Methodological considerations for kinematic analysis of upper limbs in healthy and poststroke adults Part II: a systematic review of motion capture systems and kinematic metrics

Effects of end-effector robotic arm reach training with functional electrical stimulation for chronic stroke survivors

BACKGROUND

Upper-extremity dysfunction significantly affects dependence in the daily lives of stroke survivors, limiting their participation in the social environment and reducing their quality of life.

OBJECTIVES

This study aimed to investigate the effect of end-effector robotic arm reach training (RAT) with functional electrical stimulation (FES) on upper-limb motor recovery in chronic stroke survivors.

METHODS

In this single-blinded randomized controlled trial, 28 chronic stroke survivors were randomized to receive RAT-with-FES and RAT-without-FES for 40 min/day, three times per week over a 4-week period, and the data of 26 participants were used in the final analysis. Upper-limb motor recovery was measured using the Fugl-Meyer assessment (FMA), and kinematics (movement time, speed, and distance) during reaching movements toward targets placed in three directions (ipsilateral, median, and contralateral sides) were measured using a robotic arm.

RESULTS

The upper-limb motor recovery (FMA and kinematics) improvement for the within-group comparisons tended to be greater in the RAT-with-FES group than in the RAT-without-FES group. However, in the between-group comparison, no significant differences were found in FMA, and significant differences were observed only for 2 distance parameters of kinematic factors: total (23.0% vs. 1.7%) and straight total (25.5% vs. 2.6%) distance on the ipsilateral side (p < 0.05).

CONCLUSIONS

This study was unable to clearly reveal the positive effects of electrical stimulation combined with robotic arm training. However, we believe that it provides basic data that furthers our understanding of the role of hybrid neuroprostheses in stroke rehabilitation and the factors determining successful treatment.

Remotely Assessing Motor Function and Activity of the Upper Extremity After Stroke: A Systematic Review of Validity and Clinical Utility of Tele-Assessments

OBJECTIVE

The aim of this systematic review is to identify currently available tele-assessments for motor impairments of the upper extremity in adults after a stroke and to assess their psychometric properties and clinical utility.

DATA SOURCES

We searched for studies describing the psychometric properties of tele-assessments for the motor function of the upper extremity. A systematic search was conducted in the Cumulative Index to Nursing and Allied Health Literature, Medline via OVID, Embase, The Cochrane Library, Scopus, Web of Science and Institute of Electrical and Electronics Engineers Xplore from inception until 30 April 2024.

REVIEW METHODS

The quality assessment for the included studies and the rating of the psychometric properties were performed using the COSMIN Risk of Bias Checklist for systematic reviews of patient-reported outcome measures.

RESULTS

A total of 12 studies (N = 3912) describing 11 tele-assessments met the predefined inclusion criteria. The included assessments were heterogeneous in terms of quality and psychometric properties and risk of bias. None of the tele-assessments currently meets the criteria of clinical utility to be recommended for clinical practice without restriction.

CONCLUSION

The quality and clinical utility of tele-assessments varied widely, suggesting a cautious consideration for immediate clinical practice application. There is potential for tele-assessments in clinical practice, but the clinical benefits need to be improved by simplifying the complexity of tele-assessments.

REGISTRATION NUMBER

CRD42022335035.

The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions

In recent years, there has been a notable increase in the clinical adoption of instrumental upper limb kinematic assessment. This trend aligns with the rising prevalence of cerebrovascular impairments, one of the most prevalent neurological disorders. Indeed, there is a growing need for more objective outcomes to facilitate tailored rehabilitation interventions following stroke. Emerging technologies, like head-mounted virtual reality (HMD-VR) platforms, have responded to this demand by integrating diverse tracking methodologies. Specifically, HMD-VR technology enables the comprehensive tracking of body posture, encompassing hand position and gesture, facilitated either through specific tracker placements or via integrated cameras coupled with sophisticated computer graphics algorithms embedded within the helmet. This review aims to present the state-of-the-art applications of HMD-VR platforms for kinematic analysis of the upper limb in post-stroke patients, comparing them with conventional tracking systems. Additionally, we address the potential benefits and challenges associated with these platforms. These systems might represent a promising avenue for safe, cost-effective, and portable objective motor assessment within the field of neurorehabilitation, although other systems, including robots, should be taken into consideration.

