Somehow you think chronic research will do any good? Long ago you will have plateaued and insurance will have quit paying. Chronic research needs to be done with the survivor in mind. Robotics will never fit that bill.
A randomized clinical control study on the efficacy of three-dimensional upper limb robotic exoskeleton training in chronic stroke
Journal of NeuroEngineering and Rehabilitation volume 19, Article number: 14 (2022)
Abstract
Background
Although robotics assisted rehabilitation has proven to be effective in stroke rehabilitation, a limited functional improvements in Activities of Daily Life has been also observed after the administration of robotic training. To this aim in this study we compare the efficacy in terms of both clinical and functional outcomes of a robotic training performed with a multi-joint functional exoskeleton in goal-oriented exercises compared to a conventional physical therapy program, equally matched in terms of intensity and time. As a secondary goal of the study, it was assessed the capability of kinesiologic measurements—extracted by the exoskeleton robotic system—of predicting the rehabilitation outcomes using a set of robotic biomarkers collected at the baseline.
Methods
A parallel-group randomized clinical trial was conducted within a group of 26 chronic post-stroke patients. Patients were randomly assigned to two groups receiving robotic or manual therapy. The primary outcome was the change in score on the upper extremity section of the Fugl-Meyer Assessment (FMA) scale. As secondary outcome a specifically designed bimanual functional scale, Bimanual Activity Test (BAT), was used for upper limb functional evaluation. Two robotic performance indices were extracted with the purpose of monitoring the recovery process and investigating the interrelationship between pre-treatment robotic biomarkers and post-treatment clinical improvement in the robotic group.
Results
A significant clinical and functional improvements in both groups (p < 0.01) was reported. More in detail a significantly higher improvement of the robotic group was observed in the proximal portion of the FMA (p < 0.05) and in the reduction of time needed for accomplishing the tasks of the BAT (p < 0.01). The multilinear-regression analysis pointed out a significant correlation between robotic biomarkers at the baseline and change in FMA score (R2 = 0.91, p < 0.05), suggesting their potential ability of predicting clinical outcomes.
Conclusion
Exoskeleton-based robotic upper limb treatment might lead to better functional outcomes, if compared to manual physical therapy. The extracted robotic performance could represent predictive indices of the recovery of the upper limb. These results are promising for their potential exploitation in implementing personalized robotic therapy.
Clinical Trial Registration clinicaltrials.gov, NCT03319992 Unique Protocol ID: RH-UL-LEXOS-10. Registered 20.10.2017, https://clinicaltrials.gov/ct2/show/NCT03319992
Background
Upper limb motor impairment is one of the most frequent causes of long term disability following stroke and it is particularly problematic given its negative impact on Activities of Daily Living (ADL) [1]. Physical therapy and exercise promote the motor recovery after stroke with consequent regain of function and changes in cortical reorganization according to residual neuroplasticity [2]. It has been demonstrated that the amount and intensity of practice and the degree of participation, as well as the task-oriented training, play a crucial role in positively affecting the neuroplastic changes [3]. Apart the intrinsic ability of providing a high number of specific practice movements, robot-mediated therapy can be successfully coupled with virtual reality (VR) technology allowing patients to train in a more ecological and enriched environment which could give an opportunity to practice functional movements and everyday activities that are not or cannot be practiced within the hospital environment [4].
However, although scientific literature provides supporting evidence of the efficacy of upper limb robotic treatments after stroke compared to manual therapy [5, 6], it is still arguable the achievement of an effective improvement in terms of regained upper limb function and consequent transfer of abilities to ADL. One recent, large pragmatic randomized controlled trial performed with the MIT-Manus robotic gym system [7] concluded that robot-assisted training did not lead to improvement in upper limb function in ADLs compared with usual care, measured by ARAT test. To overcome this potential limit of some robotic rehabilitation programs, it has been so far hypothesized in literature that robotic training with exoskeletons, based on three-dimensional spatial, task-oriented and more naturalistic movements [8], is likely to provide higher benefits in terms of recovery in ADLs and improvement of upper limb function.
In the scientific literature there are still however not only a limited number of randomized controlled trials (RCT) concerning robotic therapy with three-dimensional spatial robotic exoskeletons to support this hypothesis, but also contrasting evidences. The asymmetry of studies conducted with End Effector (EE) devices vs Exoskeletons (Exo) is for example evident from data published in one recent meta-review [5], where only 3 exoskeletons RCT are reported, of which one based on passive exoskeleton device only,vs. 11 trials employing EE devices.
