Muscle Synergies and Clinical Outcome Measures Describe Different Factors of Upper Limb Motor Function in Stroke Survivors Undergoing Rehabilitation in a Virtual Reality Environment

Recent studies have investigated muscle synergies as biomarkers for stroke, but it remains controversial if muscle synergies and clinical observation convey the same information on motor impairment. We aim to identify whether muscle synergies and clinical scales convey the same information or not. Post-stroke patients were administered an upper limb treatment. Before (T0) and after (T1) treatment, we assessed motor performance with clinical scales and motor output with EMG-derived muscle synergies. We implemented an exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA) to identify the underlying relationships among all variables, at T0 and T1, and a general linear regression model to infer any relationships between the similarity between the affected and unaffected synergies (Median-sp) and clinical outcomes at T0. Clinical variables improved with rehabilitation whereas muscle-synergy parameters did not show any significant change. EFA and CFA showed that clinical variables and muscle-synergy parameters (except Median-sp) were grouped into different factors. Regression model showed that Median-sp could be well predicted by clinical scales. The information underlying clinical scales and muscle synergies are therefore different. However, clinical scales well predicted the similarity between the affected and unaffected synergies. Our results may have implications on personalizing rehabilitation protocols.

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Assessing User Transparency with Muscle Synergies during Exoskeleton-Assisted Movements: A Pilot Study on the LIGHTarm Device for Neurorehabilitation

Applied Bionics and Biomechanics ◽

10.1155/2018/7647562 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Andrea Chiavenna ◽

Alessandro Scano ◽

Matteo Malosio ◽

Lorenzo Molinari Tosatti ◽

Franco Molteni

Keyword(s):

Pilot Study ◽

Upper Limb ◽

Surface Electromyography ◽

Healthy Subjects ◽

Daily Life ◽

Muscle Synergy ◽

Muscle Synergies ◽

Gravity Compensation ◽

Weight Support ◽

Desirable Feature

Exoskeleton devices for upper limb neurorehabilitation are one of the most exploited solutions for the recovery of lost motor functions. By providing weight support, passively compensated exoskeletons allow patients to experience upper limb training. Transparency is a desirable feature of exoskeletons that describes how the device alters free movements or interferes with spontaneous muscle patterns. A pilot study on healthy subjects was conducted to evaluate the feasibility of assessing transparency in the framework of muscle synergies. For such purpose, the LIGHTarm exoskeleton prototype was used. LIGHTarm provides gravity support to the upper limb during the execution of movements in the tridimensional workspace. Surface electromyography was acquired during the execution of three daily life movements (reaching, hand-to-mouth, and hand-to-nape) in three different conditions: free movement, exoskeleton-assisted (without gravity compensation), and exoskeleton-assisted (with gravity compensation) on healthy people. Preliminary results suggest that the muscle synergy framework may provide valuable assessment of user transparency and weight support features of devices aimed at rehabilitation.

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Validity, reliability, and sensitivity to motor impairment severity of a multi-touch app designed to assess hand mobility, coordination, and function after stroke

Journal of NeuroEngineering and Rehabilitation ◽

10.1186/s12984-021-00865-9 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Sara Mollà-Casanova ◽

Roberto Llorens ◽

Adrián Borrego ◽

Bárbara Salinas-Martínez ◽

Pilar Serra-Añó

Keyword(s):

Upper Limb ◽

Convergent Validity ◽

Hand Function ◽

Motor Impairment ◽

Minimal Detectable Change ◽

Motor Impairments ◽

Clinical Scales ◽

Clinical Assessments ◽

And Function ◽

Impairment Severity

Abstract Background The assessment of upper-limb motor impairments after stroke is usually performed using clinical scales and tests, which may lack accuracy and specificity and be biased. Although some instruments exist that are capable of evaluating hand functions and grasping during functional tasks, hand mobility and dexterity are generally either not specifically considered during clinical assessments or these examinations lack accuracy. This study aimed to determine the convergent validity, reliability, and sensitivity to impairment severity after a stroke of a dedicated, multi-touch app, named the Hand Assessment Test. Methods The hand mobility, coordination, and function of 88 individuals with stroke were assessed using the app, and their upper-limb functions were assessed using the Fugl-Meyer Assessment for Upper Extremity, the Jebsen-Taylor Hand Function Test, the Box and Block Test, and the Nine Hole Peg Test. Twenty-three participants were further considered to investigate inter- and intra-rater reliability, standard error of measurement, and the minimal detectable change threshold of the app. Finally, participants were categorized according to motor impairment severity and the sensitivity of the app relative to these classifications was investigated. Results Significant correlations, of variable strengths, were found between the measurements performed by the app and the clinical scales and tests. Variable reliability, ranging from moderate to excellent, was found for all app measurements. Exercises that involved tapping and maximum finger-pincer grasp were sensitive to motor impairment severity. Conclusions The convergent validity, reliability, and sensitivity to motor impairment severity of the app, especially of those exercises that involved tapping and the maximum extension of the fingers, together with the widespread availability of the app, could support the use of this and similar apps to complement conventional clinical assessments of hand function after stroke.

