Soft Robotics to Enhance Upper Limb Endurance in Individuals with Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disorder that affects the central nervous system and can result in various symptoms, including muscle weakness, spasticity, and fatigue, ultimately leading to the deterioration of the musculoskeletal system. However, in recent years, exosuits have emerged as a game-changing solution to assist individuals with MS during their daily activities. These lightweight and affordable wearable robotic devices have gained immense popularity. In our study, we assessed the performance of an elbow exosuit on eight individuals with MS using high-density electromyography to measure biceps muscle activity. The results demonstrated that our prototype significantly reduced muscle effort during both dynamic and isometric tasks while increasing the elbow range of motion. In addition, the exosuit effectively delayed the onset of muscle fatigue, enhancing endurance for people with MS and enabling them to perform heavy duty tasks for a longer period.

Combining FES and Exoskeletons in a Hybrid Haptic System for Enhancing VR Experience

Robotic technology and functional electrical stimulation (FES) have emerged as highly effective rehabilitative techniques for individuals with neuromuscular diseases, showcasting their ability to restore motor functions. Within the proposed study, we developed and tested a new hybrid controller combining an upper-limb exoskeleton with FES to enhance haptic feedback when performing task-oriented and bimanual movement, like pick-and-place, in a virtual environment. We investigated the performance of the proposed approach on eight unimpaired participants providing haptic feedback either only by the exoskeleton or by the hybrid system. The hybrid control presents two different modalities, assistive and resistive, to modulate the perception of the load. FES intensity is calibrated to the subjects' biomechanical properties and it is adjusted in real-time according to the real-time motion of the upper limbs. Experimental results highlighted the ability of the hybrid control to improve kinematic performance: in both hybrid modalities subjects reduced the target matching error(values between 0.048±0.007 m and 0.06±0.006 m) without affecting the normal motion smoothness (SPARC values in the hybrid conditions range from -2.58±0.12 to -3.30±0.13). Moreover, the resistive approach resulted in greater metabolic consumption (1.04±0.03 W/kg), indicating a more realistic experience of lifting a virtual object through FES that increased the perceived weight. The innovation in our hybrid control relies on the modulation of muscular activation during manipulation tasks, which could be a promising approach in the clinical treatment of neuromuscular diseases.

A robot-aided visuomotor wrist training induces motor and proprioceptive learning that transfers to the untrained ipsilateral elbow

BACKGROUND

Learning of a visuomotor task not only leads to changes in motor performance but also improves proprioceptive function of the trained joint/limb system. Such sensorimotor learning may show intra-joint transfer that is observable at a previously untrained degrees of freedom of the trained joint.

OBJECTIVE

Here, we examined if and to what extent such learning transfers to neighboring joints of the same limb and whether such transfer is observable in the motor as well as in the proprioceptive domain. Documenting such intra-limb transfer of sensorimotor learning holds promise for the neurorehabilitation of an impaired joint by training the neighboring joints.

METHODS

Using a robotic exoskeleton, 15 healthy young adults (18-35 years) underwent a visuomotor training that required them to make continuous, increasingly precise, small amplitude wrist movements. Wrist and elbow position sense just-noticeable-difference (JND) thresholds and spatial movement accuracy error (MAE) at wrist and elbow in an untrained pointing task were assessed before and immediately after, as well as 24 h after training.

RESULTS

First, all participants showed evidence of proprioceptive and motor learning in both trained and untrained joints. The mean JND threshold decreased significantly by 30% in trained wrist (M: 1.26° to 0.88°) and by 35% in untrained elbow (M: 1.96° to 1.28°). Second, mean MAE in untrained pointing task reduced by 20% in trained wrist and the untrained elbow. Third, after 24 h the gains in proprioceptive learning persisted at both joints, while transferred motor learning gains had decayed to such extent that they were no longer significant at the group level.

CONCLUSION

Our findings document that a one-time sensorimotor training induces rapid learning gains in proprioceptive acuity and untrained sensorimotor performance at the practiced joint. Importantly, these gains transfer almost fully to the neighboring, proximal joint/limb system.

Improving Walking Assistance Efficiency in Real-World Scenarios with Soft Exosuits Using Locomotion Mode Detection

The use of portable and lightweight wearable assistive devices can improve wearer locomotion efficiency by reducing the metabolic cost of walking. To achieve this goal, assistive technologies must adapt to different locomotion modes to optimize walking assistance. In this work, we developed a novel control strategy for an underactuated soft exosuit featuring a single actuator to assist bilateral hip flexion, which utilized inertial measurement units (IMUs) to discriminate between three different locomotion modes: walking up/down stairs or on level ground. Walking assistance was adjusted in real-time to maximize the assistance provided to the user. In order to preliminary test the effectiveness of this control strategy, four healthy subjects performed a walking task with the exosuit disabled (Exo Off) and enabled (Exo On). Results showed that the kinematics-based IMU classification strategy achieved an overall accuracy exceeding 95% across the three-movement patterns. Subjects were able to save an average of 10.1% on walking energy expenditure with assistance from the wearable device. This work contributes to the development of compact, high-performance lower limb assistive technologies and their development in practical applications.

Bimanual Motor Strategies and Handedness Role in Human-Robot Haptic Interaction

Bimanual object manipulation involves using both hands to interact with objects in the environment, and the process requires the central nervous system to process sensory feedback and translate it into motor commands. Although there have been significant advancements in haptics and robotics, the kinematic strategies involved in bimanual coupled tasks are still not fully understood. This study aimed to investigate the dynamic interaction between hands during the manipulation of a shared object using two impedance-controlled exoskeletons programmed to simulate bimanual coupled manipulation of virtual objects. Twenty-six participants (right-handed and left-handed) were asked to use both hands to grab and place simulated objects in specific locations. The virtual objects were rendered with four different dynamic properties, affecting the manipulation strategies used to complete the tasks. The results showed that force asymmetries were related to movement direction and handedness preference, with right-handers exhibiting asymmetries related to movement direction and left-handers showing better control of the force applied between their hands. This is possibly due to their constant exposure to objects designed for right-handed use. Additionally, the haptic properties of the virtual objects influenced task performance in terms of timing and failure for all participants. This study demonstrates the potential of advanced technologies to provide realistic simulations of multi-joint movements involving the entire upper extremities. The findings have implications for the development of training programs for bimanual object manipulation tasks and the design of virtual environments that can enhance the learning process.

