ReviewBehavioural neurology2017
Robotics in Lower-Limb Rehabilitation after Stroke.
Review in Behavioural neurology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 41 papers, 4 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.
The Effects of Gait Rehabilitation Using Treadmill-based Robotics (Exoskeletons or End-effectors) Versus Traditional Physical Therapy in Stroke Survivors: a Multicenter Controlled Non-randomized Trial
The Effect of Combined Transcranial Pulse Current Stimulation (tPCS) and Transcutaneous Electrical Nerve Stimulation (TENS) on Lower Limb Motor Function in Subacute to Chronic Stroke Patients With Hemiplegia: A Double-blind, Sham-controlled, Randomized Controlled Study
Who cites it
41 citing papers in PubMed, 4 syntheses or guidelines pooled it, 148 citations in OpenAlex.
- The efficacy of exoskeleton robotic training on ambulation recovery in patients with spinal cord injury: A meta-analysis.The journal of spinal cord medicine · 2024Pooled it
- Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness.Journal of neuroengineering and rehabilitation · 2023Pooled it
- Pooled it
- Wearable Ankle Robots in Post-stroke Rehabilitation of Gait: A Systematic Review.Frontiers in neurorobotics · 2019Pooled it
- Effects of different intensity training with a lower limb exoskeleton robot on walking function in people with subacute stroke: a randomized controlled trial.Journal of neuroengineering and rehabilitation · 2026Trial
- Development and Upgrade of a Robot That Enables Three-Dimensional Trunk Motion and Lower Limb Exercise for Stroke Patients: A Pilot Clinical Investigation Including a User Feasibility Test.BioMed research international · 2026Trial
- Enhanced rehabilitation for unstable pelvic tile C fractures: integrating mechanotherapy and early intervention.Journal of orthopaedic surgery and research · 2025Trial
- Exoskeleton rehabilitation robot training for balance and lower limb function in sub-acute stroke patients: a pilot, randomized controlled trial.Journal of neuroengineering and rehabilitation · 2024Trial
- Three-Dimensional Gait Analysis and sEMG Measures for Robotic-Assisted Gait Training in Subacute Stroke: A Randomized Controlled Trial.BioMed research international · 2023Trial
- Adaptive intelligent controller for a lower limb rehabilitation robot using QAOA-based online membership optimization.Scientific reports · 2026Article
- Priming iTBS for lower limb rehabilitation after stroke: Protocol for a randomized controlled trial on efficacy and neuroplasticity.PloS one · 2026Article
- Modern Technologies Supporting Motor Rehabilitation After Stroke: A Narrative Review.Journal of clinical medicine · 2025Review
- Development of a Bayesian Network-Based Parallel Mechanism for Lower Limb Gait Rehabilitation.Biomimetics (Basel, Switzerland) · 2025Article
- Effects of robot rehabilitation on the motor function and gait in children with cerebral palsy: a systematic review and meta-analysis.Journal of exercise rehabilitation · 2024Review
- Therapeutic robots for post-stroke rehabilitation.Medical review (2021) · 2024Review
- AI-based methodologies for exoskeleton-assisted rehabilitation of the lower limb: a review.Frontiers in robotics and AI · 2024Review
- Socially interactive agents for robotic neurorehabilitation training: conceptualization and proof-of-concept study.Frontiers in artificial intelligence · 2024Article
- Traditional Chinese Rehabilitation Exercise (TCRE) for Myofascial Pain: Current Evidence and Further Challenges.Journal of pain research · 2024Review
- Adaptive Gait Training of a Lower Limb Rehabilitation Robot Based on Human-Robot Interaction Force Measurement.Cyborg and bionic systems (Washington, D.C.) · 2024Article
- [Multi-modal synergistic quantitative analysis and rehabilitation assessment of lower limbs for exoskeleton].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the increase in the elderly, stroke has become a common disease, often leading to motor dysfunction and even permanent disability. Lower-limb rehabilitation robots can help patients to carry out reasonable and effective training to improve the motor function of paralyzed extremity. In this paper, the developments of lower-limb rehabilitation robots in the past decades are reviewed. Specifically, we provide a classification, a comparison, and a design overview of the driving modes, training paradigm, and control strategy of the lower-limb rehabilitation robots in the reviewed literature. A brief review on the gait detection technology of lower-limb rehabilitation robots is also presented. Finally, we discuss the future directions of the lower-limb rehabilitation robots.
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.