State of the art and challenges for the classification of studies on electromechanical and robotic devices in neurorehabilitation: a scoping review

Gandolfi, Marialuisa; Valè, Nicola; Posteraro, Federico; Morone, Giovanni; Dell’Orco, Antonella; Botticelli, Anita; Dimitrova, Eleonora; Gervasoni, Elisa; Goffredo, Michela; Zenzeri, Jacopo; Antonini, Arianna; Daniele, C.; Benanti, Paolo; Boldrini, Paolo; Bonaiuti, Donatella; Castelli, Enrico; Draicchio, Francesco; Falabella, Vincenzo; Galeri, Silvia; Gimigliano, Francesca; Grigioni, Mauro; Mazzon, Stefano; Molteni, Franco; Petrarca, Maurizio; Picelli, Alessandro; Senatore, Michele; Turchetti, Giuseppe; Giansanti, Daniele; Mazzoleni, Stefano

doi:10.23736/s1973-9087.21.06922-7

Cited by 32 publications

(28 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This outcome has been subsequently confirmed by Mehrholz et al who reviewed the literature on the efficacy of upper limb Robot-assisted Therapy (ulRT) in improving activities of daily living, arm function, and arm muscle strength (6). The efficacy (7)(8)(9)(10)(11), acceptability (12), safety (13), and cost-effectiveness (14) of ulRT in stroke patients are well-established in literature.…”

Section: Introductionmentioning

confidence: 80%

Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

et al. 2021

Self Cite

View full text Add to dashboard Cite

Background: The efficacy of upper-limb Robot-assisted Therapy (ulRT) in stroke subjects is well-established. The robot-measured kinematic data can assess the biomechanical changes induced by ulRT and the progress of patient over time. However, literature on the analysis of pre-treatment kinematic parameters as predictive biomarkers of upper limb recovery is limited.Objective: The aim of this study was to calculate pre-treatment kinematic parameters from point-to-point reaching movements in different directions and to identify biomarkers of upper-limb motor recovery in subacute stroke subjects after ulRT.Methods: An observational retrospective study was conducted on 66 subacute stroke subjects who underwent ulRT with an end-effector robot. Kinematic parameters were calculated from the robot-measured trajectories during movements in different directions. A Generalized Linear Model (GLM) was applied considering the post-treatment Upper Limb Motricity Index and the kinematic parameters (from demanding directions of movement) as dependent variables, and the pre-treatment kinematic parameters as independent variables.Results: A subset of kinematic parameters significantly predicted the motor impairment after ulRT: the accuracy in adduction and internal rotation movements of the shoulder was the major predictor of post-treatment Upper Limb Motricity Index. The post-treatment kinematic parameters of the most demanding directions of movement significantly depended on the ability to execute elbow flexion-extension and abduction and external rotation movements of the shoulder at baseline.Conclusions: The multidirectional analysis of robot-measured kinematic data predicts motor recovery in subacute stroke survivors and paves the way in identifying subjects who may benefit more from ulRT.

show abstract

Section: Introductionmentioning

confidence: 80%

Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…There is a need for stricter collaborations between clinicians, neuropsychologists, and bioengineers to develop transversal know-how about the clinical-biomechanical-neuroscientific interconnection between different robotic parameters and their effects on patients' neuroplasticity. As claimed by the Italian Consensus Conference on Robotics in Neurorehabilitation, there is a limited understanding of the clinical relevance of robots' main features and their rehabilitative contents, and thus, the neurological underpinnings of robot-assisted recovery are not entirely understood [17].…”

Section: Discussionmentioning

confidence: 99%

“…The recent Italian Consensus Conference on Robotics in Neurorehabilitation claimed that in most studies, the information on the technical aspects of the device was not exhaustive for explaining the complexity of the performed movements and poor attention was deserved to the level of robotic assistance, types of the movements performed, and in general to the training modalities [17]. This consensus conference also reported that a lot of studies were focused on chronic stages of stroke, implicitly suggesting that neuroplasticity induced by robotic interventions may occur also in this phase [17]. On the other hand, studies about robotic training and conventional rehabilitation could be affected by the so-called "effectiveness paradox" [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

