Something happened but I have no clue on how this will help survivors recover.
Can kinematic parameters of 3D reach-to-target movements be used as a proxy for clinical outcome measures in chronic stroke rehabilitation? An exploratory study
Journal of NeuroEngineering and Rehabilitation volume 17, Article number: 106 (2020)
Abstract
Background
Despite numerous trials investigating robot-assisted therapy (RT) effects on upper-extremity (UE) function after stroke, few have explored the relationship between three-dimensional (3D) reach-to-target kinematics and clinical outcomes. The objectives of this study were to 1) investigate the correlation between kinematic parameters of 3D reach-to-target movements and UE clinical outcome measures, and 2) examine the degree to which differences in kinematic parameters across individuals can account for differences in clinical outcomes in response to RT.
Methods
Ten chronic stroke survivors participated in a pilot RT intervention (eighteen 1-h sessions) integrating cognitive skills training and a home-action program. Clinical outcome measures and kinematic parameters of 3D reach-to-target movements were collected pre- and post-intervention. The correlation between clinical outcomes and kinematic parameters was investigated both cross-sectionally and longitudinally (i.e., changes in response to the intervention). Changes in clinical outcomes and kinematic parameters were tested for significance in both group and subject-by-subject analyses. Potential associations between individual differences in kinematic parameters and differences in clinical outcomes were examined.
Results
Moderate-to-strong correlation was found between clinical measures and specific kinematic parameters when examined cross-sectionally. Weaker correlation coefficients were found longitudinally. Group analyses revealed significant changes in clinical outcome measures in response to the intervention; no significant group changes were observed in kinematic parameters. Subject-by-subject analyses revealed changes with moderate-to-large effect size in the kinematics of 3D reach-to-target movements pre- vs. post-intervention. Changes in clinical outcomes and kinematic parameters varied widely across participants.
Conclusions
Large variability was observed across subjects in response to the intervention. The correlation between changes in kinematic parameters and clinical outcomes in response to the intervention was variable and not strong across parameters, suggesting no consistent change in UE motor strategies across participants. These results highlight the need to investigate the response to interventions at the individual level. This would enable the identification of clusters of individuals with common patterns of change in response to an intervention, providing an opportunity to use cluster-specific kinematic parameters as a proxy of clinical outcomes.
Trial registration
ClinicalTrials.gov, NCT02747433. Registered on April 21st, 2016
Introduction
Every year, about 795,000 people suffer a new or recurrent stroke in the United States [1] leading to hemiparesis and significant effects on the functional use of the paretic arm and hand [2]. Despite treatment, upper-extremity (UE) motor impairments and limited abilities to reach for and manipulate objects persist [3]. Less than half of the individuals who experience a stroke and severe UE hemiparesis in the acute phase regain purposeful UE function after 6 months [4, 5].
A large body of literature based on motor learning theories has shown that high-intensity, high-dosage rehabilitation interventions can facilitate sensorimotor recovery in stroke survivors [6,7,8,9]. Guidelines [10] recommend that the response to rehabilitation interventions be assessed across domains of the International Classification of Functioning, Disability and Health (ICF) [11]. Accordingly, clinical research studies report the results of rehabilitation interventions via a collection of standardized clinical outcome measures of UE function (e.g., Fugl-Meyer Assessment Upper Extremity subscale [FMA-UE] [12], Wolf Motor Function Test [WMFT] and Functional Ability Scale [WMFT-FAS] [13, 14]), and measures of UE activity performance in the home (e.g., Motor Activity Log [MAL] [15]).
Researchers and clinicians have investigated the use of kinematic parameters of UE movements as a proxy for clinical outcome measures after stroke [16,17,18]. This interest has been motivated by the development of rehabilitation technologies (e.g., robotic training devices and wearable sensing technologies) to collect data during the performance of UE movements and the need for precise and valid measures of UE motor function. While many researchers have used kinematic parameters to study two-dimensional (2D) UE reaching movements, few have studied the kinematics of three-dimensional (3D) movements [19,20,21].
Kinematic parameters derived via tracking of 2D arm reaching movements moderately correlated with FMA-UE scores, WMFT and WMFT-FAS scores, and self-reports of the amount of use (MAL-AOU) and quality of movement (MAL-QOM) of the hemiparetic limb [19,20,21]. Moderate correlation was also shown between clinical scores and kinematic parameters of UE movements performed using a rehabilitation robot. Seminal work by Rohrer et al. [22] showed that improvements in robot-based kinematic parameters aimed to capture the smoothness of arm reaching movements moderately correlated with changes in FMA-UE scores in response to robot-assisted intervention. Colombo et al. [23,24,25] further demonstrated a moderate correlation between robot-based kinematic parameters and FMA-UE scores; work by Zollo et al. [26], Otaka et al. [27], Duret et al. [28, 29], and Pila et al. [30] made comparable observations. Other authors achieved similar results by collecting kinematic data during the performance of tasks consisting of drawing geometric figures of different shapes [31, 32], tracing large semicircular arcs to measure UE active range of motion [33], or deriving kinematic parameters from distal movements (e.g., wrist and finger movements) [34]. Larger correlations were shown by Krebs et al. [35] when implementing more complex analytical models than those utilized in previous work. Interestingly, despite the moderate correlation coefficients between clinical scores and kinematic parameters at the group level, studies reporting data on a subject-by-subject basis showed a significant variability across individuals [22, 23, 28].
Because they are more relevant from a functional point of view than 2D movements, several authors have focused their efforts on the analysis of 3D movements and the associations between their kinematic parameters and clinical outcome measures. Seminal work by Cirstea [36] showed a strong correlation between joint kinematics of 3D arm-reaching movements and FMA-UE scores. However, these results are in conflict with later studies showing moderate-to-poor associations between 3D arm-reaching kinematics and FMA-UE scores [37,38,39]. Other research of UE kinematics during the performance of simulated drinking from a glass [40,41,42,43,44] also reported moderate-to-poor correlations with clinical outcome measures of motor impairment and activity performance. Subject-by-subject kinematic analyses are not typically reported for 3D arm-reaching movements and are needed to examine individual differences that contribute to these low associations. Specifically, individual analyses may reveal the degree to which changes in UE activity performance may be attributed to the restitution of motor function or use of compensatory movement strategies after stroke. Additionally, little is known about the association between changes in the kinematic parameters and changes in the clinical outcome measures observed in response to the intervention.
To that end, we analyzed pilot data collected during 3D reach-to-target movements in chronic stroke survivors who received a novel robot-assisted therapy protocol to 1) investigate the correlation between kinematic parameters of three-dimensional (3D) reach-to-target movements and UE clinical outcome measures, both cross-sectionally and longitudinally, and 2) examine the degree to which differences in kinematic parameters across individuals can account for differences in clinical outcomes in response to RT.
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