Position as Well as Velocity Dependence of Spasticity-Four-Dimensional Characterizations of Catch Angle

Isokinetic and electromyographic characterization of ankle plantarflexors' hypertonia in people with multiple sclerosis

BACKGROUND

This study aimed at quantifying ankle plantarflexors' resistance to passive motion (RPM) by isokinetic dynamometry and muscle activity through surface electromyography (sEMG) in persons with multiple sclerosis (PwMS) with limb stiffness and spasticity.

METHODS

Slow and fast ankle dorsiflexions (from 5°/s to 210°/s) were imparted passively by an isokinetic dynamometer, and sEMG activity of plantarflexors was recorded at the same time as the square root of the moving average. Based on RPM evaluated at 5°/s, ankles were classified as more- and less-resistant as measured by average peak torque (APT).

RESULTS

Measurements were obtained bilaterally from 24 PwMS (median EDSS: 5.5) with median Modified Ashworth Scale (MAS) score of 1.75. Compared to the lowest velocity inducing EMG-evident responses (120°/s), RPM increased significantly at 180°/s (+137.8 %; p < 0.0005) and 210°/s (+85.3 %; p < 0.0005) in the less-resistant side, and only at 210°/s (+113.8 %; p < 0.0005) in the more-resistant side. sEMG activity increased significantly and similarly between limbs at increasing velocities. Significant velocity-dependent increases were detected in both limbs, with no difference by side, at 180°/s (+34.5 %; p = 0.005) and 210°/s (+48.4 %; p = 0.004). Regression analyses confirmed side (β=0.542; p < 0.0001) and speed (β=0.238; p < 0.0001) as significant predictors of APT change, but only speed for sEMG (speed: β=0.215; p = 0.019; side: β=0.012; p = 0.893). Bivariate correlations revealed that RPM was associated negatively with MAS and positively with sEMG.

CONCLUSION

Spasticity presented bilaterally in PwMS, with different mixed pictures of passive and reflex stiffness, both requiring attention. Combining isokinetics and sEMG allows detecting even subtle, subclinical alterations that can prompt and drive early tailored management.

AAPM&R consensus guidance on spasticity assessment and management

BACKGROUND

The American Academy of Physical Medicine and Rehabilitation (AAPM&R) conducted a comprehensive review in 2021 to identify opportunities for enhancing the care of adult and pediatric patients with spasticity. A technical expert panel (TEP) was convened to develop consensus-based practice recommendations aimed at addressing gaps in spasticity care.

OBJECTIVE

To develop consensus-based practice recommendations to identify and address gaps in spasticity care.

METHODS

The Spasticity TEP engaged in a 16-month virtual meeting process, focusing on formulating search terms, refining research questions, and conducting a structured evidence review. Evidence quality was assessed by the AAPM&R Evidence, Quality and Performance Committee (EQPC), and a modified Delphi process was employed to achieve consensus on recommendation statements and evidence grading. The Strength of Recommendation Taxonomy (SORT) guided the rating of individual studies and the strength of recommendations.

RESULTS

The TEP approved five recommendations for spasticity management and five best practices for assessment and management, with one recommendation unable to be graded due to evidence limitations. Best practices were defined as widely accepted components of care, while recommendations required structured evidence reviews and grading. The consensus guidance statement represents current best practices and evidence-based treatment options, intended for use by PM&R physicians caring for patients with spasticity.

CONCLUSION

This consensus guidance provides clinicians with practical recommendations for spasticity assessment and management based on the best available evidence and expert opinion. Clinical judgment should be exercised, and recommendations tailored to individual patient needs, preferences, and risk profiles. The accompanying table summarizes the best practice recommendations for spasticity assessment and management, reflecting principles with little controversy in care delivery.

Using sEMG Signal Frequency to Evaluate Post-Stroke Elbow Spasticity

Spasticity is a motor disorder with high prevalence and critical consequences following a stroke. Reliable and sensitive measurements are important to guide the selection and evaluation of treatment strategies. Technology-assisted methods, such as the surface electromyography (sEMG) technique, have been developed to measure spasticity as sensitive and accurate alternatives to commonly used clinical scales. However, sEMG amplitude based measures may confound spasticity-induced muscle activities with other types of muscle contractions. This study thus introduces the idea of using sEMG frequency information to detect spasticity as a potential solution to overcome the limitations of existing sEMG based measures. The preliminary results of three patients demonstrate the possibility and future research directions for this approach.