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Upper-Limb Muscle Synergy Features in Human-Robot Interaction with Circle-Drawing Movements

Applied Bionics and Biomechanics ◽

10.1155/2021/8850785 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Cheng Wang ◽

Shutao Zhang ◽

Jingyan Hu ◽

Zhejing Huang ◽

Changcheng Shi

Keyword(s):

Motor Function ◽

Upper Limb ◽

Healthy Subjects ◽

Human Robot Interaction ◽

Muscle Synergy ◽

Muscle Synergies ◽

Robot Interaction ◽

Rehabilitation Robots ◽

Circle Drawing ◽

Semg Signals

The upper-limb rehabilitation robots can be developed as an efficient tool for motor function assessments. Circle-drawing has been used as a specific task for robot-based motor function measurement. The upper-limb movement-related kinematic and kinetic parameters measured by motion and force sensors embedded in the rehabilitation robots have been widely studied. However, the muscle synergies characterized by multiple surface electromyographic (sEMG) signals in upper limbs during human-robot interaction (HRI) with circle-drawing movements are rarely investigated. In this research, the robot-assisted and constrained circle-drawing movements for upper limb were used to increase the consistency of muscle synergy features. Both clockwise and counterclockwise circle-drawing tasks were implemented by all healthy subjects using right hands. The sEMG signals were recorded from six muscles in upper limb, and nonnegative matrix factorization (NMF) analysis was utilized to obtain muscle synergy information. Both synergy pattern and activation coefficient were calculated to represent the spatial and temporal features of muscle synergies, respectively. The results obtained from the experimental study confirmed that high structural similarity of muscle synergies was found among the subjects during HRI with circle-drawing movement by healthy subjects, which indicates healthy people may share a common underlying muscle control mechanism during constrained upper-limb circle-drawing movement. This study indicates the muscle synergy analysis during the HRI with constrained circle-drawing movement could be considered as a task for upper-limb motor function assessment.

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Sensory-Based Priming for Upper Extremity Hemiparesis After Stroke: A Scoping Review

OTJR Occupation Participation and Health ◽

10.1177/15394492211032606 ◽

2021 ◽

pp. 153944922110326

Author(s):

Mary E. Stoykov ◽

Courtney Heidle ◽

Shamshir Kang ◽

Lisa Lodesky ◽

Lindsay E. Maccary ◽

...

Keyword(s):

Electrical Stimulation ◽

Motor Skills ◽

Upper Limb ◽

Scoping Review ◽

Web Of Science ◽

Motor Impairment ◽

Cochrane Collaboration ◽

Prisma Statement ◽

Meta Analyses ◽

The Cochrane Collaboration

Sensory priming is a technique to facilitate neuroplasticity and improve motor skills after injury. Common sensory priming modalities include peripheral nerve stimulation/somatosensory electrical stimulation (PNS/SES), transient functional deafferentation (TFD), and vibration. The aim of this study was to determine whether sensory priming with a motor intervention results in improved upper limb motor impairment or function after stroke. PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and EMBASE were the databases used to search the literature in July 2020. This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and recommendations for the Cochrane collaboration. In total, 30 studies were included in the analysis: three studies examined TFD, 16 examined PNS/SES, 10 studied vibration, and one combined the three stimulation techniques. Most studies reported significant improvements for participants receiving sensory priming. Given the low risk, it may be advantageous to use sensory-based priming prior to or concurrent with upper limb training after stroke.

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Effect of post-stroke spasticity on voluntary movement of the upper limb

Journal of NeuroEngineering and Rehabilitation ◽

10.1186/s12984-021-00876-6 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Hadar Lackritz ◽

Yisrael Parmet ◽

Silvi Frenkel-Toledo ◽

Melanie C. Baniña ◽

Nachum Soroker ◽

...

Keyword(s):

Upper Limb ◽

Target Location ◽

Distance Measure ◽

Movement Time ◽

Motor Impairment ◽

Reach To Grasp ◽

Motion Patterns ◽

Post Stroke ◽

The Impact ◽

Elbow Motion

Abstract Background Hemiparesis following stroke is often accompanied by spasticity. Spasticity is one factor among the multiple components of the upper motor neuron syndrome that contributes to movement impairment. However, the specific contribution of spasticity is difficult to isolate and quantify. We propose a new method of quantification and evaluation of the impact of spasticity on the quality of movement following stroke. Methods Spasticity was assessed using the Tonic Stretch Reflex Threshold (TSRT). TSRT was analyzed in relation to stochastic models of motion to quantify the deviation of the hemiparetic upper limb motion from the normal motion patterns during a reaching task. Specifically, we assessed the impact of spasticity in the elbow flexors on reaching motion patterns using two distinct measures of the ‘distance’ between pathological and normal movement, (a) the bidirectional Kullback–Liebler divergence (BKLD) and (b) Hellinger’s distance (HD). These measures differ in their sensitivity to different confounding variables. Motor impairment was assessed clinically by the Fugl-Meyer assessment scale for the upper extremity (FMA-UE). Forty-two first-event stroke patients in the subacute phase and 13 healthy controls of similar age participated in the study. Elbow motion was analyzed in the context of repeated reach-to-grasp movements towards four differently located targets. Log-BKLD and HD along with movement time, final elbow extension angle, mean elbow velocity, peak elbow velocity, and the number of velocity peaks of the elbow motion were computed. Results Upper limb kinematics in patients with lower FMA-UE scores (greater impairment) showed greater deviation from normality when the distance between impaired and normal elbow motion was analyzed either with the BKLD or HD measures. The severity of spasticity, reflected by the TSRT, was related to the distance between impaired and normal elbow motion analyzed with either distance measure. Mean elbow velocity differed between targets, however HD was not sensitive to target location. This may point at effects of spasticity on motion quality that go beyond effects on velocity. Conclusions The two methods for analyzing pathological movement post-stroke provide new options for studying the relationship between spasticity and movement quality under different spatiotemporal constraints.

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