Deep learning approaches for seizure video analysis: A review

Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable features such as altered facial expressions. The analysis of these clinical signs, referred to as semiology, is subject to observer variations when specialists evaluate video-recorded events in the clinical setting. To enhance the accuracy and consistency of evaluations, computer-aided video analysis of seizures has emerged as a natural avenue. In the field of medical applications, deep learning and computer vision approaches have driven substantial advancements. Historically, these approaches have been used for disease detection, classification, and prediction using diagnostic data; however, there has been limited exploration of their application in evaluating video-based motion detection in the clinical epileptology setting. While vision-based technologies do not aim to replace clinical expertise, they can significantly contribute to medical decision-making and patient care by providing quantitative evidence and decision support. Behavior monitoring tools offer several advantages such as providing objective information, detecting challenging-to-observe events, reducing documentation efforts, and extending assessment capabilities to areas with limited expertise. The main applications of these could be (1) improved seizure detection methods; (2) refined semiology analysis for predicting seizure type and cerebral localization. In this paper, we detail the foundation technologies used in vision-based systems in the analysis of seizure videos, highlighting their success in semiology detection and analysis, focusing on work published in the last 7 years. We systematically present these methods and indicate how the adoption of deep learning for the analysis of video recordings of seizures could be approached. Additionally, we illustrate how existing technologies can be interconnected through an integrated system for video-based semiology analysis. Each module can be customized and improved by adapting more accurate and robust deep learning approaches as these evolve. Finally, we discuss challenges and research directions for future studies.

Age- and sex-related differences in upper-body joint and endpoint kinematics during a drinking task in healthy adults

Background

The objective kinematic assessments of activities of daily living are desired. However, the limited knowledge regarding age- and sex-related differences prevents the adaptation of these measurements to clinical settings and in-home exercises. Therefore, this study aimed to determine the effects of age and sex on joint and endpoint kinematics during a common activity of daily living, specifically, drinking from a glass.

Methods

In total, 32 healthy adults (18 males and 14 females) aged 22-77 years performed a drinking task comprising reaching for a glass, bringing it forward and sipping, returning it, and placing the hand back to the starting position, which was recorded using a three-dimensional motion-capturing system. A two-way analysis of variance was used to statistically compare joint angles at five different time points and endpoint kinematic variables in the four drinking phases between older and younger age groups and sexes.

Results

Wrist radial deviation was greater in older adults than in younger participants at all five different time points (F = 5.16-7.34, p ≤ 0.03, η2 = 0.14-0.21). Moreover, lesser shoulder abduction and greater shoulder internal rotation and forearm pronation when moving and returning the hand to the starting position were observed in the female group than in the male group (F = 4.21-20.03, p ≤ 0.0497, η2 = 0.13-0.41). Trunk flexion was lower in the female group than in the male group at all time points (F = 4.25-7.13, p ≤ 0.0485, η2 = 0.12-0.19). Regarding endpoint kinematics, the performance time in the reaching phase was longer in older adults than in younger individuals (F = 4.96, p = 0.03, η2 = 0.14). Furthermore, a shorter time while returning the hand to the starting position was observed in the female group than in the male group (F = 9.55, p < 0.01, η2 = 0.22).

Conclusions

The joint kinematics of drinking were partially characterized by an age effect, whereas endpoint kinematics were scattered in all drinking phases. Sex-related effects in most upper-body motions and postures may cause rapid motions in females. Therefore, clinicians could use this knowledge for precise assessments and to suggest feasible in-home exercises.

Upper extremity kinematics: development of a quantitative measure of impairment severity and dissimilarity after stroke

Background

Strokes are a leading cause of disability worldwide, with many survivors experiencing difficulty in recovering upper extremity movement, particularly hand function and grasping ability. There is currently no objective measure of movement quality, and without it, rehabilitative interventions remain at best informed estimations of the underlying neural structures' response to produce movement. In this article, we utilize a novel modification to Procrustean distance to quantify curve dissimilarity and propose the Reach Severity and Dissimilarity Index (RSDI) as an objective measure of motor deficits.

Methods

All experiments took place at the Medstar National Rehabilitation Hospital; persons with stroke were recruited from the hospital patient population. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individuals completed sets of reach-to-target tasks to extrapolate kinematic metrics describing motor performance. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were congruous to able-bodied sub-movements.

