A functional analysis-based approach to quantify upper limb impairment level in chronic stroke patients: a pilot study

Experimental Validation of an Upper Limb Benchmarking Framework in Healthy and Post-Stroke Individuals: A Pilot Study

In the context of neurorehabilitation, there have been rapid and continuous improvements in sensors-based clinical tools to quantify limb performance. As a result of the increasing integration of technologies in the assessment procedure, the need to integrate evidence-based medicine with benchmarking has emerged in the scientific community. In this work, we present the experimental validation of our previously proposed benchmarking scheme for upper limb capabilities in terms of repeatability, reproducibility, and clinical meaningfulness. We performed a prospective multicenter study on neurologically intact young and elderly subjects and post-stroke patients while recording kinematics and electromyography. 60 subjects (30 young healthy, 15 elderly healthy, and 15 post-stroke) completed the benchmarking protocol. The framework was repeatable among different assessors and instrumentation. Age did not significantly impact the performance indicators of the scheme for healthy subjects. In post-stroke subjects, the movements presented decreased smoothness and speed, the movement amplitude was reduced, and the muscular activation showed lower power and lower intra-limb coordination. We revised the original framework reducing it to three motor skills, and we extracted 14 significant performance indicators with a good correlation with the ARAT clinical scale. The applicability of the scheme is wide, and it may be considered a valuable tool for upper limb functional evaluation in the clinical routine.

A guide to inter-joint coordination characterization for discrete movements: a comparative study

Characterizing human movement is essential for understanding movement disorders, evaluating progress in rehabilitation, or even analyzing how a person adapts to the use of assistive devices. Thanks to the improvement of motion capture technology, recording human movement has become increasingly accessible and easier to conduct. Over the last few years, multiple methods have been proposed for characterizing inter-joint coordination. Despite this, there is no real consensus regarding how these different inter-joint coordination metrics should be applied when analyzing the coordination of discrete movement from kinematic data. In this work, we consider 12 coordination metrics identified from the literature and apply them to a simulated dataset based on reaching movements using two degrees of freedom. Each metric is evaluated according to eight criteria based on current understanding of human motor control physiology, i.e, each metric is graded on how well it fulfills each of these criteria. This comparative analysis highlights that no single inter-joint coordination metric can be considered as ideal. Depending on the movement characteristics that one seeks to understand, one or several metrics among those reviewed here may be pertinent in data analysis. We propose four main factors when choosing a metric (or a group of metrics): the importance of temporal vs. spatial coordination, the need for result explainability, the size of the dataset, and the computational resources. As a result, this study shows that extracting the relevant characteristics of inter-joint coordination is a scientific challenge and requires a methodical choice. As this preliminary study is conducted on a limited dataset, a more comprehensive analysis, introducing more variability, could be complementary to these results.

A unified scheme for the benchmarking of upper limb functions in neurological disorders

BACKGROUND

In neurorehabilitation, we are witnessing a growing awareness of the importance of standardized quantitative assessment of limb functions. Detailed assessments of the sensorimotor deficits following neurological disorders are crucial. So far, this assessment has relied mainly on clinical scales, which showed several drawbacks. Different technologies could provide more objective and repeatable measurements. However, the current literature lacks practical guidelines for this purpose. Nowadays, the integration of available metrics, protocols, and algorithms into one harmonized benchmarking ecosystem for clinical and research practice is necessary.

METHODS

This work presents a benchmarking framework for upper limb capacity. The scheme resulted from a multidisciplinary and iterative discussion among several partners with previous experience in benchmarking methodology, robotics, and clinical neurorehabilitation. We merged previous knowledge in benchmarking methodologies for human locomotion and direct clinical and engineering experience in upper limb rehabilitation. The scheme was designed to enable an instrumented evaluation of arm capacity and to assess the effectiveness of rehabilitative interventions with high reproducibility and resolution. It includes four elements: (1) a taxonomy for motor skills and abilities, (2) a list of performance indicators, (3) a list of required sensor modalities, and (4) a set of reproducible experimental protocols.

RESULTS

We proposed six motor primitives as building blocks of most upper-limb daily-life activities and combined them into a set of functional motor skills. We identified the main aspects to be considered during clinical evaluation, and grouped them into ten motor abilities categories. For each ability, we proposed a set of performance indicators to quantify the proposed ability on a quantitative and high-resolution scale. Finally, we defined the procedures to be followed to perform the benchmarking assessment in a reproducible and reliable way, including the definition of the kinematic models and the target muscles.

