Effect of ultrasound-guided injection of botulinum toxin type A into shoulder joint cavity on shoulder pain in poststroke patients: study protocol for a randomized controlled trial.

BACKGROUND: Hemiplegic shoulder pain (HSP) is a common complication after stroke. It severely affects the recovery of upper limb motor function. Early shoulder pain in hemiplegic patients is mainly neuropathic caused by central nerve injury or neuroplasticity. Commonly used corticosteroid injections in the shoulder joint can reduce shoulder pain; however, the side effects also include soft tissue degeneration or increased tendon fragility, and the long-term effects remain controversial. Botulinum toxin injections are relatively new and are thought to block the transmission of pain receptors in the shoulder joint cavity and inhibit the production of neuropathogenic substances to reduce neurogenic inflammation. Some studies suggest that the shoulder pain of hemiplegia after stroke is caused by changes in the central system related to shoulder joint pain, and persistent pain may induce the reorganization of the cortical sensory center or motor center. However, there is no conclusive evidence as to whether or not the amelioration of pain by botulinum toxin affects brain function. In previous studies of botulinum toxin versus glucocorticoids (triamcinolone acetonide injection) in the treatment of shoulder pain, there is a lack of observation of differences in changes in brain function. As the content of previous assessments of pain improvement was predominantly subjective, objective quantitative assessment indicators were lacking. Functional near-infrared imaging (fNIRS) can remedy this problem. METHODS: This study protocol is designed for a double-blind, randomized controlled clinical trial of patients with post-stroke HSP without biceps longus tenosynovitis or acromion bursitis. Seventy-eight patients will be randomly assigned to either the botulinum toxin type A or glucocorticoid group. At baseline, patients in each group will receive shoulder cavity injections of either botulinum toxin or glucocorticoids and will be followed for 1 and 4 weeks. The primary outcome is change in shoulder pain on the visual analog scale (VAS). The secondary outcome is the assessment of changes in oxyhemoglobin levels in the corresponding brain regions by fNIRS imaging, shoulder flexion, external rotation range of motion, upper extremity Fugl-Meyer, and modified Ashworth score. DISCUSSION: Ultrasound-guided botulinum toxin type A shoulder joint cavity injections may provide evidence of pain improvement in patients with HSP. The results of this trial are also help to analyze the correlation between changes in shoulder pain and changes in cerebral hemodynamics and shoulder joint motor function. TRIAL REGISTRATION: Chinese clinical Trial Registry, ChiCTR2300070132. Registered 03 April 2023, https://www.chictr.org.cn/showproj.html?proj=193722 .

Analysis of lumbar spine loading during walking in patients with chronic low back pain and healthy controls: An OpenSim-Based study.

Low back pain (LBP) is one of the most prevalent and disabling disease worldwide. However, the specific biomechanical changes due to LBP are still controversial. The purpose of this study was to estimate the lumbar and lower limb kinematics, lumbar moments and loads, muscle forces and activation during walking in healthy adults and LBP. A total of 18 healthy controls and 19 patients with chronic LBP were tested for walking at a comfortable speed. The kinematic and dynamic data of the subjects were collected by 3D motion capture system and force plates respectively, and then the motion simulation was performed by OpenSim. The OpenSim musculoskeletal model was used to calculate lumbar, hip, knee and ankle joint angle variations, lumbar moments and loads, muscle forces and activation of eight major lumbar muscles. In our results, significant lower lumbar axial rotation angle, lumbar flexion/extension and axial rotation moments, as well as the muscle forces of the four muscles and muscle activation of two muscles were found in patients with LBP than those of the healthy controls (p < 0.05). This study may help providing theoretical support for the evaluation and rehabilitation treatment intervention of patients with LBP.

An Adaptive Hammerstein Model for FES-Induced Torque Prediction Based on Variable Forgetting Factor Recursive Least Squares Algorithm.

