A neuromusculoskeletal model to simulate the constant angular velocity elbow extension test of spasticity

Biomechanical study of the effect of traction on elbow joint capsule contracture

Dynamic orthoses have a significant effect on the treatment of elbow capsular contracture. Because of the lack of quantitative research on traction forces, determining the appropriate traction force to help stretch soft tissues and maintain the joint's range of motion is a challenge in the rehabilitation process. We developed a human elbow finite element (FE) model incorporating the activity behavior of the muscles and considering different capsular contracture locations, including total, anterior and posterior capsular contractures, to analyze the internal biomechanical responses of different capsular contracture models during flexion (30 to 80 degrees). Traction loads of 10, 20, 30 and 40 N were applied to the ulna and radius at the maximum flexion angle (80 degrees) to explore the appropriate traction loads at week 4 after a joint capsule injury. We observed a significant increase in posterior capsule stress with anterior capsular contracture (ACC), and the maximum peak stress was 1.3 times higher than that in the healthy model. During the fourth week after elbow capsule injury, the appropriate traction forces for total capsule contracture (TCC), ACC and posterior capsule contracture (PCC) were 20, 10 and 20 N, respectively; these forces maintained a stable biomechanical environment for the elbow joint and achieved a soft tissue pulling effect, thus increasing elbow mobility. The results can be used as a quantitative guide for the rehabilitation physicians to determine the traction load for a specific patient.

Rigidity in Parkinson's disease: evidence from biomechanical and neurophysiological measures

Although rigidity is a cardinal motor sign in patients with Parkinson's disease (PD), the instrumental measurement of this clinical phenomenon is largely lacking, and its pathophysiological underpinning remains still unclear. Further advances in the field would require innovative methodological approaches able to measure parkinsonian rigidity objectively, discriminate the different biomechanical sources of muscle tone (neural or visco-elastic components), and finally clarify the contribution to 'objective rigidity' exerted by neurophysiological responses, which have previously been associated with this clinical sign (i.e. the long-latency stretch-induced reflex). Twenty patients with PD (67.3 ± 6.9 years) and 25 age- and sex-matched controls (66.9 ± 7.4 years) were recruited. Rigidity was measured clinically and through a robotic device. Participants underwent robot-assisted wrist extensions at seven different angular velocities randomly applied, when ON therapy. For each value of angular velocity, several biomechanical (i.e. elastic, viscous and neural components) and neurophysiological measures (i.e. short and long-latency reflex and shortening reaction) were synchronously assessed and correlated with the clinical score of rigidity (i.e. Unified Parkinson's Disease Rating Scale-part III, subitems for the upper limb). The biomechanical investigation allowed us to measure 'objective rigidity' in PD and estimate the neuronal source of this phenomenon. In patients, 'objective rigidity' progressively increased along with the rise of angular velocities during robot-assisted wrist extensions. The neurophysiological examination disclosed increased long-latency reflexes, but not short-latency reflexes nor shortening reaction, in PD compared with control subjects. Long-latency reflexes progressively increased according to angular velocities only in patients with PD. Lastly, specific biomechanical and neurophysiological abnormalities correlated with the clinical score of rigidity. 'Objective rigidity' in PD correlates with velocity-dependent abnormal neuronal activity. The observations overall (i.e. the velocity-dependent feature of biomechanical and neurophysiological measures of objective rigidity) would point to a putative subcortical network responsible for 'objective rigidity' in PD, which requires further investigation.

The role of the joint capsule in the stability of the elbow joint

Existing studies lack a clear understanding of the interaction of the joint capsule with surrounding tissues and the local mechanical environment. Particularly, a finite element model of human elbow joint incorporating active behavior of muscle was constructed. The simulation was performed during the elbow joint flexion movement under different injury conditions of capsule (anterior capsule, posterior capsule, medial anterior capsule, lateral anterior capsule, medial posterior capsule, and lateral posterior capsule). The stress distribution and transfer of the joint capsule, ulnar cartilage, and ligaments were obtained under different injuries and flexion angles, to explore the influence of capsule injures on the stability of the elbow joint. In medial injury posterior capsule, the peak stress of the ulnar cartilage occurred at 60° flexion and shifted from posteromedial to anteromedial. And the stress was about 1.8 times that of no injury capsule. In several cases of posterior capsule injury, the stress of capsule decreased significantly and the peak stress was 40% of that in no injury joint capsule. In the case of anterior capsular injury, the cartilage stress did not change significantly, and the stress of anterior bundle and annular ligament changed slightly in the late flexion movement. These findings provide some help for doctors to treat elbow injury and understand the interaction of tissues around the joint after trauma.