CONCLUSIONS

This work represents the first unified scheme for the benchmarking of upper limb capacity. To reach a consensus, this scheme should be validated with real experiments across clinical conditions and motor skills. This validation phase is expected to create a shared database of human performance, necessary to have realistic comparisons of treatments and drive the development of new personalized technologies.

Depth Estimation for Egocentric Rehabilitation Monitoring Using Deep Learning Algorithms

Upper limb impairment is one of the most common problems for people with neurological disabilities, affecting their activity, quality of life (QOL), and independence. Objective assessment of upper limb performance is a promising way to help patients with neurological upper limb disorders. By using wearable sensors, such as an egocentric camera, it is possible to monitor and objectively assess patients’ actual performance in activities of daily life (ADLs). We analyzed the possibility of using Deep Learning models for depth estimation based on a single RGB image to allow the monitoring of patients with 2D (RGB) cameras. We conducted experiments placing objects at different distances from the camera and varying the lighting conditions to evaluate the performance of the depth estimation provided by two deep learning models (MiDaS & Alhashim). Finally, we integrated the best performing model for depth-estimation (MiDaS) with other Deep Learning models for hand (MediaPipe) and object detection (YOLO) and evaluated the system in a task of hand-object interaction. Our tests showed that our final system has a 78% performance in detecting interactions, while the reference performance using a 3D (depth) camera is 84%.

A low-dimensional representation of arm movements and hand grip forces in post-stroke individuals

Characterizing post-stroke impairments in the sensorimotor control of arm and hand is essential to better understand altered mechanisms of movement generation. Herein, we used a decomposition algorithm to characterize impairments in end-effector velocity and hand grip force data collected from an instrumented functional task in 83 healthy control and 27 chronic post-stroke individuals with mild-to-moderate impairments. According to kinematic and kinetic raw data, post-stroke individuals showed reduced functional performance during all task phases. After applying the decomposition algorithm, we observed that the behavioural data from healthy controls relies on a low-dimensional representation and demonstrated that this representation is mostly preserved post-stroke. Further, it emerged that reduced functional performance post-stroke correlates to an abnormal variance distribution of the behavioural representation, except when reducing hand grip forces. This suggests that the behavioural repertoire in these post-stroke individuals is mostly preserved, thereby pointing towards therapeutic strategies that optimize movement quality and the reduction of grip forces to improve performance of daily life activities post-stroke.

Somatosensory Cortex Repetitive Transcranial Magnetic Stimulation and Associative Sensory Stimulation of Peripheral Nerves Could Assist Motor and Sensory Recovery After Stroke

Background

We investigated whether transcranial magnetic stimulation (rTMS) over the primary somatosensory cortex (S1) and sensory stimulation (SS) could promote upper limb recovery in participants with subacute stroke.

Methods

Participants were randomized into four groups: rTMS/Sham SS, Sham rTMS/SS, rTMS/SS, and control group (Sham rTMS/Sham SS). Participants underwent ten sessions of sham or active rTMS over S1 (10 Hz, 1,500 pulses, 120% of resting motor threshold, 20 min), followed by sham or active SS. The SS involved active sensory training (exploring features of objects and graphesthesia, proprioception exercises), mirror therapy, and Transcutaneous electrical nerve stimulation (TENS) in the region of the median nerve in the wrist (stimulation intensity as the minimum intensity at which the participants reported paresthesia; five electrical pulses of 1 ms duration each at 10 Hz were delivered every second over 45 min). Sham stimulations occurred as follows: Sham rTMS, coil was held while disconnected from the stimulator, and rTMS noise was presented with computer loudspeakers with recorded sound from a real stimulation. The Sham SS received therapy in the unaffected upper limb, did not use the mirror and received TENS stimulation for only 60 seconds. The primary outcome was the Body Structure/Function: Fugl-Meyer Assessment (FMA) and Nottingham Sensory Assessment (NSA); the secondary outcome was the Activity/Participation domains, assessed with Box and Block Test, Motor Activity Log scale, Jebsen-Taylor Test, and Functional Independence Measure.

Results

Forty participants with stroke ischemic (n = 38) and hemorrhagic (n = 2), men (n = 19) and women (n = 21), in the subacute stage (10.6 ± 6 weeks) had a mean age of 62.2 ± 9.6 years, were equally divided into four groups (10 participants in each group). Significant somatosensory improvements were found in participants receiving active rTMS and active SS, compared with those in the control group (sham rTMS with sham SS). Motor function improved only in participants who received active rTMS, with greater effects when active rTMS was combined with active SS.