Technology-assisted assessment of spasticity: a systematic review

BACKGROUND

Spasticity is defined as "a motor disorder characterised by a velocity dependent increase in tonic stretch reflexes (muscle tone) with exaggerated tendon jerks". It is a highly prevalent condition following stroke and other neurological conditions. Clinical assessment of spasticity relies predominantly on manual, non-instrumented, clinical scales. Technology based solutions have been developed in the last decades to offer more specific, sensitive and accurate alternatives but no consensus exists on these different approaches.

METHOD

A systematic review of literature of technology-based methods aiming at the assessment of spasticity was performed. The approaches taken in the studies were classified based on the method used as well as their outcome measures. The psychometric properties and usability of the methods and outcome measures reported were evaluated.

RESULTS

124 studies were included in the analysis. 78 different outcome measures were identified, among which seven were used in more than 10 different studies each. The different methods rely on a wide range of different equipment (from robotic systems to simple goniometers) affecting their cost and usability. Studies equivalently applied to the lower and upper limbs (48% and 52%, respectively). A majority of studies applied to a stroke population (N = 79). More than half the papers did not report thoroughly the psychometric properties of the measures. Analysis identified that only 54 studies used measures specific to spasticity. Repeatability and discriminant validity were found to be of good quality in respectively 25 and 42 studies but were most often not evaluated (N = 95 and N = 78). Clinical validity was commonly assessed only against clinical scales (N = 33). Sensitivity of the measure was assessed in only three studies.

CONCLUSION

The development of a large diversity of assessment approaches appears to be done at the expense of their careful evaluation. Still, among the well validated approaches, the ones based on manual stretching and measuring a muscle activity reaction and the ones leveraging controlled stretches while isolating the stretch-reflex torque component appear as the two promising practical alternatives to clinical scales. These methods should be further evaluated, including on their sensitivity, to fully inform on their potential.

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

Multimodal assessment of spasticity using a point-of-care instrumented glove to separate neural and biomechanical contributions

Accurate assessment of spasticity is crucial for physicians to select the most suitable treatment for patients. However, the current clinical practice standard is limited by imprecise assessment scales relying on perception. Here, we equipped the clinician with a portable, multimodal sensor glove to shift bedside evaluations from subjective perception to objective measurements. The measurements were correlated with biomechanical properties of muscles and revealed dynamic characteristics of spasticity, including catch symptoms and velocity-dependent resistance. Using the biomechanical data, a radar metric was developed for ranking severity in spastic knees and elbows. The continuous monitoring results during anesthesia induction enable the separation of neural and structural contributions to spasticity in 21 patients. This work delineated effects of reflex excitations from structural abnormalities, to classify underlying causes of spasticity that will inform treatment decisions for evidence-based patient care.

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Tool to shift from subjective scales to objective metrics in spasticity evaluation

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Develop a multifaceted metric to rank severity based on biomechanical properties

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Delineate effects of hyper-reflexes and structural abnormalities in spastic muscles

Assessment of the Mechanical Support Characteristics of a Light and Wearable Robotic Exoskeleton Prototype Applied to Upper Limb Rehabilitation

Robotic exoskeletons are active devices that assist or counteract the movements of the body limbs in a variety of tasks, including in industrial environments or rehabilitation processes. With the introduction of textile and soft materials in these devices, the effective motion transmission, mechanical support of the limbs, and resistance to physical disturbances are some of the most desirable structural features. This paper proposes an evaluation protocol and assesses the mechanical support properties of a servo-controlled robotic exoskeleton prototype for rehabilitation in upper limbs. Since this prototype was built from soft materials, it is necessary to evaluate the mechanical behavior in the areas that support the arm. Some of the rehabilitation-supporting movements such as elbow flexion and extension, as well as increased muscle tone (spasticity), are emulated. Measurements are taken using the reference supplied to the system's control stage and then compared with an external high-precision optical tracking system. As a result, it is evidenced that the use of soft materials provides satisfactory outcomes in the motion transfer and support to the limb. In addition, this study lays the groundwork for a future assessment of the prototype in a controlled laboratory environment using human test subjects.

Inter-rater reliability of the Australian Spasticity Assessment Scale in poststroke spasticity

To investigate the inter-rater reliability of the Australian Spasticity Assessment Scale (ASAS) in adult stroke patients with spasticity, two experienced clinicians rated the elbow flexor, wrist flexor, and ankle plantar flexor spasticity by using the ASAS in 85 persons with stroke. Unweighted and weighted (linear and quadratic) kappa statistics were used to calculate the inter-rater reliability for each muscle group. Unweighted kappa coefficients for elbow flexors (n = 83), wrist flexors (n = 80), and ankle plantar flexors (n = 77) were 0.67, 0.60, and 0.55, respectively. Linear and quadratic weighted kappa coefficients, respectively, were 0.77 and 0.87 for elbow flexors, 0.72 and 0.82 for wrist flexors, and 0.72 and 0.85 for ankle plantar flexors. The raters never disagreed by more than a single score in the rating of elbow flexors. On the contrary, the raters disagreed by more than a single score in three patients in the rating of ankle plantar flexors and in one patient in the rating of wrist flexors. The results suggested that inter-rater reliability of the ASAS differed according to the spastic muscle group assessed and the statistical method used. The strength of the agreement on the ASAS, an ordinal scale, ranged from good to very good when the weighted kappa values were considered.