Quantitative measurement of resistance force and subsequent attenuation during passive isokinetic extension of the wrist in patients with mild to moderate spasticity after stroke

Background

Spasticity is evaluated by measuring the increased resistance to passive movement, primarily by manual methods. Few options are available to measure spasticity in the wrist more objectively. Furthermore, no studies have investigated the force attenuation following increased resistance. The aim of this study was to conduct a safe quantitative evaluation of wrist passive extension stiffness in stroke survivors with mild to moderate spastic paresis using a custom motor-controlled device. Furthermore, we wanted to clarify whether the changes in the measured values could quantitatively reflect the spastic state of the flexor muscles involved in the wrist stiffness of the patients.

Materials and methods

Resistance forces were measured in 17 patients during repetitive passive extension of the wrist at velocities of 30, 60, and 90 deg/s. The Modified Ashworth Scale (MAS) in the wrist and finger flexors was also assessed by two skilled therapists and their scores were averaged (i.e., average MAS) for analysis. Of the fluctuation of resistance, we focused on the damping just after the peak forces and used these for our analysis. A repeated measures analysis of variance was conducted to assess velocity-dependence. Correlations between MAS and damping parameters were analyzed using Spearman’s rank correlation.

Results

The damping force and normalized value calculated from damping part showed significant velocity-dependent increases.

There were significant correlations (ρ = 0.53–0.56) between average MAS for wrist and the normalized value of the damping part at 90 deg/s. The correlations became stronger at 60 deg/s and 90 deg/s when the MAS for finger flexors was added to that for wrist flexors (ρ = 0.65–0.68).

Conclusions

This custom-made isokinetic device could quantitatively evaluate spastic changes in the wrist and finger flexors simultaneously by focusing on the damping part, which may reflect the decrease in resistance we perceive when manually assessing wrist spasticity using MAS.

Trial registration UMIN Clinical Trial Registry, as UMIN000030672, on July 4, 2018

Quantifying neural and non-neural components of wrist hyper-resistance after stroke: Comparing two instrumented assessment methods

Patients with poor upper limb motor recovery after stroke are likely to develop increased resistance to passive wrist extension, i.e., wrist hyper-resistance. Quantification of the underlying neural and non-neural elastic components is of clinical interest. This cross-sectional study compared two methods: a commercially available device (NeuroFlexor®) with an experimental EMG-based device (Wristalyzer) in 43 patients with chronic stroke. Spearman's rank correlation coefficients (r) between components, modified Ashworth scale (MAS) and range of passive wrist extension (PRoM) were calculated with 95% confidence intervals. Neural as well as elastic components assessed by both devices were associated (r = 0.61, 95%CI: 0.38-0.77 and r = 0.53, 95%CI: 0.28-0.72, respectively). The neural component assessed by the NeuroFlexor® associated significantly with the elastic components of NeuroFlexor® (r = 0.46, 95%CI: 0.18-0.67) and Wristalyzer (r = 0.36, 95%CI: 0.06-0.59). The neural component assessed by the Wristalyzer was not associated with the elastic components of both devices. Neural and elastic components of both devices associated similarly with the MAS (r = 0.58, 95%CI: 0.34-0.75 vs. 0.49, 95%CI: 0.22-0.69 and r = 0.51, 95%CI: 0.25-0.70 vs. 0.30, 95%CI: 0.00-0.55); elastic components associated with PRoM (r = -0.44, 95%CI: -0.65- -0.16 vs. -0.74, 95%CI: -0.85- -0.57 for NeuroFlexor® and Wristalyzer respectively). Results demonstrate that both methods perform similarly regarding the quantification of neural and elastic wrist hyper-resistance components and have an added value when compared to clinical assessment with the MAS alone. The added value of EMG in the discrimination between neural and non-neural components requires further investigation.

Effect of the medial collateral ligament and the lateral ulnar collateral ligament injury on elbow stability: a finite element analysis

Ligaments are the most important stabilizer of elbow. However, the stress of ligaments is hard to measure because of the complex biomechanical environment in the elbow. Our objective was to develop a human elbow finite element model and to validate it by a comparison with previous experimental data. Then several different ligaments injury conditions and elbow flexion were simulated to analyse the elbow instability and to stress the biomechanical consequences. The computational investigation of different effects of ligament constraints of elbow was studied by means of finite element analysis. The stress of the anterior bundle was almost greater than other ligaments in all conditions, which played the most important role during the elbow flexion. The posterior bundle was the secondary stabilizer during flexion after the anterior bundle. The lateral ulnar collateral ligament (LUCL) injury could result in an increase of the ulnar cartilage stress. The anterior bundle and the LUCL were recommended to be repaired in elbow joint dislocations and fractures. This study could help understand the dynamic effects of ligaments on the joint over the entire extension by investigating the tissue stress.