“…This consensus conference also reported that a lot of studies were focused on chronic stages of stroke, implicitly suggesting that neuroplasticity induced by robotic interventions may occur also in this phase [17]. On the other hand, studies about robotic training and conventional rehabilitation could be affected by the so-called "effectiveness paradox" [17][18][19]. This paradox highlights the discrepancy between the clinical approach, claiming that therapy should be personalized to be more effective, and the scientific approach which needs standardized therapeutic protocols to prove the efficacy of a treatment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Clinical Interpretation of Working Volume and Weight Support in Upper Limb Robotic Neurorehabilitation after Stroke

et al. 2021

Self Cite

View full text Add to dashboard Cite

In the past two decades, many studies reported the efficacy of upper limb robotic rehabilitation in patients after stroke, also in its chronic phase. Among the possible advantages of robotic therapy over conventional therapy are the objective measurements of kinematic and kinetic parameters during therapy, such as the spatial volume covered by the patient’s upper limb and the weight support provided by the robot. However, the clinical meaning and the usability of this information is still questioned. Forty patients with chronic stroke were enrolled in this study and assessed at the beginning of upper limb robotic therapy (Armeo® Power) and after two weeks (ten sessions) of therapy by recording the working volume and weight support provided by the robot and by administering six clinical scales to assess upper limb mobility, strength, spasticity, pain, neurological deficits, and independency. At baseline, the working volume significantly correlated with spasticity, whereas weight support significantly correlated with upper limb strength, pain, spasticity, and neurological deficits. After two weeks of robotic rehabilitation, all the clinical scores as well as the two parameters improved. However, the percentage changes in the working volume and weight support did not significantly correlate with any of the changes in clinical scores. These results suggest caution in using the robotic parameters as outcome measures because they could follow the general improvement of the patient, but complex relationships with clinical features are possible. Robotic parameters should be analyzed in combination with the clinical scores or other objective measures because they may be informative about therapy progression, and there is a need to combine their clinical, neuroscientific, and biomechanical results to avoid misleading interpretations.

show abstract

“…However, the literature is rather heterogeneous in terms of devices used, population investigated, and type of rehabilitation interventions. Moreover, in this solid but heterogeneous body of evidence, only a small fraction of previous research focused on rehabilitation in the developmental age [12].…”

Section: Introductionmentioning

confidence: 99%

Electromechanical and Robotic Devices for Gait and Balance Rehabilitation of Children with Neurological Disability: A Systematic Review

Valè

Gandolfi

Vignoli³

et al. 2021

Applied Sciences

Self Cite

View full text Add to dashboard Cite

In the last two decades, a growing interest has been focused on gait and balance robot-assisted rehabilitation in children with neurological disabilities. Robotic devices allow the implementation of intensive, task-specific training fostering functional recovery and neuroplasticity phenomena. However, limited attention has been paid to the protocols used in this research framework. This systematic review aims to provide an overview of the existing literature on robotic systems for the rehabilitation of gait and balance in children with neurological disabilities and their rehabilitation applications. The literature search was carried out independently and synchronously by three authors on the following databases: MEDLINE, Cochrane Library, PeDro, Institute of Electrical and Electronics Engineers, ScienceDirect, and Google Scholar. The data collected included three subsections referring to clinical, technical, and regulatory aspects. Thirty-one articles out of 81 found on the primary literature search were included in the systematic review. Most studies involved children with cerebral palsy. Only one-third of the studies were randomized controlled trials. Overall, 17 devices (nine end-effector systems and eight exoskeletons) were investigated, among which only 4 (24%) were bore the CE mark. Studies differ on rehabilitation protocols duration, intensity, and outcome measures. Future research should improve both rehabilitation protocols’ and devices’ descriptions.

show abstract

State of the art and challenges for the classification of studies on electromechanical and robotic devices in neurorehabilitation: a scoping review

Cited by 32 publications

References 28 publications

Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

Retrospective Robot-Measured Upper Limb Kinematic Data From Stroke Patients Are Novel Biomarkers

Clinical Interpretation of Working Volume and Weight Support in Upper Limb Robotic Neurorehabilitation after Stroke

Electromechanical and Robotic Devices for Gait and Balance Rehabilitation of Children with Neurological Disability: A Systematic Review

Contact Info

Product

Resources

About