Modeling the muscle response to functional electrical stimulation (FES) is an important step during model-based FES control system design. The Hammerstein structure is widely used in simulating this nonlinear biomechanical response. However, a fixed relationship cannot cope well with the time-varying property of muscles and muscle fatigue. In this paper, we proposed an adaptive Hammerstein model to predict ankle joint torque induced by electrical stimulation, which used variable forgetting factor recursive least squares (VFFRLS) method to update the model parameters. To validate the proposed model, ten healthy individuals were recruited for short-duration FES experiments, ten for long-duration FES experiments, and three stroke patients for both. The isometric ankle dorsiflexion torque induced by FES was measured, and then the test performance of the fixed-parameter Hammerstein model, the adaptive Hammerstein model based on fixed forgetting factor recursive least squares (FFFRLS) and the adaptive Hammerstein model based on VFFRLS was compared. The goodness of fit, root mean square error, peak error and success rate were applied to evaluate the accuracy and stability of the model. The results indicate a significant improvement in both the accuracy and stability of the proposed adaptive model compared to the fixed-parameter model and the adaptive model based on FFFRLS. The proposed adaptive model enhances the ability of the model to cope with muscle changes.

Isometric Plantarflexion Moment Prediction Based on a Compartment-specific HD-sEMG-driven Musculoskeletal Model.

OBJECTIVE: electromyogram (EMG)-driven musculoskeletal models have been widely used to investigate human movements while existing EMG-driven models commonly neglect regional heterogeneity in anatomy and activation within a skeletal muscle. To consider neuromuscular compartment anatomy and activation, a subject- and compartment-specific EMG-driven model was developed for isometric plantarflexion moment prediction. METHODS: the model was hill-type consisting of gastrocnemius medialis, gastrocnemius lateralis, and soleus around the ankle joint, and each muscle was discretised into four compartments. The moment arms of each compartment were determined using magnetic resonance imaging and the compartment activation was calculated based on high-density surface EMG signals. And the hill-type compartment parameters were tuned in a calibration process. The developed compartment-specific model and a generic EMG-driven model were examined by comparing their predicted net ankle moments with measurements obtained while subjects performed isometric plantarflexion tasks at different contraction levels. RESULTS: compared to the generic EMG-driven model, the isometric plantarflexion moment prediction using the compartment-specific model was more accurate at all contraction levels, with the average prediction error decreasing from average 13.81% to 10.11%. The contraction of each compartment was found to be generally non-uniform at all contraction levels. CONCLUSION: the developed compartment-specific model enabled accurate prediction of isometric plantarflexion moment and the simulation of non-uniform muscular contraction, which is more physiologically appropriate than the existing EMG-driven models. SIGNIFICANCE: the proposed compartment-specific formulation opens new perspectives for subject-specific musculoskeletal modelling, which has great potential in understanding regional characteristics of the neuromuscular activities.

Trajectory Deformation-Based Multi-Modal Adaptive Compliance Control for a Wearable Lower Limb Rehabilitation Robot.

Adaptive compliance control is critical for rehabilitation robots to cope with the varying rehabilitation needs and enhance training safety. This article presents a trajectory deformation-based multi-modal adaptive compliance control strategy (TD-MACCS) for a wearable lower limb rehabilitation robot (WLLRR), which includes a high-level trajectory planner and a low-level position controller. Dynamic motion primitives (DMPs) and a trajectory deformation algorithm (TDA) are integrated into the high-level trajectory planner, generating multi-joint synchronized desired trajectories through physical human-robot interaction (pHRI). In particular, the amplitude modulation factor of DMPs and the deformation factor of TDA are adapted by a multi-modal adaptive regulator, achieving smooth switching of human-dominant mode, robot-dominant mode, and soft-stop mode. Besides, a linear active disturbance rejection controller is designed as the low-level position controller. Four healthy participants and two stroke survivors are recruited to conduct robot-assisted walking experiments using the TD-MACCS. The results show that the TD-MACCS can smoothly switch three control modes while guaranteeing trajectory tracking accuracy. Moreover, we find that appropriately increasing the upper bound of the deformation factor can enhance the average walking speed (AWS) and root mean square of trajectory deviation (RMSTD).

Modeling Ankle Torque and Stiffness Induced by Functional Electrical Stimulation.

Functional electrical stimulation (FES) is commonly used for individuals with neuromuscular impairments to generate muscle contractions. Both joint torque and stiffness play important roles in maintaining stable posture and resisting external disturbance. However, most previous studies only focused on the modulation of joint torque using FES while ignoring the joint stiffness. A model that can simultaneously modulate both ankle torque and stiffness induced by FES was investigated in this study. This model was composed of four subparts including an FES-to-activation model, a musculoskeletal geometry model, a Hill-based muscle-tendon model, and a joint stiffness model. The model was calibrated by the maximum voluntary contraction test of the tibialis anterior (TA) and gastrocnemius medial (GAS) muscles. To validate the model, the estimated torque and stiffness by the model were compared with the measured torque and stiffness induced by FES, respectively. The results showed that the proposed model can estimate torque and stiffness with electrically stimulated TA or/and GAS, which was significantly correlated to the measured torque and stiffness. The proposed model can modulate both joint torque and stiffness induced by FES in the isometric condition, which can be potentially extended to modulate the joint torque and stiffness during FES-assisted walking.

