ArticleBiomedical engineering online2020
Motor improvement estimation and task adaptation for personalized robot-aided therapy: a feasibility study.
Article in Biomedical engineering online, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02770300 (Effect of an Automatic Personalized Robot-assisted Rehabilitation on Cortical Organization and Clinical Recovery After Stroke), which is not on this map. Cited by 10 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Effect of an Automatic Personalized Robot-assisted Rehabilitation on Cortical Organization and Clinical Recovery After Stroke
Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- On the correlation between training modalities and recovery stages in poststroke robotic rehabilitation of the upper limb: a systematic review.Journal of neuroengineering and rehabilitation · 2026Pooled it
- Artificial intelligence in rehabilitation: a living systematic mapping review - first release.European journal of physical and rehabilitation medicine · 2025Pooled it
- A multimodal machine learning approach to forecast upper limb motor recovery after stroke using kinematic and electromyographic data - A pilot-study.Journal of neuroengineering and rehabilitation · 2026Article
- Relearning Upper Limb Proprioception After Stroke Through Robotic Therapy: A Feasibility Analysis.Journal of clinical medicine · 2025Article
- A fuzzy-logic approach for longitudinal assessment of patients' psychophysiological state: an application to upper-limb orthopedic robot-aided rehabilitation.Journal of neuroengineering and rehabilitation · 2024Article
- Novel evaluation of upper-limb motor performance after stroke based on normal reaching movement model.Journal of neuroengineering and rehabilitation · 2023Article
- An online method to monitor hand muscle tone during robot-assisted rehabilitation.Frontiers in robotics and AI · 2023Article
- Orientation control strategies and adaptation to a visuomotor perturbation in rotational hand movements.PLoS computational biology · 2022Article
- Neurorehabilitation From a Distance: Can Intelligent Technology Support Decentralized Access to Quality Therapy?Frontiers in robotics and AI · 2021Article
- Global trends in wearable sensors for stroke motor rehabilitation: A bibliometric analysis.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
Abstract
backgroundIn the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients' individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches.
methodsHere, we present a model-based approach to personalize robot-aided rehabilitation therapy within training sessions. The proposed method combines the information from different motor performance measures recorded from the robot to continuously estimate patients' motor improvement for a series of point-to-point reaching movements in different directions. Additionally, it comprises a personalization routine to automatically adapt the rehabilitation training. We engineered our approach using an upper-limb exoskeleton. The implementation was tested with 17 healthy subjects, who underwent a motor-adaptation paradigm, and two subacute stroke patients, exhibiting different degrees of motor impairment, who participated in a pilot test undergoing rehabilitative motor training.
resultsThe results of the exploratory study with healthy subjects showed that the participants divided into fast and slow adapters. The model was able to correctly estimate distinct motor improvement progressions between the two groups of participants while proposing individual training protocols. For the two pilot patients, an analysis of the selected motor performance measures showed that both patients were able to retain the improvements gained during training when reaching movements were reintroduced at a later stage. These results suggest that the automated training adaptation was appropriately timed and specifically tailored to the abilities of each individual.
conclusionsThe results of our exploratory study demonstrated the feasibility of the proposed model-based approach for the personalization of robot-aided rehabilitation therapy. The pilot test with two subacute stroke patients further supported our approach, while providing encouraging results for the applicability in clinical settings. Trial registration This study is registered in ClinicalTrials.gov (NCT02770300, registered 30 March 2016, https://clinicaltrials.gov/ct2/show/NCT02770300).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.