Proportional myoelectric control of a virtual bionic arm in participants with hemiparesis, muscle spasticity, and impaired range of motion

BACKGROUND

This research aims to improve the control of assistive devices for individuals with hemiparesis after stroke by providing intuitive and proportional motor control. Stroke is the leading cause of disability in the United States, with 80% of stroke-related disability coming in the form of hemiparesis, presented as weakness or paresis on half of the body. Current assistive exoskeletonscontrolled via electromyography do not allow for fine force regulation. Current control strategies provide only binary, all-or-nothing control based on a linear threshold of muscle activity.

METHODS

In this study, we demonstrate the ability of participants with hemiparesis to finely regulate their muscle activity to proportionally control the position of a virtual bionic arm. Ten stroke survivors and ten healthy, aged-matched controls completed a target-touching task with the virtual bionic arm. We compared the signal-to-noise ratio (SNR) of the recorded electromyography (EMG) signals used to train the control algorithms and the task performance using root mean square error, percent time in target, and maximum hold time within the target window. Additionally, we looked at the correlation between EMG SNR, task performance, and clinical spasticity scores.

RESULTS

All stroke survivors were able to achieve proportional EMG control despite limited or no physical movement (i.e., modified Ashworth scale of 3). EMG SNR was significantly lower for the paretic arm than the contralateral nonparetic arm and healthy control arms, but proportional EMG control was similar across conditions for hand grasp. In contrast, proportional EMG control for hand extension was significantly worse for paretic arms than healthy control arms. The participants' age, time since their stroke, clinical spasticity rate, and history of botulinum toxin injections had no impact on proportional EMG control.

CONCLUSIONS

It is possible to provide proportional EMG control of assistive devices from a stroke survivor's paretic arm. Importantly, information regulating fine force output is still present in muscle activity, even in extreme cases of spasticity where there is no visible movement. Future work should incorporate proportional EMG control into upper-limb exoskeletons to enhance the dexterity of stroke survivors.

Post-traumatic hand rehabilitation using a powered metacarpal-phalangeal exoskeleton: a pilot study

BACKGROUND

In the context of post-traumatic hand rehabilitation, stiffness of the hand joints limits the range of motion (ROM), grip strength, and the possibility of performing simple grasps. Robotic rehabilitation has been widely adopted for hand treatment with neurological patients, but its application in the orthopaedic scenario remains limited. In this paper, a pilot study targeting this population is presented, where the rehabilitation is performed using a powered finger exoskeleton, namely I-Phlex. The device aims to mobilize the metacarpal-phalangeal joint (MCP) in flexion-extension movements. The objective of the study was to verify the short-term efficacy, experience of use, and safety of I-Phlex in a clinical setting. As a secondary objective, the study verified the device's capability to measure clinically relevant variables.

METHODS

Six subjects with trauma-related illnesses of the right hand took part in the experiment. Passive and active range of motion (PROM and AROM) were recorded at the beginning and the end of the session by the therapist and by the exoskeleton. Experience of use was assessed through ad-hoc questionnaires and a numerical pain rate scale (NPRS). Safety was assessed by computing the number of adverse events during the operation.

RESULTS

Median increases in the PROM and AROM of 5.88% and 11.11% respectively were recorded among subjects. The questionnaires reported a median score of 93.83; IQR (85.01-100) and 80.00; IQR (79.79-93.75) respectively. No increase in the median NPRS was recorded among subjects between pre-and post-treatment. No major adverse event or injury to the patients was recorded. Only one malfunction was reported due to the brake of a transmission cable, but the patient reported no injury or discomfort. No statistical significance was observed between the ROM measurement recorded using the exoskeleton and the ones taken by the therapist using the goniometer.

CONCLUSIONS

The device and related rehabilitation exercises can be successfully used in the clinical rehabilitation of the MCP joint. The device measurements are in line with the goniometer assessment from the therapist. Future studies will aim to reinforce the results obtained, introducing a control group to conclude on the specific contribution of the technology compared to conventional therapy.

TRIAL REGISTRATION

Hand Motor Rehabilitation Using a Wearable Robotic Device (WRL HX MCP), Clinicaltrials.gov ID NCT05155670, Registration date 13 December 2021, URL https://clinicaltrials.gov/ct2/show/NCT05155670 .

Concurrent and continuous estimation of multi-finger forces by synergy mapping and reconstruction: a pilot study

Objective.The absence of intuitive control in present myoelectric interfaces makes it a challenge for users to communicate with assistive devices efficiently in real-world conditions. This study aims to tackle this difficulty by incorporating neurophysiological entities, namely muscle and force synergies, onto multi-finger force estimation to allow intuitive myoelectric control.Approach. Eleven healthy subjects performed six isometric grasping tasks at three muscle contraction levels. The exerted fingertip forces were collected concurrently with the surface electromyographic (sEMG) signals from six extrinsic and intrinsic muscles of hand. Muscle synergies were then extracted from recorded sEMG signals, while force synergies were identified from measured force data. Afterwards, a linear regressor was trained to associate the two types of synergies. This would allow us to predict multi-finger forces simply by multiplying the activation signals derived from muscle synergies with the weighting matrix of initially identified force synergies. To mitigate the false activation of unintended fingers, the force predictions were finally corrected by a finger state recognition procedure.Main results. We found that five muscle synergies and four force synergies are able to make a tradeoff between the computation load and the prediction accuracy for the proposed model; When trained and tested on all six grasping tasks, our method (SYN-II) achieved better performance (R2= 0.80 ± 0.04, NRMSE = 0.19 ± 0.01) than conventional sEMG amplitude-based method; Interestingly, SYN-II performed better than all other methods when tested on two unknown tasks outside the four training tasks (R2= 0.74 ± 0.03, NRMSE = 0.22 ± 0.02), which indicated better generalization ability.Significance. This study shows the first attempt to link between muscle and force synergies to allow concurrent and continuous estimation of multi-finger forces from sEMG. The proposed approach may lay the foundation for high-performance myoelectric interfaces that allow users to control robotic hands in a more natural and intuitive manner.