Findings

Movement initiation proceeds comparably to the reference curve in both two- and three-dimensional representations of mild impairment movement. There were significant effects of the location of congruent segments between subject and reference curves, mean velocities, peak roll angle, and target error. These metrics were used to calculate a preliminary RSDI score with severity and dissimilarity sub-scores, and subjects were reclassified in terms of rehabilitation goals as Speed Emphasis, Strength Emphasis, and Combined Emphasis.

Interpretation

The modified Procrustes method shows promise in identifying disruptions in movement and monitoring recovery without adding to patient or clinician burden. The proposed RSDI score can be adapted and expanded to other functional movements and used as an objective clinical tool. By reducing the impact of stroke on disability, there is a significant potential to improve quality of life through individualized rehabilitation.

Quantitative Comparison of Hand Kinematics Measured with a Markerless Commercial Head-Mounted Display and a Marker-Based Motion Capture System in Stroke Survivors

Upper-limb paresis is common after stroke. An important tool to assess motor recovery is to use marker-based motion capture systems to measure the kinematic characteristics of patients' movements in ecological scenarios. These systems are, however, very expensive and not readily available for many rehabilitation units. Here, we explored whether the markerless hand motion capabilities of the cost-effective Oculus Quest head-mounted display could be used to provide clinically meaningful measures. A total of 14 stroke patients executed ecologically relevant upper-limb tasks in an immersive virtual environment. During task execution, we recorded their hand movements simultaneously by means of the Oculus Quest's and a marker-based motion capture system. Our results showed that the markerless estimates of the hand position and peak velocity provided by the Oculus Quest were in very close agreement with those provided by a marker-based commercial system with their regression line having a slope close to 1 (maximum distance: mean slope = 0.94 ± 0.1; peak velocity: mean slope = 1.06 ± 0.12). Furthermore, the Oculus Quest had virtually the same sensitivity as that of a commercial system in distinguishing healthy from pathological kinematic measures. The Oculus Quest was as accurate as a commercial marker-based system in measuring clinically meaningful upper-limb kinematic parameters in stroke patients.

Quantitative Assessment of Upper Limb Movement in Post-Stroke Adults for Identification of Sensitive Measures in Reaching and Lifting Activities

BACKGROUND

The assumption of this work is the achievement of objective results of the movement structure, which forms the basis for in-depth analysis and, consequently, for determining the upper limb movements that are most affected by stroke compared to healthy people.

METHODS

An analysis of relevant and systematically identified features of upper limb movement in post-stroke adults is presented based on scalable hypothesis tests. The basic features were calculated using movements defined by the x, y, and z coordinates (i.e., 3D trajectory time series) and compared to the results of post-stroke patients with healthy controls of similar age.

RESULTS

After automatic feature selection, out of the 1004 common features of upper limb movement, the most differentiated were the upper arm movements in reaching kinematics. In terms of movement type, movements in the frontal plane (shoulder abduction and adduction) were the most sensitive to changes. The largest number of discriminating features was determined on the basis of acceleration time series.

CONCLUSIONS

In the 3D assessment of functional activities of the upper limb, the upper arm turned out to be the most differentiated body segment, especially during abduction and adduction movements. The results indicate a special need to pay attention to abduction and adduction movements to improve the activities of daily living of the upper limbs after a stroke.

Usability of Functional Electrical Stimulation in Upper Limb Rehabilitation in Post-Stroke Patients: A Narrative Review

Stroke leads to significant impairment in upper limb (UL) function. The goal of rehabilitation is the reestablishment of pre-stroke motor stroke skills by stimulating neuroplasticity. Among several rehabilitation approaches, functional electrical stimulation (FES) is highlighted in stroke rehabilitation guidelines as a supplementary therapy alongside the standard care modalities. The aim of this study is to present a comprehensive review regarding the usability of FES in post-stroke UL rehabilitation. Specifically, the factors related to UL rehabilitation that should be considered in FES usability, as well a critical review of the outcomes used to assess FES usability, are presented. This review reinforces the FES as a promising tool to induce neuroplastic modifications in post-stroke rehabilitation by enabling the possibility of delivering intensive periods of treatment with comparatively less demand on human resources. However, the lack of studies evaluating FES usability through motor control outcomes, specifically movement quality indicators, combined with user satisfaction limits the definition of FES optimal therapeutical window for different UL functional tasks. FES systems capable of integrating postural control muscles involving other anatomic regions, such as the trunk, during reaching tasks are required to improve UL function in post-stroke patients.

