Does kinematics add meaningful information to clinical assessment in post-stroke upper limb rehabilitation? A case report

Real-time, accurate, and open source upper-limb musculoskeletal analysis using a single RGBD camera - An exploratory hand-cycling study

Biomechanical biofeedback may enhance rehabilitation and provide clinicians with more objective task evaluation. These feedbacks often rely on expensive motion capture systems (∼$100000), which restricts their widespread use, leading to the development of computer vision-based methods. These methods are subject to large joint angle errors, considering the upper limb, and exclude the scapula and clavicle motion in the analysis. Our open-source approach offers a user-friendly solution for high-fidelity upper-limb kinematics using a single consumer-grade depth-sensing camera (∼$500) and includes semi-automatic skin marker labeling. Real-time biomechanical analysis, ranging from kinematics to muscle force estimation, was conducted on eight participants performing a hand-cycling motion to demonstrate the applicability of our approach on the upper limb. Markers were recorded by the depth-sensing camera and an optoelectronic camera system, considered as a reference. Muscle activity and external load were recorded using eight electromyography sensors and instrumented hand pedals, respectively. Bland-Altman analysis revealed significant agreements in the 3D markers' positions between the two motion capture methods, with errors averaging 3.3 ± 3.9 mm. The error propagation was low for the biomechanical analysis, with joint angle differences, for example, below 5° when comparing both systems. Biofeedback from the depth-sensing camera was provided at 68 Hz. Our study introduces a novel method for using a depth-sensing camera as a low-cost motion capture solution. Results from healthy participants suggest its potential for accurate kinematic reconstruction and comprehensive upper-limb biomechanical studies. Further investigation is needed to explore its clinical applications in pathological populations.

Using a tablet to understand the spatial and temporal characteristics of complex upper limb movements in chronic stroke

Robotic devices are commonly used to quantify sensorimotor function of the upper limb after stroke; however, the availability and cost of such devices make it difficult to facilitate implementation in clinical environments. Tablets (e.g. iPad) can be used as devices to facilitate rehabilitation but are rarely used as assessment tools for the upper limb. The current study aimed to implement a tablet-based Maze Navigation Task to examine complex upper-limb movement in individuals with chronic stroke. We define complex upper-limb movement as reaching movements that require multi-joint coordination in a dynamic environment. We predicted that individuals with stroke would have more significant spatial errors, longer movement times, and slower speeds compared to controls with increasing task complexity. Twenty individuals with chronic stroke who had a variety of arm and hand function (Upper extremity Fugl-Myer 52.8 ± 18.3) and twenty controls navigated eight pseudorandomized mazes on an iPad using a digitizing stylus. The task was designed to elicit reaching movements engaging both the shoulder and elbow joints. Each maze became increasingly complex by increasing the number of 90° turns. We instructed participants to navigate each maze as quickly and accurately as possible while avoiding the maze's boundaries. Sensorimotor behavior was quantified using the following metrics: Error Time (time spent hitting or outside boundaries), Peak Speed, Average Speed, and Movement Time, Number of Speed Peaks. We found that individuals with stroke had significantly greater Error Time for all maze levels (all, p < 0.01), while both speed metrics, Movement Time and Number of Speed Peaks were significantly lower for several levels (all, p < 0.05). As maze complexity increased, the performance of individuals with stroke worsened only for Error Time while control performance remained consistent (p < 0.001). Our results indicate that a complex movement task on a tablet can capture temporal and spatial impairments in individuals with stroke, as well as how task complexity impacts movement quality. This work demonstrates that a tablet is a suitable tool for the assessment of complex movement after stroke and can serve to inform rehabilitation after stroke.