Adaptive Hybrid FES-Force Controller for Arm Exosuit

Patients suffering from neuromuscular diseases experience motor disabilities which hinder their independence during activities of daily living (ADLs). For such impaired subjects, robotic devices and Functional Electrical Stimulation (FES) are technologies commonly used to rehabilitate lost functions. Nevertheless, both systems present some limitations, and merging FES and robots in Hybrid Robotic Rehabilitation Systems allows to overcome these boundaries. Here we propose for the first time a hybrid cooperative controller involving FES and a soft wearable upper arm exosuit to rehabilitate elbow movements. We tested the designed hybrid controller on six healthy participants. The results showed how the proposed hybrid controller allowed the wearers to perform flexion movements with no significant decrease in accuracy and precision with respect to the exosuit alone, while significantly decreasing the fatigue level by about 63% and delaying its onset with respect to the FES action alone.

A Comprehensive Framework for the Modelling of Cartesian Force Output in Human Limbs

Neuromuscular functional electrical stimulation represents a valid technique for functional rehabilitation or, in the form of a neuroprosthesis, for the assistance of neurological patients. However, the selected stimulation of single muscles through surface electrodes remains challenging particularly for the upper extremity. In this paper, we present the MyoCeption, a comprehensive setup, which enables intuitive modeling of the user's musculoskeletal system, as well as proportional stimulation of the muscles with 16-bit resolution through up to 10 channels. The system can be used to provide open-loop force control, which, if coupled with an adequate body tracking system, can be used to implement an impedance control where the control loop is closed around the body posture. The system is completely self-contained and can be used in a wide array of scenarios, from rehabilitation to VR to teleoperation. Here, the MyoCeption's control environment has been experimentally validated through comparison with a third-party simulation suite. The results indicate that the musculoskeletal model used for the MyoCeption provides muscle geometries that are qualitatively similar to those computed in the baseline model.

Soft, lightweight wearable robots to support the upper limb in activities of daily living: a feasibility study on chronic stroke patients

Stroke can be a devastating condition that impairs the upper limb and reduces mobility. Wearable robots can aid impaired users by supporting performance of Activities of Daily Living (ADLs). In the past decade, soft devices have become popular due to their inherent malleable and low-weight properties that makes them generally safer and more ergonomic. In this study, we present an improved version of our previously developed gravity-compensating upper limb exosuit and introduce a novel hand exoskeleton. The latter uses 3D-printed structures that are attached to the back of the fingers which prevent undesired hyperextension of joints. We explored the feasibility of using this integrated system in a sample of 10 chronic stroke patients who performed 10 ADLs.We observed a significant reduction of 30.3 ± 3.5% (mean ± standard error), 31.2 ± 3.2% and 14.0 ± 5.1% in the mean muscular activity of the Biceps Brachii (BB), Anterior Deltoid (AD) and Extensor Digitorum Communis muscles, respectively. Additionally, we observed a reduction of 14.0 ± 11.5%, 14.7 ± 6.9% and 12.8 ± 4.4% in the coactivation of the pairs of muscles BB and Triceps Brachii (TB), BB and AD, and TB and Pectoralis Major (PM), respectively, typically associated to pathological muscular synergies, without significant degradation of healthy muscular coactivation. There was also a significant increase of elbow flexion angle (12.1±1.5°). These results further cement the potential of using lightweight wearable devices to assist impaired users.

Evaluating Viscoelastic Properties of the Wrist Joint During External Perturbations: Influence of Velocity, Grip, and Handedness

In this study, we designed a robot-based method to compute a mechanical impedance model that could extract the viscoelastic properties of the wrist joint. Thirteen subjects participated in the experiment, testing both dominant and nondominant hands. Specifically, the robotic device delivered position-controlled disturbances in the flexion-extension degree of freedom of the wrist. The external perturbations were characterized by small amplitudes and fast velocities, causing rotation at the wrist joint. The viscoelastic characteristics of the mechanical impedance of the joint were evaluated from the wrist kinematics and corresponding torques. Since the protocol used position inputs to determine changes in mean wrist torque, a detailed analysis of wrist joint dynamics could be made. The scientific question was whether and how these mechanical features changed with various grip demands and perturbation velocities. Nine experimental conditions were tested for each hand, given by the combination of three velocity perturbations (fast, medium, and slow) and three hand grip conditions [self-selected grip, medium and high grip force, as percentage of the maximum voluntary contraction (MVC)]. Throughout the experiments, electromyographic signals of the extensor carpi radialis (ECR) and the flexor carpi radialis (FCR) were recorded. The novelty of this work included a custom-made soft grip sensor, wrapped around the robotic handle, to accurately quantify the grip force exerted by the subjects during experimentation. Damping parameters were in the range of measurements from prior studies and consistent among the different experimental conditions. Stiffness was independent of both direction and velocity of perturbations and increased with increasing grip demand. Both damping and stiffness were not different between the dominant and nondominant hands. These results are crucial to improving our knowledge of the mechanical characteristics of the wrist, and how grip demands influence these properties. This study is the foundation for future work on how mechanical characteristics of the wrist are affected in pathological conditions.

Efficacy of wrist robot-aided orthopedic rehabilitation: a randomized controlled trial

Background

In recent years, many studies focused on the use of robotic devices for both the assessment and the neuro-motor reeducation of upper limb in subjects after stroke, spinal cord injuries or affected by neurological disorders. Contrarily, it is still hard to find examples of robot-aided assessment and rehabilitation after traumatic injuries in the orthopedic field. However, those benefits related to the use of robotic devices are expected also in orthopedic functional reeducation.

Methods

After a wrist injury occurred at their workplace, wrist functionality of twenty-three subjects was evaluated through a robot-based assessment and clinical measures (Patient Rated Wrist Evaluation, Jebsen-Taylor and Jamar Test), before and after a 3-week long rehabilitative treatment. Subjects were randomized in two groups: while the control group (n = 13) underwent a traditional rehabilitative protocol, the experimental group (n = 10) was treated replacing traditional exercises with robot-aided ones.