One of the first clinical studies addressing this issue was the randomized trial conducted with Pneu-WREX in a group 26 patients [9], wherein three dimensional movement against gravity in the context of simulated functional tasks that required use of the hand conducted with assist-as-needed controller robotic training was found to be more effective than conventional table-top training. According to authors’ the observed results benefits may also have arisen in part due to the fact that the robot allowed 3D movements that incorporate hand grip and release, rather than just planar or single-joint movements.
In a large controlled study (77 patients) [10], the robotic treatment conducted with the ARMin exoskeleton was compared with the manual physical and occupational therapy, showing that robotic training enhanced arm motor function more effectively than manual therapy, as measured by the upper extremity portion of the Fugl-Meyer scale (FMA-UE).
Also we observed in our previous study [11] in chronic stroke through instrumental study of the reaching performance that exoskeleton training produced positive effects in movement execution, in terms of decreased execution time, improved movement smoothness and increased active joint ranges of motion.
On the other side, another recent randomized controlled trial compared End Effector (EE) and Exoskeleton (Exo) robot therapy in patients with stroke [12] after 4 weeks of intervention, suggesting that the EE robot intervention is better than the Exo robot intervention among chronic stroke patients with moderate-to-severe impairment of upper extremity function.
Also within the cross-over study conducted with BONES exoskeleton [13], patients were assigned with different random order to both single joint and multiple joint robotic training. The results of the study showed how multi-joint functional robotic training was not superior to single joint robotic training for Box and Block Test score (primary outcome) and for other secondary outcome measurements (FMA, Wolf Motor Function Test WMFT, Motor Activity Log MAL scales).
So to what extent the 3D nature of therapy robotic assistance provided with exoskeletons can be a determinant factor for motor recovery?
To provide further clinical and experimental evidences to answer this question, we have compared within a randomized controlled clinical trial the effects of a robotic exoskeleton training in three-dimensional task-oriented exercises versus an equally intensive program of manual therapy intervention (1) to assess if the observed motor improvements are reflected into higher functional outcomes—and so improved transfer of abilities into ADL—than conventional manual therapy and (2) to understand how the eventual observed changes can be interpreted in terms of kinematic measurements automatically extracted by the exoskeleton.
As a second aspect, several clinical studies, including animal ones [14], support with growing consensus that individualized approach to stroke rehabilitation, for instance based on stratification of patients into groups with different probabilities of upper limb recovery, could enhance the recovery of lost motor function. In this context, the use of biomarkers plays an important role [15, 16]. Beside neurophysiological and neuroimaging biomarkers, robotic biomarkers may be a valuable clinical instrument for determining the effect of a rehabilitation therapy [17]. These robotic biomarkers have the great advantage to be entirely objective in capturing the quality of movement which can be immediately provided as an index of the recovery progress [18]. The extraction and the analysis of robotic biomarkers can be used for both monitoring the ongoing recovery process during treatment and for investigating the relationship with primary clinical outcome. It is reasonable to think that as next step robotic biomarkers can be used to optimize the design of rehabilitation therapies tailored to the need of individual patients.
In [19] first, it was demonstrated the high potential of prediction of the outcome of a therapeutic treatment in stroke, performing an objective and analytical assessment of motor recovery through the acquisition of kinesiological and kinetic parameters and finding a prediction, supported by a statistically significant correlation with clinical scales, while in [20] it was confirmed the capability of predicting Fugl-Meyer assessment scale through robotic and clinical biomarkers.
Predictive clinical models of post-stroke motor recovery allow specific early interventions which is the phase in which the largest treatment effect can be obtained. Patient-specific prognostic models for monitoring post-stroke recovery have been developed and validated to assess their clinical effectiveness [21]. The most reliable predictors of the functional outcome are age and motor function assessed on clinical scales immediately after the acute event [22].
The use of metrics based on biomechanical parameters to estimate movement capabilities can raise the knowledge about motor recovery mechanisms. However, because of insufficient validation, the clinical integration of those methods is still limited.
So based on the characteristics of spatial movement involved in exoskeleton rehabilitation, a secondary goal of the study is to investigate whether in the robotic group the measured robotic performance biomarkers, based on patient’s performance automatically extracted at the enrollment of treatment, could predict the clinical and functional outcome of the robotic rehabilitation treatment.
More at link.
No comments:
Post a Comment