Quantifying Quality of Reaching Movements Longitudinally Post-Stroke: A Systematic Review

Background

Disambiguation of behavioral restitution from compensation is important to better understand recovery of upper limb motor control post-stroke and subsequently design better interventions. Measuring quality of movement (QoM) during standardized performance assays and functional tasks using kinematic and kinetic metrics potentially allows for this disambiguation.

Objectives

To identify longitudinal studies that used kinematic and/or kinetic metrics to investigate post-stroke recovery of reaching and assess whether these studies distinguish behavioral restitution from compensation.

Methods

A systematic literature search was conducted using the databases PubMed, Embase, Scopus, and Wiley/Cochrane Library up to July 1st, 2020. Studies were identified if they performed longitudinal kinematic and/or kinetic measurements during reaching, starting within the first 6 months post-stroke.

Results

Thirty-two longitudinal studies were identified, which reported a total of forty-six different kinematic metrics. Although the majority investigated improvements in kinetics or kinematics to quantify recovery of QoM, none of these studies explicitly addressed the distinction between behavioral restitution and compensation. One study obtained kinematic metrics for both performance assays and a functional task.

Conclusions

Despite the growing number of kinematic and kinetic studies on post-stroke recovery, longitudinal studies that explicitly seek to delineate between behavioral restitution and compensation are still lacking in the literature. To rectify this situation, future studies should measure kinematics and/or kinetics during performance assays to isolate restitution and during a standardized functional task to determine the contributions of restitution and compensation.

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.

Development of a revolute-type kinematic model for human upper limb using a matrix approach

A mathematical model is proposed for a revolute joint mechanism with an n-degree of freedom (DOF). The matrix approach is used for finding the relation between two consecutive links to determine desired link parameters such as position, velocity and acceleration using the forward kinematic approach. The matrix approach was confirmed for a proposed 10 DOF revolute type (R-type) human upper limb model with servo motors at each joint. Two DOFs are considered each at shoulder, elbow and wrist joint, followed by four DOF for the fingers. Two DOFs were considered for metacarpophalangeal (mcp) and one DOF each for proximal interphalangeal (pip) and distal interphalangeal (dip) joints. MATLAB script function was used to evaluate the mathematical model for determining kinematic parameters for all the proposed human upper limb model joints. The simplified method for kinematic analysis proposed in this paper will further simplify the dynamic modeling of any mechanism for determining joint torques and hence, easy to design control system for joint movements.

A New Software for Quantifying Motor Deficit After Stroke: A Case-Control Feasibility Pilot Study

Introduction: The degree of disability after stroke needs to be objectively measured to implement adequate rehabilitation programs. Here, we evaluate the feasibility of a custom-built software to assess motor status after stroke.

Methods: This is a prospective, case–control pilot study comparing stroke patients with healthy volunteers. A workout evaluation that included trunk and upper limb movement was captured with Kinect® and kinematic metrics were extracted with Akira®. Trunk and joint angles were analyzed and compared between cases and controls. Patients were evaluated within the first week from stroke onset using the National Institutes of Health Stroke Scale (NIHSS), Fulg-Meyer Assessment (FMA), and modified Rankin Scale (mRS) scales; the relationship with kinematic measurements was explored.

Results: Thirty-seven patients and 33 controls were evaluated. Median (IQR) NIHSS of cases was 2 (0–4). The kinematic metrics that showed better discriminatory capacity were body sway during walking (less in cases than in controls, p = 0.01) and the drift in the forearm–trunk angle during shoulder abduction in supination (greater in cases than in controls, p = 0.01). The body sway during walking was moderately correlated with NIHSS score (Rho = −0.39; p = 0.01) but better correlated with mRS score (Rho = −0.52; p < 0.001) and was associated with the absence of disability (mRS 0–1) (OR = 0.64; p = 0.02). The drift in the forearm–trunk angle in supination was associated with the presence of disability (mRS >1) (OR = 1.27; p = 0.04).

Conclusion: We present a new software that detects even mild motor impairment in stroke patients underestimated by clinical scales but with an impact on patient functionality.