Results

Functionality, assessed through the function subscale of PRWE scale, improved in both groups (experimental p = 0.016; control p < 0.001) and was comparable between groups, both pre (U = 45.5, p = 0.355) and post (U = 47, p = 0.597) treatment. Additionally, even though groups’ performance during the robotic assessment was comparable before the treatment (U = 36, p = 0.077), after rehabilitation the experimental group presented better results than the control one (U = 26, p = 0.015).

Conclusions

This work can be considered a starting point for introducing the use of robotic devices in the orthopedic field. The robot-aided rehabilitative treatment was effective and comparable to the traditional one. Preserving efficacy and safety conditions, a systematic use of these devices could lead to decrease human therapists’ effort, increase repeatability and accuracy of assessments, and promote subject’s engagement and voluntary participation. Trial Registration ClinicalTrial.gov ID: NCT04739644. Registered on February 4, 2021—Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/study/NCT04739644.

A soft, synergy-based robotic glove for grasping assistance

This paper presents a soft, tendon-driven, robotic glove designed to augment grasp capability and provide rehabilitation assistance for postspinal cord injury patients. The basis of the design is an underactuation approach utilizing postural synergies of the hand to support a large variety of grasps with a single actuator. The glove is lightweight, easy to don, and generates sufficient hand closing force to assist with activities of daily living. Device efficiency was examined through a characterization of the power transmission elements, and output force production was observed to be linear in both cylindrical and pinch grasp configurations. We further show that, as a result of the synergy-inspired actuation strategy, the glove only slightly alters the distribution of forces across the fingers, compared to a natural, unassisted grasping pattern. Finally, a preliminary case study was conducted using a participant suffering from an incomplete spinal cord injury (C7). It was found that through the use of the glove, the participant was able to achieve a 50% performance improvement (from four to six blocks) in a standard Box and Block test.

A robot-aided visuomotor wrist training induces gains in proprioceptive and movement accuracy in the contralateral wrist

Proprioceptive training is a neurorehabilitation approach known to improve proprioceptive acuity and motor performance of a joint/limb system. Here, we examined if such learning transfers to the contralateral joints. Using a robotic exoskeleton, 15 healthy, right-handed adults (18-35 years) trained a visuomotor task that required making increasingly small wrist movements challenging proprioceptive function. Wrist position sense just-noticeable-difference thresholds (JND) and spatial movement accuracy error (MAE) in a wrist-pointing task that was not trained were assessed before and immediately as well as 24 h after training. The main results are: first, training reduced JND thresholds (- 27%) and MAE (- 33%) in the trained right wrist. Sensory and motor gains were observable 24 h after training. Second, in the untrained left wrist, mean JND significantly decreased (- 32%) at posttest. However, at retention the effect was no longer significant. Third, motor error at the untrained wrist declined slowly. Gains were not significant at posttest, but MAE was significantly reduced (- 27%) at retention. This study provides first evidence that proprioceptive-focused visuomotor training can induce proprioceptive and motor gains not only in the trained joint but also in the contralateral, homologous joint. We discuss the possible neurophysiological mechanism behind such sensorimotor transfer and its implications for neurorehabilitation.

Robotic Assessment of Wrist Proprioception During Kinaesthetic Perturbations: A Neuroergonomic Approach

Position sense refers to an aspect of proprioception crucial for motor control and learning. The onset of neurological diseases can damage such sensory afference, with consequent motor disorders dramatically reducing the associated recovery process. In regular clinical practice, assessment of proprioceptive deficits is run by means of clinical scales which do not provide quantitative measurements. However, existing robotic solutions usually do not involve multi-joint movements but are mostly applied to a single proximal or distal joint. The present work provides a testing paradigm for assessing proprioception during coordinated multi-joint distal movements and in presence of kinaesthetic perturbations: we evaluated healthy subjects' ability to match proprioceptive targets along two of the three wrist's degrees of freedom, flexion/extension and abduction/adduction. By introducing rotations along the pronation/supination axis not involved in the matching task, we tested two experimental conditions, which differed in terms of the temporal imposition of the external perturbation: in the first one, the disturbance was provided after the presentation of the proprioceptive target, while in the second one, the rotation of the pronation/ supination axis was imposed during the proprioceptive target presentation. We investigated if (i) the amplitude of the perturbation along the pronation/supination would lead to proprioceptive miscalibration; (ii) the encoding of proprioceptive target, would be influenced by the presentation sequence between the target itself and the rotational disturbance. Eighteen participants were tested by means of a haptic neuroergonomic wrist device: our findings provided evidence that the order of disturbance presentation does not alter proprioceptive acuity. Yet, a further effect has been noticed: proprioception is highly anisotropic and dependent on perturbation amplitude. Unexpectedly, the configuration of the forearm highly influences sensory feedbacks, and significantly alters subjects' performance in matching the proprioceptive targets, defining portions of the wrist workspace where kinaesthetic and proprioceptive acuity are more sensitive. This finding may suggest solutions and applications in multiple fields: from general haptics where, knowing how wrist configuration influences proprioception, might suggest new neuroergonomic solutions in device design, to clinical evaluation after neurological damage, where accurately assessing proprioceptive deficits can dramatically complement regular therapy for a better prediction of the recovery path.

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.