Review on Patient-Cooperative Control Strategies for Upper-Limb Rehabilitation Exoskeletons

Technology-supported rehabilitation therapy for neurological patients has gained increasing interest since the last decades. The literature agrees that the goal of robots should be to induce motor plasticity in subjects undergoing rehabilitation treatment by providing the patients with repetitive, intensive, and task-oriented treatment. As a key element, robot controllers should adapt to patients’ status and recovery stage. Thus, the design of effective training modalities and their hardware implementation play a crucial role in robot-assisted rehabilitation and strongly influence the treatment outcome. The objective of this paper is to provide a multi-disciplinary vision of patient-cooperative control strategies for upper-limb rehabilitation exoskeletons to help researchers bridge the gap between human motor control aspects, desired rehabilitation training modalities, and their hardware implementations. To this aim, we propose a three-level classification based on 1) “high-level” training modalities, 2) “low-level” control strategies, and 3) “hardware-level” implementation. Then, we provide examples of literature upper-limb exoskeletons to show how the three levels of implementation have been combined to obtain a given high-level behavior, which is specifically designed to promote motor relearning during the rehabilitation treatment. Finally, we emphasize the need for the development of compliant control strategies, based on the collaboration between the exoskeleton and the wearer, we report the key findings to promote the desired physical human-robot interaction for neurorehabilitation, and we provide insights and suggestions for future works.

Smoothness metrics for reaching performance after stroke. Part 1: which one to choose?

Background

Smoothness is commonly used for measuring movement quality of the upper paretic limb during reaching tasks after stroke. Many different smoothness metrics have been used in stroke research, but a ‘valid’ metric has not been identified. A systematic review and subsequent rigorous analysis of smoothness metrics used in stroke research, in terms of their mathematical definitions and response to simulated perturbations, is needed to conclude whether they are valid for measuring smoothness. Our objective was to provide a recommendation for metrics that reflect smoothness after stroke based on: (1) a systematic review of smoothness metrics for reaching used in stroke research, (2) the mathematical description of the metrics, and (3) the response of metrics to simulated changes associated with smoothness deficits in the reaching profile.

Methods

The systematic review was performed by screening electronic databases using combined keyword groups Stroke, Reaching and Smoothness. Subsequently, each metric identified was assessed with mathematical criteria regarding smoothness: (a) being dimensionless, (b) being reproducible, (c) being based on rate of change of position, and (d) not being a linear transform of other smoothness metrics. The resulting metrics were tested for their response to simulated changes in reaching using models of velocity profiles with varying reaching distances and durations, harmonic disturbances, noise, and sub-movements. Two reaching tasks were simulated; reach-to-point and reach-to-grasp. The metrics that responded as expected in all simulation analyses were considered to be valid.

Results

The systematic review identified 32 different smoothness metrics, 17 of which were excluded based on mathematical criteria, and 13 more as they did not respond as expected in all simulation analyses. Eventually, we found that, for reach-to-point and reach-to-grasp movements, only Spectral Arc Length (SPARC) was found to be a valid metric.

Conclusions

Based on this systematic review and simulation analyses, we recommend the use of SPARC as a valid smoothness metric in both reach-to-point and reach-to-grasp tasks of the upper limb after stroke. However, further research is needed to understand the time course of smoothness measured with SPARC for the upper limb early post stroke, preferably in longitudinal studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00949-6.

Evaluation of a multi-sensor Leap Motion setup for biomechanical motion capture of the hand

The Leap Motion controller (LMC) offers a low-cost means of markerless hand tracking, however, its utility is limited by a small field of view and reliance on appropriate sensor positioning. A recent update from Leap Motion has enabled the use of a multiple LMC device on a single computer, allowing the tracking of hands from multiple orientations, potentially overcoming the aforementioned limitations. This study describes a method of implementing a multi-LMC setup and evaluates its effect on the validity and reliability of the derived kinematics. This study implemented a Kabsch algorithm and Kalman filter to re-orientate and fuse the trajectories captured by three LMC at different orientations. Reliability was assessed by comparing between-day differences in maximum joint angles (ΔMJA) and a calculated coefficient of multiple correlations (CMC). Validity was assessed by comparing the LMC to the gold standard, a Vicon markered motion capture (MMC) system, and calculating the ΔMJA and applying the linear fit method. The proposed method was evaluated by comparing the reliability and validity of the single-LMC setups to the multi-LMC setup. A multi-LMC setup proved successful in improving the reliability and validity of kinematic data, most notably where reliability and validity were poor and variation was high between the single-LMC setups. Findings suggest that through implementing the proposed method, limitations associated with single-LMC setups, notably its reliance on optimal sensor positioning, can be overcome.

