Quantification of Upper-Limb Motor Function for Stroke Rehabilitation Through Manifold Similarity of Muscle Synergy

 I have no clue. Ask your competent? doctor how this is going to get you 100% recovered. I consider assessments worthless unless they point directly to the EXACT STROKE REHAB PROTOCOLS that get you recovered!

Quantification of Upper-Limb Motor Function for Stroke Rehabilitation Through Manifold Similarity of Muscle Synergy

Xiao Li; Hong Zeng; Yongqiang Li; Aiguo Song

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Abstract:

Quantifying post-stroke patient motor function is important for assessing rehabilitation progress and optimizing the behavior of adaptive rehabilitation robots. To this end, researchers have increasing turned to the concept of muscle synergies, which encodes the simplified neuromuscular control strategy employed by the central nervous system in response to post-stroke impairment. In essence, the assessment metrics should possess two key attributes: the ability to differentiate between individuals in the pathological and healthy groups, and the capacity to yield consistent measurements within the same individual, thereby facilitating the refinement of adaptive control algorithms. Recent findings have indicated that employing manifold similarity measurements can enhance the class separability and intra-class compactness for the classification/clustering algorithm. Consequently, we hypothesize that evaluating synergy and synergy activation similarities, while considering the underlying manifold structure, will render a more sensitive and reliable approach for quantifying motor function in post-stroke patients. To validate our hypothesis, we conducted a study involving twenty healthy subjects and ten post-stroke patients. Our results demonstrate that the utilization of manifold similarities leads to superior outcomes compared to conventional metrics based on muscle synergy. Specifically, we observed higher sensitivity ( gw v.s. Sw , 0.0457 v.s. 0.0030 ), greater intra-subject reliability ( gc v.s. Sc , 0.6060 v.s. 0.1081 ), and stronger correlations with clinical scores ( gw v.s. Sw , 0.7588 v.s. 0.6249 ) than conventional metrics. Therefore, the proposed similarity metrics may be promising for transferring to adaptive control of rehabilitation robots.

Published in: IEEE Robotics and Automation Letters ( Early Access )

Psychometric Properties of a New Measure of Upper Limb Performance in Post-Stroke Individuals: Trunk-Based Index of Performance

Assessing recovery is so damn fucking easy. You ask the survivor: 'Are you 100% recovered?' 'Y/N'. Quit overthinking this.

Psychometric Properties of a New Measure of Upper Limb Performance in Post-Stroke Individuals: Trunk-Based Index of Performance

Daniele Piscitelli, PhD https://orcid.org/0000-0002-5240-3798, Melanie C. Baniña, PhD https://orcid.org/0000-0002-6055-0229, […], and Mindy F. Levin, PhD https://orcid.org/0000-0002-8965-7484 Mindy.levin@mcgill.ca+2View all authors and affiliations

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https://doi.org/10.1177/15459683221143462

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Abstract

Background

Several measures of upper limb (UL) motor tasks have been developed to characterize recovery. However, UL performance and movement quality measures in isolation may not provide a true profile of functional recovery.

Objective

To investigate the measurement properties of a new trunk-based Index of Performance (IPt) of the UL combining endpoint performance (accuracy and speed) and movement quality (trunk displacement) in stroke.

Methods

Participants with stroke (n = 25, mean time since stroke: 18.7 ± 17.2 months) performed a reaching task over 3 evaluation sessions. The IPt was computed based on Fitts’ Law that incorporated endpoint accuracy and speed corrected by the amount of trunk displacement. Test–retest reliability was analyzed using intraclass correlation coefficient (ICC) and Bland–Altman plots. Standard error of measurement (SEM) and Minimal Detectable Change (MDC) were determined. Validity was investigated through the relationship between IPt, Fugl–Meyer Assessment (FMA-UE), and Action Research Arm Test (ARAT), as well as the ability of IPt to distinguish between levels of UL motor impairment severity.

Results

Test–retest reliability was excellent (ICC = .908, 95% CI: 0.807-0.96). Bland–Altman did not show systematic differences. SEM and MDC₉₅ were 14% and 39%, respectively. Construct validity was satisfactory. The IPt showed low-to-moderate relationships with FMA-UE (R² ranged from .236 to .428) and ARAT (R² ranged from .277 to .306). IPt scores distinguished between different levels of UL severity.

Conclusions

The IPt showed evidence of good reliability, and initial validity. The IPt may be a promising tool for research and clinical settings. Further research is warranted to investigate its validity with additional comparator instruments.

Introduction

The first consensus meeting of the Stroke Recovery and Rehabilitation Roundtable (SRRR) concluded that more accurate and predictive kinematic measures of upper limb (UL) function need to be developed to distinguish between changes in behavior due to functional recovery or compensation.¹ They concluded that more informative measures of motor behavior are vital to the understanding of neural repair processes and training effects on motor action.^2,3 Consequently, the second SRRR consensus panel recommended 4 performance “assays” to characterize real change at the body structure/function level and 1 functional task at the activity level.⁴ In this context, “assay” refers to a movement component that is applicable to a wide range of motor actions or tasks. Assays were chosen based on their ability to quantify the execution of a movement component outside the context of the performance of any specific motor task. They include a measure of coordination between shoulder and elbow movements; finger force individuation; maximal isometric grip and pinch strength. At the activity level, evaluation of endpoint kinematics (eg, speed, smoothness), and joint and trunk displacements during a standardized reaching task were recommended.⁴

Although deviations from typical movement patterns provide information about the motor elements contributing to task performance, it is unclear how individual elements, including the presence of motor compensations, reflect skilled movement. Regarding UL reaching, skilled movement has been defined as an action that is executed at a short latency with high speed and precision.⁵ This is often referred to as the speed–accuracy trade-off relationship, based on the concept of Fitts’ law.⁶ Fitts’ Law results in a measure that integrates the time to move the hand to the target as a function of the hand-to-target distance and the target width, but does not account for the influence of compensatory trunk movements. Quantification of compensatory movement is vital to the development of a metric for skilled reaching since, in contrast to healthy participants, in patients with moderate-to-severe stroke, endpoint precision is often influenced by trunk displacement.^7,8

We propose a novel application of Fitts’ Law characterizing skilled reaching in people with stroke, that also accounts for the amount of trunk displacement used during reaching, called the Trunk-based Index of Performance, IPt. The new measure incorporates trunk displacement in the classic Index of Performance (IP) measure, which is expressed as the Index of Difficulty (ID) of the task divided by the Movement Time (MT; IP = ID/MT), where ID is a function of the reaching distance (D) to the target divided by the target width (W), such that ID = log₂ (2D/W).

The classic IP has been used in numerous experiments in motor control, psychology, and neuroscience.^9,10 However, it has received less attention in studies of the recovery of reaching skill in the neurorehabilitation literature¹¹ (but see Smits-Engelsman et al¹²), in which motor skill is usually characterized as smaller endpoint error and/or faster movement speed.¹³ The new measure, IPt, may be better able to capture real-world manifestations of motor skill learning, where increased skill is inferred if both variables change in the expected direction (faster speed, increased precision),¹⁴ with less trunk compensation.

The study goal was to determine the clinimetric properties, that is, reliability (ie, test–retest reliability, measurement error) and validity of IPt as a measure of motor skill in people with chronic stroke performing a standardized reaching task. We hypothesized that IPt would show high test–retest reliability and discriminate between participants with mild or moderate-to-severe hemiparesis. Preliminary results have appeared in abstract form.¹⁵

 

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