Relationship Between Muscular Activity and Assistance Magnitude for a Myoelectric Model Based Controlled Exosuit

The growing field of soft wearable exosuits, is gradually gaining terrain and proposing new complementary solutions in assistive technology, with several advantages in terms of portability, kinematic transparency, ergonomics, and metabolic efficiency. Those are palatable benefits that can be exploited in several applications, ranging from strength and resistance augmentation in industrial scenarios, to assistance or rehabilitation for people with motor impairments. To be effective, however, an exosuit needs to synergistically work with the human and matching specific requirements in terms of both movements kinematics and dynamics: an accurate and timely intention-detection strategy is the paramount aspect which assume a fundamental importance for acceptance and usability of such technology. We previously proposed to tackle this challenge by means of a model-based myoelectric controller, treating the exosuit as an external muscular layer in parallel to the human biomechanics and as such, controlled by the same efferent motor commands of biological muscles. However, previous studies that used classical control methods, demonstrated that the level of device's intervention and effectiveness of task completion are not linearly related: therefore, using a newly implemented EMG-driven controller, we isolated and characterized the relationship between assistance magnitude and muscular benefits, with the goal to find a range of assistance which could make the controller versatile for both dynamic and static tasks. Ten healthy participants performed the experiment resembling functional daily activities living in separate assistance conditions: without the device's active support and with different levels of intervention by the exosuit. Higher assistance levels resulted in larger reductions in the activity of the muscles augmented by the suit actuation and a good performance in motion accuracy, despite involving a decrease of the movement velocities, with respect to the no assistance condition. Moreover, increasing torque magnitude by the exosuit resulted in a significant reduction in the biological torque at the elbow joint and in a progressive effective delay in the onset of muscular fatigue. Thus, contrarily to classical force and proportional myoelectric schemes, the implementation of an opportunely tailored EMG-driven model based controller affords to naturally match user's intention detection and provide an assistance level working symbiotically with the human biomechanics.

Assessment of human wrist rigidity and pain in post-traumatic patients

The aim of this work is to present a novel robot-based method to assess the sources of a lack of functionality in patients with recent traumatic wrist injuries. Post-traumatic patients experience limited range of motion as well as strength and proprioceptive deficits. These dysfunctions are related to different complications that usually follow the injuries: pain, increased rigidity, lack of movement fluency and loss of stability could arise differently, according to the severity, site and kind of lesion. Their quantitative evaluation could be essential to target rehabilitation treatments to the specific problem and to optimize and speed up the functional recovery. The use of robotic devices for assessment not only ensures objectivity and repeatability, but could also help to estimate the goodness of the evaluation itself, in terms of reliability and patient's engagement. Ten subjects with different types of wrist injuries were enrolled in this study and required to perform passive robot-guided reaching movements. Forces and angular positions were used to evaluate subject's range of motion, rigidity and pain that, considered together, allowed a comprehensive characterization of the level of healing and functionality achieved by each subject.

On the edge between soft and rigid: an assistive shoulder exoskeleton with hyper-redundant kinematics

In this paper, we present a prototype of an innovative portable shoulder exoskeleton for human assistance and augmentation. The device provides torques to flexion/extension movements of the shoulder, compensating for gravitational forces, and is passively compliant along the remaining degrees of freedom letting the shoulder moving along them. The novelty of our system is a flexible link, made of a hyper-redundant passive structure, that avoids joint misalignment by adapting to the complex movements of the humerus head, similarly to a soft component. The flexible link is compliant to rotations around one axis but rigid around the other two axes, allowing transmission of flexion/extension torque but kinematically transparent along the remaining degrees of freedom. The device is light weight and allows to cover around the 82% of the shoulder flexion/extension range of motion. The exoskeleton was tested on a cohort of 5 healthy subjects, monitoring shoulder kinematics, interaction forces and acquiring the electromyography of three major muscles contributing to shoulder flexion. During both static postures and dynamic movements, assistance from the exoskeleton resulted in a significant reduction of muscular effort in the anterior (-32.2% in static, -25.3% in dynamic) and medial deltoid (56.9% in static, -49.6% in dynamic) and an average reduction of the biceps brachii.

IMU-based assistance modulation in upper limb soft wearable exosuits

Soft exosuits have advantages over their rigid counterparts in terms of portability, transparency and ergonomics. Our previous work has shown that a soft, fabric-based exosuit, actuated by an electric motor and a Bowden cable, reduced the muscular effort of the user when flexing the elbow. This previous exosuit used a gravity compensation algorithm with the assumption that the shoulder was adducted at the trunk. In this investigation, the shoulder elevation angle was incorporated into the gravity compensation control via inertial measurement units (IMUs). We assessed our updated gravity compensation model with four healthy, male subjects (age: $26.2 \pm 1.19$ years) who followed an elbow flexion reference trajectory which reached three amplitudes $(25^{\circ}, 50^{\circ}, 75^{\circ})$ and was repeated at three shoulder angles $(25^{\circ}, 50^{\circ}, 75^{\circ})$. To assess the performance of the exosuit; the smoothness, tracking accuracy and muscle activity were investigated during each motion. We found a reduction of biceps brachii activation (24.3%) in the powered condition compared to the unpowered condition. In addition, there was an improvement in kinematic smoothness (0.83%) and a reduction of tracking accuracy (26.5%) in the powered condition with respect to the unpowered condition. We can conclude that the updated gravity compensation algorithm has increased the number of supported movements by considering the shoulder elevation, which has improved the usability of the device.

Design and Validation of a Modular One-To-Many Actuator for a Soft Wearable Exosuit

The size, weight, and power consumption of soft wearable robots rapidly scale with their number of active degrees of freedom. While various underactuation strategies have been proposed, most of them impose hard constrains on the kinetics and kinematics of the device. Here we propose a paradigm to independently control multiple degrees of freedom using a set of modular components, all tapping power from a single motor. Each module consists of three electromagnetic clutches, controlled to convert a constant unidirectional motion in an arbitrary output trajectory. We detail the design and functioning principle of each module and propose an approach to control the velocity and position of its output. The device is characterized in free space and under loading conditions. Finally, we test the performance of the proposed actuation scheme to drive a soft exosuit for the elbow joint, comparing it with the performance obtained using a traditional DC motor and an unpowered-exosuit condition. The exosuit powered by our novel scheme reduces the biological torque required to move by an average of 46.2%, compared to the unpowered condition, but negatively affects movement smoothness. When compared to a DC motor, using the our paradigm slightly deteriorates performance. Despite the technical limitations of the current design, the method proposed in this paper is a promising way to design more portable wearable robots.

