were gated by residual electromyography (EMG) activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR) = 62.7 ± 21.4% on day 4 and 67.1 ± 14.6% on day 5. The overall false positive rate (FPR) across subjects was 27.74 ± 37.46% on day 4 and 27.5 ± 35.64% on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10%). On average, motor intent was detected -367 ± 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration.

A Hands-Free Interface for Controlling Virtual Electric-Powered Wheelchairs

This paper focuses on how to provide mobility to people with motor impairments with the integration of robotics and wearable computing systems. The burden of learning to control powered mobility devices should not fall entirely on the people with disabilities. Instead, the system should be able to learn the user's movements. This requires learning the degrees of freedom of user movement, and mapping these degrees of freedom onto electric-powered wheelchair (EPW) controls. Such mapping cannot be static because in some cases users will eventually improve with practice. Our goal in this paper is to present a hands-free interface (HFI) that can be customized to the varying needs of EPW users with appropriate mapping between the users' degrees of freedom and EPW controls. EPW users with different impairment types must learn how to operate a wheelchair with their residual body motions. EPW interfaces are often customized to fit their needs. An HFI utilizes the signals generated by the user's voluntary shoulder and elbow movements and translates them into an EPW control scheme. We examine the correlation of kinematics that occur during moderately paced repetitive elbow and shoulder movements for a range of motion. The output of upper-limb movements (shoulder and elbows) was tested on six participants, and compared with an output of a precision position tracking (PPT) optical system for validation. We find strong correlations between the HFI signal counts and PPT optical system during different upper-limb movements (ranged from r = 0.86 to 0.94). We also tested the HFI performance in driving the EPW in a virtual reality environment on a spinal-cord-injured (SCI) patient. The results showed that the HFI was able to adapt and translate the residual mobility of the SCI patient into efficient control commands within a week's training. The results are encouraging for the development of more efficient HFIs, especially for wheelchair users.

Detecting movement intent from scalp EEG in a novel upper limb robotic rehabilitation system for stroke

Stroke can be a source of significant upper extremity dysfunction and affect the quality of life (QoL) in survivors. In this context, novel rehabilitation approaches employing robotic rehabilitation devices combined with brain-machine interfaces can greatly help in expediting functional recovery in these individuals by actively engaging the user during therapy. However, optimal training conditions and parameters for these novel therapeutic systems are still unknown. Here, we present preliminary findings demonstrating successful movement intent detection from scalp electroencephalography (EEG) during robotic rehabilitation using the MAHI Exo-II in an individual with hemiparesis following stroke. These findings have strong clinical implications for the development of closed-loop brain-machine interfaces to robotic rehabilitation systems.