ArticleArchives of public health = Archives belges de sante publique2023
Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review.
Article in Archives of public health = Archives belges de sante publique, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- Effects of Bilateral Robotic Arm Training in Stroke Patients: A Systematic Review and Meta-Analysis.Medical sciences (Basel, Switzerland) · 2026Pooled it
- Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis.Frontiers in human neuroscience · 2024Pooled it
- A Sensor-Based Upper Limb Treatment in Hemiplegic Patients: Results from a Randomized Pilot Study.Sensors (Basel, Switzerland) · 2024Trial
- Adaptive Sliding-Mode Controller with Grey Wolf Optimization and Interval Type-2 Fuzzy Logic System for Rehabilitation Lower-Limb Exoskeletons.Biomimetics (Basel, Switzerland) · 2026Article
- Robot-Assisted Gravity Compensation for Upper Limb Motor Rehabilitation: A Systematic Review.Bioengineering (Basel, Switzerland) · 2026Review
- Digital and virtual reality-based rehabilitation versus conventional therapy for rotator cuff tears and post-repair recovery: a systematic review and meta-analysis.JSES reviews, reports, and techniques · 2026Review
- Patient performance assessment methods for upper extremity rehabilitation in assist-as-needed therapy strategies: a comprehensive review.Medical & biological engineering & computing · 2025Review
- Care provided by humanoid robots: a scoping review.Investigacion y educacion en enfermeria · 2025Article
- Innovative Metaheuristic Optimization Approach with a Bi-Triad for Rehabilitation Exoskeletons.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNeuromotor rehabilitation and improvement of upper limb functions are necessary to improve the life quality of patients who have experienced injuries or have pathological outcomes. Modern approaches, such as robotic-assisted rehabilitation can help to improve rehabilitation processes and thus improve upper limb functions. Therefore, the aim of this study was to investigate the role of robots in upper limb disability improvement and rehabilitation.
methodsThis scoping review was conducted by search in PubMed, Web of Science, Scopus, and IEEE (January 2012- February 2022). Articles related to upper limb rehabilitation robots were selected. The methodological quality of all the included studies will be appraised using the Mixed Methods Appraisal Tool (MMAT). We used an 18-field data extraction form to extract data from articles and extracted the information such as study year, country, type of study, purpose, illness or accident leading to disability, level of disability, assistive technologies, number of participants in the study, sex, age, rehabilitated part of the upper limb using a robot, duration and frequency of treatment, methods of performing rehabilitation exercises, type of evaluation, number of participants in the evaluation process, duration of intervention, study outcomes, and study conclusions. The selection of articles and data extraction was made by three authors based on inclusion and exclusion criteria. Disagreements were resolved through consultation with the fifth author. Inclusion criteria were articles involving upper limb rehabilitation robots, articles about upper limb disability caused by any illness or injury, and articles published in English. Also, articles involving other than upper limb rehabilitation robots, robots related to rehabilitation of diseases other than upper limb, systematic reviews, reviews, and meta-analyses, books, book chapters, letters to the editor, and conference papers were also excluded. Descriptive statistics methods (frequency and percentage) were used to analyses the data.
resultsWe finally included 55 relevant articles. Most of the studies were done in Italy (33.82%). Most robots were used to rehabilitate stroke patients (80%). About 60.52% of the studies used games and virtual reality rehabilitate the upper limb disabilities using robots. Among the 14 types of applied evaluation methods, "evaluation and measurement of upper limb function and dexterity" was the most applied evaluation method. "Improvement in musculoskeletal functions", "no adverse effect on patients", and "Safe and reliable treatment" were the most cited outcomes, respectively.
conclusionsOur findings show that robots can improve musculoskeletal functions (musculoskeletal strength, sensation, perception, vibration, muscle coordination, less spasticity, flexibility, and range of motion) and empower people by providing a variety of rehabilitation capabilities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.