An LDA-Based Approach for Real-Time Simultaneous Classification of Movements Using Surface Electromyography

Myoelectric-based decoding strategies offer significant advantages in the areas of human-machine interactions because they are intuitive and require less cognitive effort from the users. However, a general drawback in using machine learning techniques for classification is that the decoder is limited to predicting only one movement at any instant and hence restricted to performing the motion in a sequential manner, whereas human motor control strategy involves simultaneous actuation of multiple degrees of freedom (DOFs) and is considered to be a natural and efficient way of performing tasks. Simultaneous decoding in the context of myoelectric-based movement control is a challenge that is being addressed recently and is increasingly popular. In this paper, we propose a novel classification strategy capable of decoding both the individual and combined movements, by collecting data from only the individual motions. Additionally, we exploit low-dimensional representation of the myoelectric signals using a supervised decomposition algorithm called linear discriminant analysis, to simplify the complexity of control and reduce computational cost. The performance of the decoding algorithm is tested in an online context for the two DOFs task comprising the hand and wrist movements. Results indicate an overall classification accuracy of 88.02% for both the individual and combined motions.

Physiological and kinematic effects of a soft exosuit on arm movements

BACKGROUND

Soft wearable robots (exosuits), being lightweight, ergonomic and low power-demanding, are attractive for a variety of applications, ranging from strength augmentation in industrial scenarios, to medical assistance for people with motor impairments. Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous design refinement.

METHODS

We present a novel wearable exosuit for assistance/augmentation of the elbow and introduce a controller that compensates for gravitational forces acting on the limb while allowing the suit to cooperatively move with its wearer. Eight healthy subjects wore the exosuit and performed elbow movements in two conditions: with assistance from the device (powered) and without assistance (unpowered). The test included a dynamic task, to evaluate the impact of the assistance on the kinematics and dynamics of human movement, and an isometric task, to assess its influence on the onset of muscular fatigue.

RESULTS

Powered movements showed a low but significant degradation in accuracy and smoothness when compared to the unpowered ones. The degradation in kinematics was accompanied by an average reduction of 59.20±5.58% (mean ± standard error) of the biological torque and 64.8±7.66% drop in muscular effort when the exosuit assisted its wearer. Furthermore, an analysis of the electromyographic signals of the biceps brachii during the isometric task revealed that the exosuit delays the onset of muscular fatigue.

CONCLUSIONS

The study examined the effects of an exosuit on the characteristics of human movements. The suit supports most of the power needed to move and reduces the effort that the subject needs to exert to counteract gravity in a static posture, delaying the onset of muscular fatigue. We interpret the decline in kinematic performance as a technical limitation of the current device. This work suggests that a powered exosuit can be a good candidate for industrial and clinical applications, where task efficiency and hardware transparency are paramount.

Quantitative assessment of motor functions post-stroke: Responsiveness of upper-extremity robotic measures and its task dependence

Technology aided measures offer a sensitive, accurate and time-efflcient approach for the assessment of sensorimotor function after neurological impairment compared to standard clinical assessments. This preliminary study investigated the relationship between task definition and its effect on robotic measures using a planar, two degree of freedom, robotic-manipulator (H-Man). Four chronic stroke participants (49.5±11.95 years, 2 Female, FMA: 37.5±13.96) and eight healthy control participants (26.25± 4.70 years, 2 Female) participated in the study. Motor functions were evaluated using line tracing and circle tracing tasks with dominant and nondominant hand of healthy and affected vs. non affected hand of stroke participants. The results show significant dependence of quantitative measures on investigated tasks.

3D-Structured Stretchable Strain Sensors for Out-of-Plane Force Detection

Stretchable strain sensors, as the soft mechanical interface, provide the key mechanical information of the systems for healthcare monitoring, rehabilitation assistance, soft exoskeletal devices, and soft robotics. Stretchable strain sensors based on 2D flat film have been widely developed to monitor the in-plane force applied within the plane where the sensor is placed. However, to comprehensively obtain the mechanical feedback, the capability to detect the out-of-plane force, caused by the interaction outside of the plane where the senor is located, is needed. Herein, a 3D-structured stretchable strain sensor is reported to monitor the out-of-plane force by employing 3D printing in conjunction with out-of-plane capillary force-assisted self-pinning of carbon nanotubes. The 3D-structured sensor possesses large stretchability, multistrain detection, and strain-direction recognition by one single sensor. It is demonstrated that out-of-plane forces induced by the air/fluid flow are reliably monitored and intricate flow details are clearly recorded. The development opens up for the exploration of next-generation 3D stretchable sensors for electronic skin and soft robotics.

Codification mechanisms of wrist position sense

Proprioceptive signals from cutaneous, joint, tendon and muscle receptors create the basis for bodily perception and are known to be essential for motor control. However, which are the mechanisms underlying the proprioceptive signals and which are the variables that affect them is still a matter of debate. In particular, what is worth to investigate is, namely, the codification of proprioceptive information related to pointing movements of the wrist towards kinesthetic targets. In this work we asked 10 healthy adults to perform with their wrist a robot-aided proprioceptive matching task, in which the starting position of the matching movements was shifted forward or backward, in order to ascertain to which extent such shifts cause target over/under estimation and how important is movement's length on task performance. Results indicate that accuracy and precision of performance are highly correlated with the starting position and targets tended to be undershot when the active matching movements were longer. Moreover, further analysis revealed a consistent decrement of movement speed for shorter movements and conversely, faster displacement in case of backward of starting position.

A robot-aided visuo-motor training that improves proprioception and spatial accuracy of untrained movement

Proprioceptive function can become enhanced during motor learning. Yet, we have incomplete knowledge to what extent proprioceptive function is trainable and how a training that enhances proprioception may influence performance in untrained motor skills. To address this knowledge gap, healthy young adults (N = 14) trained in a visuomotor task that required learners to make increasingly accurate wrist movements. Using a robotic exoskeleton coupled with a virtual visual environment, participants tilted a virtual table through continuous wrist flexion/extension movements with the goal to position a rolling ball on table into a target. With learning progress, the level of difficulty increased by altering the virtual ball mechanics and the gain between joint movement and ball velocity. Before and after training, wrist position sense acuity and spatial movement accuracy in an untrained, discrete wrist-pointing task was assessed using the same robot. All participants showed evidence of proprioceptive-motor learning. Mean position sense discrimination threshold improved by 34%. Wrist movement accuracy in the untrained pointing task improved by 27% in 13/14 participants. This demonstrates that a short sensorimotor training challenging proprioception can a) effectively enhance proprioceptive acuity and b) improve the accuracy of untrained movement. These findings provide a scientific basis for applying such somatosensory-based motor training to clinical populations with known proprioceptive dysfunction to enhance sensorimotor performance.