Effect of Stretching of Spastic Elbow Under Intelligent Control in Chronic Stroke Survivors-A Pilot Study

Objective: To assess the short-term effects of strenuous dynamic stretching of the elbow joint using an intelligent stretching device in chronic spastic stroke survivors.

Methods: The intelligent stretching device was utilized to provide a single session of intensive stretching to the spastic elbow joint in the sagittal plane (i.e., elbow flexion and extension). The stretching was provided to the extreme range, safely, with control of the stretching velocity and torque to increase the joint range of motion (ROM) and reduce spasticity and joint stiffness. Eight chronic stroke survivors (age: 52.6 ± 8.2 years, post-stroke duration: 9.5 ± 3.6 years) completed a single 40-min stretching intervention session. Elbow passive and active ROM, strength, passive stiffness (quantifying the non-reflex component of spasticity), and instrumented tendon reflex test of the biceps tendon (quantifying the reflex component of the spasticity) were measured before and after stretching.

Results: After stretching, there was a significant increase in passive ROM of elbow flexion (p = 0.021, r = 0.59) and extension (p = 0.026, r = 0.59). Also, elbow active ROM and the spastic elbow flexors showed a trend of increase in their strength.

Conclusion: The intelligent stretching had a short-term positive influence on the passive movement ROM. Hence, intelligent stretching can potentially be used to repeatedly and regularly stretch spastic elbow joints, which subsequently helps to reduce upper limb impairments post-stroke.

VALIDITY AND TEST–RETEST RELIABILITY OF AN INTELLIGENT ROBOTIC SHOULDER JOINT KINEMATICS SYSTEM FOR REHABILITATION

The presence of normal upper limb arm swing movement is considered an important gait movement that affects the selective coordinated locomotor control of the shoulder, elbow, and wrist joint movements. However, in patients with neurological disorders, flexor synergy is characterized by decreased selective neuromuscular control and reciprocal disinhibition of the wrist flexor muscles associated with spasticity or shortness. This research aimed to demonstrate the reliability, validity, and feasibility of the progressive exoskeletal robotic shoulder joint kinematics system. The robotic shoulder joint kinematics system comprises a gait function-retraining robot designed to provide arm swing. The changes in the shoulder joint angle between ImageJ motion analysis software and robotic shoulder joint kinematics system were compared in this research to investigate the reliability and validity of the latter. The linear regression analysis revealed good correlation between the measured angles and the shoulder angle data ([Formula: see text]). Furthermore, the test–retest reliability test demonstrated excellent reliability ([Formula: see text]). The robotic shoulder joint kinematics system generated successful arm swing during the locomotion and range of motion training of the shoulder.

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.

VMD-based denoising methods for surface electromyography signals

OBJECTIVE

Since noise is inevitably introduced during the measurement process of surface electromyographic (sEMG) signals, two novel methods for denoising based on the variational mode decomposition (VMD) method were proposed in this work. Prior to this study, there has been no literature relating to how VMD is applied to sEMG denoising.

APPROACH

The first proposed method uses the VMD method to decompose the signal into multiple variational mode functions (VMFs), each of which has its own center frequency and narrow band, and then the wavelet soft thresholding (WST) method is applied to each VMF. This method is termed the VMD-WST. The second proposed method uses the VMD method to decompose the signal into multiple VMFs, and then the soft interval thresholding (SIT) method is performed on each VMF, which is abbreviated as VMD-SIT. Ten healthy subjects and ten stroke patients participated in the experiment, and the sEMG signals of bicep brachii were measured and analyzed. In this paper, three methods are used for quantitative evaluation of the filtering performance: the signal-to-noise ratio (SNR), root mean square error and R-squared value. The proposed two methods (VMD-WST, VMD-SIT) are compared with the empirical mode decomposition (EMD) method and the wavelet method.

MAIN RESULTS

The experimental results showed that the VMD-WST and VMD-SIT methods can effectively filter the noise effect, and the denoising effects were better than the EMD method and the wavelet method. The VMD-SIT method has the best performance.

SIGNIFICANCE

This study provides a new means of eliminating the noise of sEMG signals based on the VMD method, and it can be applied in the fields of limb movement classification, disease diagnosis, human-machine interaction and so on.