Quantitative Modeling of Spasticity for Clinical Assessment, Treatment and Rehabilitation

Spasticity, a common symptom in patients with upper motor neuron lesions, reduces the ability of a person to freely move their limbs by generating unwanted reflexes. Spasticity can interfere with rehabilitation programs and cause pain, muscle atrophy and musculoskeletal deformities. Despite its prevalence, it is not commonly understood. Widely used clinical scores are neither accurate nor reliable for spasticity assessment and follow up of treatments. Advancement of wearable sensors, signal processing and robotic platforms have enabled new developments and modeling approaches to better quantify spasticity. In this paper, we review quantitative modeling techniques that have been used for evaluating spasticity. These models generate objective measures to assess spasticity and use different approaches, such as purely mechanical modeling, musculoskeletal and neurological modeling, and threshold control-based modeling. We compare their advantages and limitations and discuss the recommendations for future studies. Finally, we discuss the focus on treatment and rehabilitation and the need for further investigation in those directions.

A Simplified Estimation of Abnormal Reflex Torque due to Elbow Spasticity Using Neuro-musculoskeletal Model

This paper is to develop a simplified estimation method of internal torque for clinical use, such as spasticity assessment. Compared with many parameters to be tuned, the proposed estimation method only has a single tuning parameter by simplifying the neuro-musculoskeletal model. Moreover, based on forward dynamics, the proposed method uses EMG signals as the input, and uses muscle activation dynamics and musculotendon dynamics to calculate internal torque. A biomechanical method based on dynamometer was applied to determine the tuning parameter and to validate the estimation result of the proposed model. Through a pilot study with healthy subjects and stroke patients, we found that the proposed estimation method would be helpful for spasticity assessment.

Measurement Properties of the NeuroFlexor Device for Quantifying Neural and Non-neural Components of Wrist Hyper-Resistance in Chronic Stroke

Introduction: Differentiating between the components of wrist hyper-resistance post stroke, i.e., pathological neuromuscular activation ("spasticity") and non-neural biomechanical changes, is important for treatment decisions. This study aimed to assess the reliability and construct validity of an innovative measurement device that quantifies these neural and non-neural components by biomechanical modeling. Methods: Forty-six patients with chronic stroke and 30 healthy age-matched subjects were assessed with the NeuroFlexor, a motor-driven device that imposes isokinetic wrist extensions at two controlled velocities (5 and 236°/s). Test-retest reliability was evaluated using intraclass correlation coefficients (ICC) and smallest detectable changes (SDC), and construct validity by testing the difference between patients and healthy subjects and between subgroups of patients stratified by modified Ashworth scale (MAS), and the association with clinical scales. Results: Test-retest reliability was excellent for the neural (NC) and non-neural elastic (EC) components (ICC 0.93 and 0.95, respectively), and good for the viscous component (VC) (ICC 0.84), with SDCs of 10.3, 3.1, and 0.5 N, respectively. NC and EC were significantly higher in patients compared to healthy subjects (p < 0.001). Components gradually increased with MAS category. NC and EC were positively associated with the MAS (r _s 0.60 and 0.52, respectively; p < 0.01), and NC with the Tardieu scale (r _s 0.36, p < 0.05). NC and EC were negatively associated with the Fugl-Meyer Assessment of the upper extremity and action research arm test (r _s ≤ -0.38, p < 0.05). Conclusions: The NeuroFlexor reliably quantifies neural and non-neural components of wrist hyper-resistance in chronic stroke, but is less suitable for clinical evaluation at individual level due to high SDC values. Although construct validity has been demonstrated, further investigation at component level is needed.