MITEx: A Portable Hand Exoskeleton for Assessment and Treatment in Neurological Rehabilitation

This work describes the design and preliminary characterization of a novel portable hand exoskeleton for poststroke rehabilitation. The platform actively mobilizes the index-metacarpophalangeal (I-MCP) joint, and it additionally offers individual rigid support to distal degrees of freedom (DoFs) of the index and thumb. The test-bench characterization proves the capability of the device to render torques at the I-MCP level with high fidelity within frequencies of interest for the application (up to 3 Hz). The introduction of a feed-forward friction compensation at the actuator level lowers the output mechanical stiffness by 32%, contributing to a highly transparent behavior; moreover, the functionality of the platform in rendering different interaction strategies (patient/robot-in-charge) is tested with three healthy subjects, showing the potential of the device to provide assistance as needed.

Towards comprehensive evaluation of the FLEXotendon glove-III: a case series evaluation in pediatric clinical cases and able-bodied adults

Injuries involving the nervous system, such as a brachial plexus palsy or traumatic brain injury, can lead to impairment in the functionality of the hand. Assistive robotics have been proposed as a possible method to improve patient outcomes in rehabilitation. The work presented here evaluates the FLEXotendon Glove-III, a 5 degree-of-freedom, voice-controlled, tendon-driven soft robotic hand exoskeleton, with two human subjects with hand impairments and four able-bodied subjects. The FLEXotendon Glove-III was evaluated on four unimpaired subjects, in conjunction with EMG sensor data, to determine the quantitative performance of the glove in applied pinch force, perturbation resistance, and exertion reduction. The exoskeleton system was also evaluated on two subjects with hand impairments, using two standardized hand function tests, the Jebsen-Taylor Hand Function Test and the Toronto Rehabilitation Institute Hand Function Test. The subjects were also presented with three qualitative questionnaires, the Capabilities of Upper Extremities Questionnaire, the Quebec User Evaluation of Satisfaction with Assistive Technology, and the Orthotics Prosthetics User Survey-Satisfaction module. From the previous design, minor design changes were made to the exoskeleton. The quick connect system was redesigned for improved performance, the number of motors was reduced to decrease overall footprint, and the entire system was placed into a compact acrylic case that can be placed into a backpack for increased portability.

Evaluation of the FLEXotendon glove-III through a human subject case study

Cervical spinal cord injury (SCI) can significantly impair an individual's hand functionality due to the disruption of nerve signals from the brain to the upper extremity. Robotic assistive hand exoskeletons have been proposed as a potential technology to facilitate improved patient rehabilitation outcomes, but few exoskeleton studies utilize standardized hand function tests and questionnaires to produce quantitative data regarding exoskeleton performance. This work presents the human subject case study evaluation of the FLEXotendon Glove-III, a 5 degree-of-freedom voice-controlled, tendon-driven soft robotic assistive hand exoskeleton for individuals with SCI. The exoskeleton system was evaluated in a case study with two individuals with SCI through two standardized hand function tests namely, the Jebsen-Taylor Hand Function Test and the Toronto Rehabilitation Institute Hand Function Test and three questionnaires (Capabilities of Upper Extremities Questionnaire, Orthotics Prosthetics Users Survey, Quebec User Evaluation of Satisfaction with Assistive Technology). Minor design changes were made to the exoskeleton: integrated fingertip force sensors to sense excessive grasp force, a quick connect system to expedite the exoskeleton glove swapping process between users, compact tendon tension sensors to measure tendon force for admittance control, and a redesigned smartphone app to encompass all aspects of exoskeleton use.

A Novel Robotic Exoskeleton for Finger Rehabilitation: Kinematics Analysis

A novel robotic exoskeleton for fingers rehabilitation is developed, which is driven by linear motors through Bowden cables. For each finger, in addition to three links acting as phalanxes, two more links acting as knuckles are also implemented. Links are connected through passive joints, by which translational and rotary movements can be realized simultaneously. Either flexion or extension motion is accomplished by one cable of adequate stiffness. This exoskeleton possesses good adaptability to finger length of different subjects and length variations during movement. The exoskeleton’s kinematics model is built by the statistics method, and piecewise polynomial functions (PPF) are chosen to describe the relationship between motor displacement and joint variables. Finally, the relationship between motor displacement and the finger’s total bending angle is obtained, which can be used for rehabilitation trajectory planning. Experimental results show that this exoskeleton achieves nearly the maximum finger bending angle of a healthy adult person, with the maximum driving force of 68.6 N.