Proprioceptive assessment in clinical settings: Evaluation of joint position sense in upper limb post-stroke using a robotic manipulator

Proprioception is a critical component for motor functions and directly affects motor learning after neurological injuries. Conventional methods for its assessment are generally ordinal in nature and hence lack sensitivity. Robotic devices designed to promote sensorimotor learning can potentially provide quantitative precise, accurate, and reliable assessments of sensory impairments. In this paper, we investigate the clinical applicability and validity of using a planar 2 degrees of freedom robot to quantitatively assess proprioceptive deficits in post-stroke participants. Nine stroke survivors and nine healthy subjects participated in the study. Participants’ hand was passively moved to the target position guided by the H-Man robot (Criterion movement) and were asked to indicate during a second passive movement towards the same target (Matching movement) when they felt that they matched the target position. The assessment was carried out on a planar surface for movements in the forward and oblique directions in the contralateral and ipsilateral sides of the tested arm. The matching performance was evaluated in terms of error magnitude (absolute and signed) and its variability. Stroke patients showed higher variability in the estimation of the target position compared to the healthy participants. Further, an effect of target was found, with lower absolute errors in the contralateral side. Pairwise comparison between individual stroke participant and control participants showed significant proprioceptive deficits in two patients. The proposed assessment of passive joint position sense was inherently simple and all participants, regardless of motor impairment level, could complete it in less than 10 minutes. Therefore, the method can potentially be carried out to detect changes in proprioceptive deficits in clinical settings.

The Influence of External Forces on Wrist Proprioception

Proprioception combines information from cutaneous, joint, tendon, and muscle receptors for maintaining a reliable internal body image. However, it is still a matter of debate, in both neurophysiology and psychology, to what extent such body image is modified or distorted by a changing haptic environment. In particular, what is worth investigating is the contribution of external forces on our perception of body and joint configuration. The proprioceptive acuity of fifteen young participants was tested with a Joint Position Matching (JPM) task, performed with the dominant wrist under five different external forces, in order to understand to what extent they affect proprioceptive acuity. Results show that accuracy and precision in target matching do not change in a significant manner as a function of the loading condition, suggesting that the multi-sensory integration process is indeed capable of discriminating different sub-modalities of proprioception, namely the joint position sense and the sense of force. Furthermore, results indicate a preference for target undershooting when movements are performed in a viscous or high resistive force field, rather than passive or null fields in which subjects did not show any predominance for under/over estimation of their position.

The effects of age and amplitude on wrist proprioceptive acuity

This study examined wrist proprioception in a cross-sectional sample of 44 children aged between 8-to 14-years and a control group of 10 neurologically and physically healthy adults. Using a 3-degrees of freedom robotic device, participants performed an ipsilateral joint position matching task in which target amplitude (40% or 80% functional range of motion [fRoM]) and degrees-of-freedom (Flexion/Extension [FE], Radial/Ulnar deviation [RUD], Pronation/Supination [PS]) were manipulated. Results indicated that proprioceptive function became more accurate and consistent over the developmental spectrum, but that the ability to utilize proprioceptive feedback did not reach adult levels till the age of 10-11 years. Furthermore, proprioceptive acuity was influenced by target amplitude, such that movements were more accurate for the 80% fROM compared to the 40% fROM target for both the RUD and PS DoFs, independently of age. The present results provide critical information about the typical development of wrist proprioception that will enable clinicians to chart the course of development and dysfunction in neurological disorders in children, and help establish protocols for the robotic diagnosis and assessment of neurodevelopmental disorders.

Modular one-to-many clutchable actuator for a soft elbow exosuit

Exoskeletons have been developed for a wide range of applications, from the military to the medical field, with the aim of augmenting human performance or compensating for neuromuscular deficiencies. However, to empower the high number of degrees of freedom of the human body, they often employ a high number of motors, increasing the size, weight and power consumption of the system. We hereby present an actuation strategy to empower our elbow exosuit that adopts a single motor to drive multiple, independently actuated, degrees of freedom. This paradigm, known as One-to-many, is achieved using a modular design where each module comprises a clutchable mechanism that allows to convert a single directional motion from the prime mover to a selectable bidirectional output. Moreover, the mechanism has a locking feature that enables the wearer of the exoskeleton to hold a static load with a minimal power consumption. We present a simple controller for the clutchable unit based on a finite-state machine model, and evaluate its performance for varying input velocities. The system is shown to have a bandwidth of 1.5 Hz, sufficient for daily elbow movements, whilst retaining a compact design.

Position and stiffness modulation of a wrist haptic device using myoelectric interface

Modulation of stiffness provides a great deal of advantage in the way humans interact with the environment, and is very important in successfully performing activities of daily living. In the context of human-machine interactions, stiffness control could provide a safer interaction, especially when dealing with unpredictable environment. In this paper we propose a user-modulated stiffness and position control for the wrist flexion/extension degree of freedom while physically coupled to a haptic device. A virtual position tracking experiment in a varying external force field is designed in order to test the performance of the control strategy with and without co-contraction techniques. Tracking accuracy and smoothness of motion indicate better performance when subjects use co-contraction techniques, and the difference in the two types of experiment is also statistically significant.

A preliminary study for quantitative assessment of upper limb proprioception

Proprioception, or sense of position and movement of the body, strongly correlates with motor recovery of the hemiplegic arm. The evaluation of the awareness of the location of joints in space involves measuring the accuracy of joint-angle replication. Robotic devices allow an accurate manipulation of joint movements necessary to assess proprioceptive status. This study evaluated the proprioceptive performance of healthy subjects by mean of the H-Man, a planar robot designed for upper-limb rehabilitation to gather preliminary normative data for neurorehabilitation applications. Twelve participants were equally divided into Aged and Young groups and were asked to indicate when their dominant hand position matched a predefined target in the contralateral, sagittal and ipsilateral direction. Results indicated a better performance for movements towards the contralateral target in terms of both absolute and signed error while there was not a significant effect of age group. Error variability was not affected by the target location and participants' age. The present study established preliminary proprioceptive metrics that could assist in providing information about the normal range of proprioceptive acuity of healthy subjects of different age.