Conclusion

The combined use of SS with rTMS over S1 represents a more effective therapy for increasing sensory and motor recovery, as well as functional independence, in participants with subacute stroke.

Clinical Trial Registration

[clinicaltrials.gov], identifier [NCT03329807].

Characterization of stroke-related upper limb motor impairments across various upper limb activities by use of kinematic core set measures

Background

Upper limb kinematic assessments provide quantifiable information on qualitative movement behavior and limitations after stroke. A comprehensive characterization of spatiotemporal kinematics of stroke subjects during upper limb daily living activities is lacking. Herein, kinematic expressions were investigated with respect to different movement types and impairment levels for the entire task as well as for motion subphases.

Method

Chronic stroke subjects with upper limb movement impairments and healthy subjects performed a set of daily living activities including gesture and grasp movements. Kinematic measures of trunk displacement, shoulder flexion/extension, shoulder abduction/adduction, elbow flexion/extension, forearm pronation/supination, wrist flexion/extension, movement time, hand peak velocity, number of velocity peaks (NVP), and spectral arc length (SPARC) were extracted for the whole movement as well as the subphases of reaching distally and proximally. The effects of the factors gesture versus grasp movements, and the impairment level on the kinematics of the whole task were tested. Similarities considering the metrics expressions and relations were investigated for the subphases of reaching proximally and distally between tasks and subgroups.

Results

Data of 26 stroke and 5 healthy subjects were included. Gesture and grasp movements were differently expressed across subjects. Gestures were performed with larger shoulder motions besides higher peak velocity. Grasp movements were expressed by larger trunk, forearm, and wrist motions. Trunk displacement, movement time, and NVP increased and shoulder flexion/extension decreased significantly with increased impairment level. Across tasks, phases of reaching distally were comparable in terms of trunk displacement, shoulder motions and peak velocity, while reaching proximally showed comparable expressions in trunk motions. Consistent metric relations during reaching distally were found between shoulder flexion/extension, elbow flexion/extension, peak velocity, and between movement time, NVP, and SPARC. Reaching proximally revealed reproducible correlations between forearm pronation/supination and wrist flexion/extension, movement time and NVP.

Conclusion

Spatiotemporal differences between gestures versus grasp movements and between different impairment levels were confirmed. The consistencies of metric expressions during movement subphases across tasks can be useful for linking kinematic assessment standards and daily living measures in future research and performing task and study comparisons.

Trial registration: ClinicalTrials.gov Identifier NCT03135093. Registered 26 April 2017, https://clinicaltrials.gov/ct2/show/NCT03135093.

U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions

BACKGROUND

Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a stroke), can help to devise effective tools for a quantitative evaluation of the impaired conditions, and to properly inform the rehabilitative process. Furthermore, the design and control of mechatronic devices can also benefit from such neuroscientific outcomes, with important implications for assistive and rehabilitation robotics and advanced human-machine interaction. To reach these goals, we believe that an exhaustive data collection on human behavior is a mandatory step. For this reason, we release U-Limb, a large, multi-modal, multi-center data collection on human upper limb movements, with the aim of fostering trans-disciplinary cross-fertilization.

CONTRIBUTION

This collection of signals consists of data from 91 able-bodied and 65 post-stroke participants and is organized at 3 levels: (i) upper limb daily living activities, during which kinematic and physiological signals (electromyography, electro-encephalography, and electrocardiography) were recorded; (ii) force-kinematic behavior during precise manipulation tasks with a haptic device; and (iii) brain activity during hand control using functional magnetic resonance imaging.

Measures of Interjoint Coordination Post-stroke Across Different Upper Limb Movement Tasks

Background: Deficits in interjoint coordination, such as the inability to move out of synergy, are frequent symptoms in stroke subjects with upper limb impairments that hinder them from regaining normal motor function. Kinematic measurements allow a fine-grained assessment of movement pathologies, thereby complementing clinical scales, like the Fugl–Meyer Motor Assessment of the Upper Extremity (FMMA-UE). The study goal was to investigate the effects of the performed task, the tested arm, the dominant affected hand, upper limb function, and age on spatiotemporal parameters of the elbow, shoulder, and trunk. The construct validity of the metrics was examined by relating them with each other, the FMMA-UE, and its arm section.