Biomechanical parameters of the elbow stretch reflex in chronic hemiparetic stroke

We sought to determine the relative velocity sensitivity of stretch reflex threshold angle and reflex stiffness during stretches of the paretic elbow joint in individuals with chronic hemiparetic stroke, and to provide guidelines to streamline spasticity assessments. We applied ramp-and-hold elbow extension perturbations ranging from 15 to 150°/s over the full range of motion in 13 individuals with hemiparesis. After accounting for the effects of passive mechanical resistance, we modeled velocity-dependent reflex threshold angle and torque-angle slope to determine their correlation with overall resistance to movement. Reflex stiffness exhibited substantially greater velocity sensitivity than threshold angle, accounting for ~ 74% (vs. ~ 15%) of the overall velocity-dependent increases in movement resistance. Reflex stiffness is a sensitive descriptor of the overall velocity-dependence of movement resistance in spasticity. Clinical spasticity assessments can be streamlined using torque-angle slope, a measure of reflex stiffness, as their primary outcome measure, particularly at stretch velocities greater than 100°/s.

Changes in the Neural and Non-neural Related Properties of the Spastic Wrist Flexors After Treatment With Botulinum Toxin A in Post-stroke Subjects: An Optimization Study

Quantifying neural and non-neural contributions to the joint resistance in spasticity is essential for a better evaluation of different intervention strategies such as botulinum toxin A (BoTN-A). However, direct measurement of muscle mechanical properties and spasticity-related parameters in humans is extremely challenging. The aim of this study was to use a previously developed musculoskeletal model and optimization scheme to evaluate the changes of neural and non-neural related properties of the spastic wrist flexors during passive wrist extension after BoTN-A injection. Data of joint angle and resistant torque were collected from 21 chronic stroke patients before, and 4 and 12 weeks post BoTN-A injection using NeuroFlexor, which is a motorized force measurement device to passively stretch wrist flexors. The model was optimized by tuning the passive and stretch-related parameters to fit the measured torque in each participant. It was found that stroke survivors exhibited decreased neural components at 4 weeks post BoNT-A injection, which returned to baseline levels after 12 weeks. The decreased neural component was mainly due to the increased motoneuron pool threshold, which is interpreted as a net excitatory and inhibitory inputs to the motoneuron pool. Though the linear stiffness and viscosity properties of wrist flexors were similar before and after treatment, increased exponential stiffness was observed over time which may indicate a decreased range of motion of the wrist joint. Using a combination of modeling and experimental measurement, valuable insights into the treatment responses, i.e., transmission of motoneurons, are provided by investigating potential parameter changes along the stretch reflex pathway in persons with chronic stroke.

Neural and non-neural related properties in the spastic wrist flexors: An optimization study

Quantifying neural and non-neural contributions to increased joint resistance in spasticity is essential for a better understanding of its pathophysiological mechanisms and evaluating different intervention strategies. However, direct measurement of spasticity-related manifestations, e.g., motoneuron and biophysical properties in humans, is extremely challenging. In this vein, we developed a forward neuromusculoskeletal model that accounts for dynamics of muscle spindles, motoneuron pools, muscle activation and musculotendon of wrist flexors and relies on the joint angle and resistant torque as the only input measurement variables. By modeling the stretch reflex pathway, neural and non-neural related properties of the spastic wrist flexors were estimated during the wrist extension test. Joint angle and resistant torque were collected from 17 persons with chronic stroke and healthy controls using NeuroFlexor, a motorized force measurement device during the passive wrist extension test. The model was optimized by tuning the passive and stretch reflex-related parameters to fit the measured torque in each participant. We found that persons with moderate and severe spasticity had significantly higher stiffness than controls. Among subgroups of stroke survivors, the increased neural component was mainly due to a lower muscle spindle rate at 50% of the motoneuron recruitment. The motoneuron pool threshold was highly correlated to the motoneuron pool gain in all subgroups. The model can describe the overall resistant behavior of the wrist joint during the test. Compared to controls, increased resistance was predominantly due to higher elasticity and neural components. We concluded that in combination with the NeuroFlexor measurement, the proposed neuromusculoskeletal model and optimization scheme served as suitable tools for investigating potential parameter changes along the stretch-reflex pathway in persons with spasticity.

Computationally efficient modeling of proprioceptive signals in the upper limb for prostheses: a simulation study

Accurate models of proprioceptive neural patterns could 1 day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimization) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modeling. This paper uses and proposes a number of approximations and optimizations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed.