Robotic assessment of the contribution of motor commands to wrist position sense

Assessing joint position sense for rehabilitation after neurological injury provides a prognostic factor in recovery and long-term functional outcomes. A common method for testing joint position sense involves the active replication of a joint configuration presented via a passive movement. However, recent evidence showed how this sense is mediated by the centrally generated signals of motor command, such that movements produced volitionally may be coded differently from passive movements and accuracy may be different when matching targets presented actively. To verify this hypothesis we asked ten participants to actively replicate a target wrist angle with the help of a visual feedback in two conditions, which differed in the mode of target presentation: active (aaJPM) or passive (paJPM). The accuracy of target matching, directional bias and variability were analyzed, as well as speed and smoothness of the matching movement and criterion movement in the aaJPM. Overall results indicate higher accuracy and lower variability in the paJPM, while directional bias showed the tendency to overshoot the target regardless of condition. The speed did not differ in the two conditions and movements were smoother in the aaJPM, suggesting a higher confidence by participants in their matching ability. In conclusion, this study suggests that motor commands negatively affect the accuracy of joint position sense when matching involves the integration of visual and proprioceptive information.

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.

Robot-aided developmental assessment of wrist proprioception in children

BACKGROUND

Several neurodevelopmental disorders and brain injuries in children have been associated with proprioceptive dysfunction that will negatively affect their movement. Unfortunately, there is lack of reliable and objective clinical examination protocols and our current knowledge of how proprioception evolves in typically developing children is still sparse.

METHODS

Using a robotic exoskeleton, we investigated proprioceptive acuity of the wrist in a group of 49 typically developing healthy children (8-15 years), and a group of 40 young adults. Without vision participants performed an ipsilateral wrist joint position matching task that required them to reproduce (match) a previously experienced target position. All three joint degrees-of-freedom of the wrist/hand complex were assessed. Accuracy and precision were evaluated as a measure of proprioceptive acuity. The cross-sectional data indicating the time course of development of acuity were then fitted by four models in order to determine which function best describes developmental changes in proprioception across age.

RESULTS

First, the robot-aided assessment proved to be an easy to administer method for objectively measuring proprioceptive acuity in both children and adult populations. Second, proprioceptive acuity continued to develop throughout middle childhood and early adolescence, improving by more than 50% with respect to the youngest group. Adult levels of performance were reached approximately by the age of 12 years. An inverse-root function best described the development of proprioceptive acuity across the age groups. Third, wrist/forearm proprioception is anisotropic across the three DoFs with the Abduction/Adduction exhibiting a higher level of acuity than those of Flexion/extension and Pronation/Supination. This anisotropy did not change across development.

CONCLUSIONS

Proprioceptive development for the wrist continues well into early adolescence. Our normative data obtained trough this novel robot-aided assessment method provide a basis against which proprioceptive function of pediatric population can be compared. This may aid the design of more effective sensorimotor intervention programs.

Preliminary design and control of a soft exosuit for assisting elbow movements and hand grasping in activities of daily living

The development of a portable assistive device to aid patients affected by neuromuscular disorders has been the ultimate goal of assistive robots since the late 1960s. Despite significant advances in recent decades, traditional rigid exoskeletons are constrained by limited portability, safety, ergonomics, autonomy and, most of all, cost. In this study, we present the design and control of a soft, textile-based exosuit for assisting elbow flexion/extension and hand open/close. We describe a model-based design, characterisation and testing of two independent actuator modules for the elbow and hand, respectively. Both actuators drive a set of artificial tendons, routed through the exosuit along specific load paths, that apply torques to the human joints by means of anchor points. Key features in our design are under-actuation and the use of electromagnetic clutches to unload the motors during static posture. These two aspects, along with the use of 3D printed components and off-the-shelf fabric materials, contribute to cut down the power requirements, mass and overall cost of the system, making it a more likely candidate for daily use and enlarging its target population. Low-level control is accomplished by a computationally efficient machine learning algorithm that derives the system’s model from sensory data, ensuring high tracking accuracy despite the uncertainties deriving from its soft architecture. The resulting system is a low-profile, low-cost and wearable exosuit designed to intuitively assist the wearer in activities of daily living.

Wrist Proprioception: Amplitude or Position Coding?

This work examines physiological mechanisms underlying the position sense of the wrist, namely, the codification of proprioceptive information related to pointing movements of the wrist toward kinesthetic targets. Twenty-four healthy subjects participated to a robot-aided assessment of their wrist proprioceptive acuity to investigate if the sensorimotor transformation involved in matching targets located by proprioceptive receptors relies on amplitude or positional cues. A joint position matching test was performed in order to explore such dichotomy. In this test, the wrist of a blindfolded participant is passively moved by a robotic device to a preset target position and, after a removal movement from this position, the participant has to actively replicate and match it as accurately as possible. The test involved two separate conditions: in the first, the matching movements started from the same initial location; in the second one, the initial location was randomly assigned. Target matching accuracy, precision, and bias in the two conditions were then compared. Overall results showed a consistent higher performance in the former condition than in the latter, thus supporting the hypothesis that the joint position sense is based on vectorial or amplitude coding rather than positional.