Methods: This is a cross-sectional observational study including chronic stroke patients with mild to moderate upper limb motor impairment. Kinematic measurements were taken using a wearable sensor suit while performing four movements with both upper limbs: (1) isolated shoulder flexion, (2) pointing, (3) reach-to-grasp a glass, and (4) key insertion. The kinematic parameters included the joint ranges of shoulder abduction/adduction, shoulder flexion/extension, and elbow flexion/extension; trunk displacement; shoulder–elbow correlation coefficient; median slope; and curve efficiency. The effects of the task and tested arm on the metrics were investigated using a mixed-model analysis. The validity of metrics compared to clinically measured interjoint coordination (FMMA-UE) was done by correlation analysis.

Results: Twenty-six subjects were included in the analysis. The movement task and tested arm showed significant effects (p < 0.05) on all kinematic parameters. Hand dominance resulted in significant effects on shoulder flexion/extension and curve efficiency. The level of upper limb function showed influences on curve efficiency and the factor age on median slope. Relations with the FMMA-UE revealed the strongest and significant correlation for curve efficiency (r = 0.75), followed by shoulder flexion/extension (r = 0.68), elbow flexion/extension (r = 0.53), and shoulder abduction/adduction (r = 0.49). Curve efficiency additionally correlated significantly with the arm subsection, focusing on synergistic control (r = 0.59).

Conclusion: The kinematic parameters of the upper limb after stroke were influenced largely by the task. These results underpin the necessity to assess different relevant functional movements close to real-world conditions rather than relying solely on clinical measures.

Study Registration: clinicaltrials.gov, identifier NCT03135093 and BASEC-ID 2016-02075.

The effect of VNS on the rehabilitation of stroke: A meta-analysis of randomized controlled studies

INTRODUCTION

The efficacy of vagus nerve stimulation (VNS) for the rehabilitation of stroke remains controversial. We conduct a systematic review and meta-analysis to explore the influence of VNS on the rehabilitation of stroke.

METHODS

We search PubMed, EMbase, Web of science, EBSCO, and Cochrane library databases through March 2020 for randomized controlled trials (RCTs) assessing the effect of VNS on the rehabilitation of stroke. This meta-analysis is performed using the random-effect model.

RESULTS

Three RCTs are included in the meta-analysis. Overall, compared with control group in stroke, VNS is associated with significantly improved FMA-UE (SMD = 3.86; 95% CI = 1.19 to 6.52; P = 0.005) and Motor Function Test (SMD = 0.33; 95% CI = 0.04 to 0.62; P = 0.03), but has no obvious impact on Box and Block Test (SMD = -0.31; 95% CI = -3.48 to 2.86; P = 0.85), Nine-Hole Peg Test (SMD = 8.35; 95% CI = -40.59 to 57.28; P = 0.74), atrial fibrillation (RR = 3.46; 95% CI = 0.39 to 30.57; P = 0.26) or adverse events (RR = 0.59; 95% CI = 0.21 to 1.61; P = 0.30).

CONCLUSIONS

VNS may be beneficial to the rehabilitation of stroke.

A novel mechatronic system for evaluating elbow muscular spasticity relying on Tonic Stretch Reflex Threshold estimation

Muscular spasticity represents one of the most common motor disorder associated to lesions of the Central Nervous System, such as Stroke, and affects joint mobility up to the complete prevention of skeletal muscle voluntary control. Its clinical evaluation is hence of fundamental relevance for an effective rehabilitation of the affected subjects. Standard assessment protocols are usually manually performed by humans, and hence their reliability strongly depends on the capabilities of the clinical operator performing the procedures. To overcome this limitation, one solution is the usage of mechatronic devices based on the estimation of the Tonic Stretch Reflex Threshold, which allows for a quite reliable and operator-independent evaluation. In this work, we present the design and characterization of a novel mechatronic device that targets the estimation of the Tonic Stretch Reflex Threshold at the elbow level, and, at the same time, it can potentially act as a rehabilitative system. Our device can deliver controllable torque/velocity stimulation and record functional parameters of the musculo-skeletal system (joint position, torque, and multi-channel ElectroMyoGraphyc patterns), with the ultimate goals of: i) providing significant information for the diagnosis and the classification of muscular spasticity, ii) enhancing the recovery evaluation of patients undergoing through therapeutic rehabilitation procedures and iii) enabling a future active usage of this device also as therapeutic tool.Clinical relevance- The contribution presented in this work proposes a technological advancement for a device-based evaluation of motion impairment related to spasticity, with a major potential impact on both the clinical appraisal and the rehabilitation procedures.