Iterative Adjustment of Stimulation Timing and Intensity During FES-Assisted Treadmill Walking for Patients After Stroke.

Functional electric stimulation (FES) is a common intervention to correct foot drop for patients after stroke. Due to the disturbances from internal time-varying muscle characteristics under electrical stimulation and external environmental uncertainties, most of the existing FES system used pre-set stimulation parameters and cannot achieve good gait performances during FES-assisted walking. Therefore, an adaptive FES control system, which used the iterative learning control to adjust the stimulation intensity based on kinematic data and a linear model to modulate the stimulation timing based on walking speed during FES-assisted treadmill walking, was designed and tested on ten patients with foot drop after stroke. In order to examine its orthotic effects, the kinematic data of the patients using the proposed control strategy were collected and compared with the data of the same patients walking using other three FES control strategies, including (1) constant pre-set stimulation intensity and timing, (2) constant pre-set stimulation intensity with speed-adaptive stimulation timing and (3) walking without FES intervention. The error between the maximum ankle dorsiflexion angle during swing phase and the target angle using the proposed control strategy was the smallest among the four conditions. Moreover, there was no significant difference in the ankle plantar flexion angle at the toe-off event and the maximum knee flexion angle during swing phase between the proposed control strategy and walking without FES. In summary, the proposed control strategy can improve FES-assisted walking performances through adaptive modulation of stimulation timing and intensity when coping with variation, and may have good potential in clinic.

The Step Response in Isometric Grip Force Tracking: A Model to Characterize Aging- and Stroke-Induced Changes.

This paper aimed to construct a model to represent dynamic motor behavior to quantitatively investigate aging- and stroke-induced changes and, thus, to explore the underlying mechanisms of grip control. Grip force tracking tasks were conducted by stroke patients, age-matched healthy controls, and healthy young adults at 25%, 50%, and 75% maximum voluntary contractions (MVC), respectively. Sensorimotor control of the tracking task was modeled as the step response of a second-order system. The results revealed that aging had no significant effect on the parameters of the model, whereas significant differences were found between the age-matched control and stroke groups. Target force level significantly affected the damping ratio and natural frequency in the young group, and significantly affected the damping ratio in the stroke group. Significant correlations were found between the wolf motor function test score and damping ratio, natural frequency, and settling time at 25% MVC. The model could describe the stroke-induced oscillation and slow response in dynamic grip force control and has the potential to be a quantitative evaluation of motor disabilities in clinic.

Finite element models of the human shoulder complex: a review of their clinical implications and modelling techniques.

The human shoulder is a complicated musculoskeletal structure and is a perfect compromise between mobility and stability. The objective of this paper is to provide a thorough review of previous finite element (FE) studies in biomechanics of the human shoulder complex. Those FE studies to investigate shoulder biomechanics have been reviewed according to the physiological and clinical problems addressed: glenohumeral joint stability, rotator cuff tears, joint capsular and labral defects and shoulder arthroplasty. The major findings, limitations, potential clinical applications and modelling techniques of those FE studies are critically discussed. The main challenges faced in order to accurately represent the realistic physiological functions of the shoulder mechanism in FE simulations involve (1) subject-specific representation of the anisotropic nonhomogeneous material properties of the shoulder tissues in both healthy and pathological conditions; (2) definition of boundary and loading conditions based on individualised physiological data; (3) more comprehensive modelling describing the whole shoulder complex including appropriate three-dimensional (3D) representation of all major shoulder hard tissues and soft tissues and their delicate interactions; (4) rigorous in vivo experimental validation of FE simulation results. Fully validated shoulder FE models would greatly enhance our understanding of the aetiology of shoulder disorders, and hence facilitate the development of more efficient clinical diagnoses, non-surgical and surgical treatments, as well as shoulder orthotics and prosthetics. © 2016 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.