Constraint-Induced Movement Therapy in multiple sclerosis: Safety and three-dimensional kinematic analysis of upper limb activity. A randomized single-blind pilot study

BACKGROUND

There are few evidences on safety of Constraint-Induced Movement Therapy (CIMT), as well as its effects in neurological conditions, including multiple sclerosis (MS).

OBJECTIVE

To evaluate safety and effectiveness of a 2-week CIMT protocol on upper limb activity of progressive MS patients through a three-dimensional (3D) kinematic analysis.

METHODS

In this randomized single-blind pilot study, we randomly allocated patients affected by progressive MS reporting a reduced use of one upper limb into two different groups: CIMT group (less affected limb blocked by a splint) and control group (undergoing bi-manual treatment). Primary outcome was CIMT safety. Furthermore, we assessed CIMT effects through clinical outcomes (hand grip strength, HGS, and 9 Hole Peg Test, 9HPT) and 3D kinematic analysis (normalized jerk, number of movement units, going phase duration, mean velocity, endpoint error). All evaluations were performed at baseline (T0) and after 2 weeks of treatment (T1) for both arms in both groups.

RESULTS

Ten MS patients, mean aged 51.0±7.7 years, were randomly allocated in the 2 groups. After treatment, no differences were found in the blocked arm. Furthermore, CIMT group showed significant improvements in clinical and kinematic parameters.

CONCLUSIONS

CIMT might be considered a safe and effective technique in MS patients.

Whole Brain White Matter Microstructure and Upper Limb Function: Longitudinal Changes in Fractional Anisotropy and Axial Diffusivity in Post-Stroke Patients

Background

Diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) measuring fractional anisotropy (FA) and axial diffusivity (AD) may be a useful biomarker for monitoring changes in white matter after stroke, but its associations with upper-limb motor recovery have not been well studied. We aim to describe changes in the whole-brain FA and AD in five post-stroke patients in relation to kinematic measures of elbow flexion to better understand the relationship between FA and AD changes and clinico-kinematic measures of upper limb motor recovery.

Methods

We performed DTI MRI at two timepoints during the acute phase of stroke, measuring FA and AD across 48 different white matter tract regions in the brains of five hemiparetic patients with infarcts in the cortex, pons, basal ganglia, thalamus, and corona radiata. We tracked the progress of these patients using clinical Fugl-Meyer Assessments and kinematic measures of elbow flexion at the acute phase within 14 (mean: 9.4 ± 2.49) days of stroke symptom onset and at a follow-up appointment 2 weeks later (mean: 16 ± 1.54) days.

Results

Changes in FA and AD in 48 brain regions occurring during stroke rehabilitation are described in relation to motor recovery. In this case series, one patient with a hemipontine infarct showed an increase in FA of the ipsilateral and contralateral corticospinal tract, whereas other patients with lesions involving the corona radiata and middle cerebral artery showed widespread decreases in perilesional FA. On the whole, FA and AD seemed to behave inversely to each other.

Conclusions

This case series describes longitudinal changes in perilesional and remote FA and AD in relation to kinematic parameters of elbow flexion at the subacute post-stroke period. Although studies with larger sample sizes are needed, our findings indicate that longitudinally measured changes in DTI-based measurements of white matter microstructural integrity may aid in the prognostication of patients affected by motor stroke.