Robot-Assisted Proprioceptive Training with Added Vibro-Tactile Feedback Enhances Somatosensory and Motor Performance

This study examined the trainability of the proprioceptive sense and explored the relationship between proprioception and motor learning. With vision blocked, human learners had to perform goal-directed wrist movements relying solely on proprioceptive/haptic cues to reach several haptically specified targets. One group received additional somatosensory movement error feedback in form of vibro-tactile cues applied to the skin of the forearm. We used a haptic robotic device for the wrist and implemented a 3-day training regimen that required learners to make spatially precise goal-directed wrist reaching movements without vision. We assessed whether training improved the acuity of the wrist joint position sense. In addition, we checked if sensory learning generalized to the motor domain and improved spatial precision of wrist tracking movements that were not trained. The main findings of the study are: First, proprioceptive acuity of the wrist joint position sense improved after training for the group that received the combined proprioceptive/haptic and vibro-tactile feedback (VTF). Second, training had no impact on the spatial accuracy of the untrained tracking task. However, learners who had received VTF significantly reduced their reliance on haptic guidance feedback when performing the untrained motor task. That is, concurrent VTF was highly salient movement feedback and obviated the need for haptic feedback. Third, VTF can be also provided by the limb not involved in the task. Learners who received VTF to the contralateral limb equally benefitted. In conclusion, somatosensory training can significantly enhance proprioceptive acuity within days when learning is coupled with vibro-tactile sensory cues that provide feedback about movement errors. The observable sensory improvements in proprioception facilitates motor learning and such learning may generalize to the sensorimotor control of the untrained motor tasks. The implications of these findings for neurorehabilitation are discussed.

The Role of Visual and Haptic Feedback During Dynamically Coupled Bimanual Manipulation

The mechanisms that underlie the control of bimanual actions in which the two hands act separately to manipulate different objects (uncoupled independent control) has been well studied. In contrast, much less is known about how the central nervous system controls bimanual actions that require the two hands act cooperatively to manipulate a single object (dynamically coupled control). Furthermore, there is scant research into the manual lateralization and role assignment in the processing of visual and haptic feedback during dynamically coupled bimanual tasks. In this experiment, we examined the role of the dominant and non-dominant hands during a dynamically coupled bimanual task in which visual and haptic feedback regarding object penetration were manipulated. Twelve subjects performed a bimanual grasp and reach task towards different target locations in the workspace by using two identical wrist robotic devices. Results showed haptic feedback is necessary for task completion, and that hand specialization plays a fundamental role in spatial and temporal coordination between the two limbs.

Preliminary analysis of non-dominant proprioceptive acuity and interlimb asymmetry in the human wrist

Proprioception provides information about limb configuration which are essential for planning and controlling its posture and movement. Asymmetries in the way dominant and non-dominant limbs exploit proprioceptive information have been previously evaluated, with contradictory results due to the difference in the employed methodology. A measure of proprioceptive acuity that does not reflect the influence of one limb on the other consists in the evaluation of the psychophysical threshold. This metric, evaluated separately for each limb and involving only passive movements, reflects a reliable measure of proprioceptive acuity. The aim of this work is to first evaluate the proprioceptive acuity of the non-dominant wrist joint in flexion/extension and adduction/abduction and to compare these results to the acuity of the dominant wrist. Data were collected during a unidirectional 2-alternative-forcedchoice test performed by six right-handed subjects. We found acuity of 1.31°, 1.26°, 1.33° and 1.63° respectively for abduction, adduction, extension and flexion of the non-dominant wrist. Acuity of the dominant wrist was assessed for five of the subjects for abduction and flexion and resulted lower (mean values were respectively 1.64° and 2.14°). The preliminary results suggest a leading role of the non-dominant wrist in the processing of the proprioceptive feedback.

Robot-Aided Mapping of Wrist Proprioceptive Acuity across a 3D Workspace

Proprioceptive signals from peripheral mechanoreceptors form the basis for bodily perception and are known to be essential for motor control. However we still have an incomplete understanding of how proprioception differs between joints, whether it differs among the various degrees-of-freedom (DoFs) within a particular joint, and how such differences affect motor control and learning. We here introduce a robot-aided method to objectively measure proprioceptive function: specifically, we systematically mapped wrist proprioceptive acuity across the three DoFs of the wrist/hand complex with the aim to characterize the wrist position sense. Thirty healthy young adults performed an ipsilateral active joint position matching task with their dominant wrist using a haptic robotic exoskeleton. Our results indicate that the active wrist position sense acuity is anisotropic across the joint, with the abduction/adduction DoF having the highest acuity (the error of acuity for flexion/extension is 4.64 ± 0.24°; abduction/adduction: 3.68 ± 0.32°; supination/pronation: 5.15 ± 0.37°) and they also revealed that proprioceptive acuity decreases for smaller joint displacements. We believe this knowledge is imperative in a clinical scenario when assessing proprioceptive deficits and for understanding how such sensory deficits relate to observable motor impairments.

Role of Muscle Synergies in Real-Time Classification of Upper Limb Motions using Extreme Learning Machines

Background

Myoelectric signals offer significant insights in interpreting the motion intention and extent of effort involved in performing a movement, with application in prostheses, orthosis and exoskeletons. Feature extraction plays a vital role, and follows two approaches: EMG and synergy features. More recently, muscle synergy based features are being increasingly explored, since it simplifies dimensionality of control, and are considered to be more robust to signal variations. Another important aspect in a myoelectrically controlled devices is the learning capability and speed of performance for online decoding. Extreme learning machine (ELM) is a relatively new neural-network based learning algorithm: its performance hasn’t been explored in the context of online control, which is a more reliable measure compared to offline analysis. To this purpose we aim at focusing our investigation on a myoelectric-based interface which is able to identify and online classify, upper limb motions involving shoulder and elbow. The main objective is to compare the performance of the decoder trained using ELM, for two different features: EMG and synergy features.

Methods

The experiments are broadly divided in two phases training/calibration and testing respectively. ELM is used to train the decoder using data acquired during the calibration phase. The performance of the decoder is then tested in online motion control by using a simulated graphical user interface replicating the human limb: subjects are requested to control a virtual arm by using their muscular activity. The decoder performance is quantified using ad-hoc metrics based on the following indicators: motion selection time, motion completion time, and classification accuracy.

Results

Performance has been evaluated for both offline and online contexts. The offline classification results indicated better performance in the case of EMG features, whereas a better classification accuracy for synergy feature was observed for online decoding. Also the other indicators as motion selection time and motion completion time, showed better trend in the case of synergy than time-domain features.

Conclusion

This work demonstrates better robustness of online decoding of upper-limb motions and motor intentions when using synergy feature. Furthermore, we have quantified the performance of the decoder trained using ELM for online control, providing a potential and viable option for real-time myoelectric control in assistive technology.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-016-0183-0) contains supplementary material, which is available to authorized users.