Development of a Haptic Elbow Spasticity Simulator (HESS) for improving accuracy and reliability of clinical assessment of spasticity

This paper presents the framework for developing a robotic system to improve accuracy and reliability of clinical assessment. Clinical assessment of spasticity tends to have poor reliability because of the nature of the in-person assessment. To improve accuracy and reliability of spasticity assessment, a haptic device, named the HESS (Haptic Elbow Spasticity Simulator) has been designed and constructed to recreate the clinical "feel" of elbow spasticity based on quantitative measurements. A mathematical model representing the spastic elbow joint was proposed based on clinical assessment using the Modified Ashworth Scale (MAS) and quantitative data (position, velocity, and torque) collected on subjects with elbow spasticity. Four haptic models (HMs) were created to represent the haptic feel of MAS 1, 1+, 2, and 3. The four HMs were assessed by experienced clinicians; three clinicians performed both in-person and haptic assessments, and had 100% agreement in MAS scores; and eight clinicians who were experienced with MAS assessed the four HMs without receiving any training prior to the test. Inter-rater reliability among the eight clinicians had substantial agreement (κ = 0.626). The eight clinicians also rated the level of realism ( 7.63 ± 0.92 out of 10) as compared to their experience with real patients.

Haptic recreation of elbow spasticity

The aim of this paper is to develop a haptic device capable of presenting standardized recreation of elbow spasticity. Using the haptic device, clinicians will be able to repeatedly practice the assessment of spasticity without requiring patient involvement, and these practice opportunities will help improve accuracy and reliability of the assessment itself. Haptic elbow spasticity simulator (HESS) was designed and prototyped according to mechanical requirements to recreate the feel of elbow spasticity. Based on the data collected from subjects with elbow spasticity, a mathematical model representing elbow spasticity is proposed. As an attempt to differentiate the feel of each score in Modified Ashworth Scale (MAS), parameters of the model were obtained respectively for three different MAS scores 1, 1+, and 2. The implemented haptic recreation was evaluated by experienced clinicians who were asked to give MAS scores by manipulating the haptic device. The clinicians who participated in the study were blinded to each other's scores and to the given models. They distinguished the three models and the MAS scores given to the recreated models matched 100% with the original MAS scores from the patients.

Validation of a New Biomechanical Model to Measure Muscle Tone in Spastic Muscles

Background. There is no easy and reliable method to measure spasticity, although it is a common and important symptom after a brain injury. Objective. The aim of this study was to develop and validate a new method to measure spasticity that can be easily used in clinical practice. Methods. A biomechanical model was created to estimate the components of the force resisting passive hand extension, namely ( a) inertia (IC), ( b) elasticity (EC), ( c) viscosity (VC), and ( d) neural components (NC). The model was validated in chronic stroke patients with varying degree of hand spasticity. Electromyography (EMG) was recorded to measure the muscle activity induced by the passive stretch. Results. The model was validated in 3 ways: ( a) NC was reduced after an ischemic nerve block, ( b) NC correlated with the integrated EMG across subjects and in the same subject during the ischemic nerve block, and ( c) NC was velocity dependent. In addition, the total resisting force and NC correlated with the modified Ashworth score. According to the model, the neural and nonneural components varied between patients. In most of the patients, but not in all, the NC dominated. Conclusions. The results suggest that the model allows valid measurement of spasticity in the upper extremity of chronic stroke patients and that it can be used to separate the neural component induced by the stretch reflex from resistance caused by altered muscle properties.

An EMG-driven musculoskeletal model for the estimation of biomechanical parameters of wrist flexors

A musculoskeletal model of wrist flexors comprising musculoskeletal dynamics and limb anatomy was experimentally validated with healthy subjects during maximum voluntary contractions. Electromyography signals recorded from flexors were used as input, while measured torques exerted by the hand were compared to the torques predicted by the model. The root mean square error and the normalized root mean square error calculated during estimation and validation phases were compared. In total, six subject-specific musculoskeletal parameters were estimated, while biomechanical indexes such as the operating range of the flexors, the stiffness of the wrist flexion musculotendon actuators, and the contribution of the muscle fibers to the joint moment were computed. Results are in agreement with previously published data.

The effect of elbow joint centre displacement on force generation and neural excitation

Joint centre displacement may occur following total elbow replacement due to aseptic loosening or surgical misalignment, and has been linked to implant failure. In this study, the effects of joint centre displacement were examined using a neuromusculoskeletal model of the elbow joint. Isometric contractions were simulated at a range of joint angles during elbow flexion and extension. Displacement of the joint centre affected the force-generating capacity about the joint, due to changes in both muscle lengths and moment arms. The magnitude and direction of the maximum joint reaction force were also altered, potentially contributing to aseptic loosening and compromising joint stability. The relationship between force generated and the level of neural excitation to the elbow flexor and extensor muscles was also affected, suggesting that altered neural control patterns could be required following joint centre displacement.