ReviewFrontiers in neurology2021
Biofeedback for Post-stroke Gait Retraining: A Review of Current Evidence and Future Research Directions in the Context of Emerging Technologies.
Review in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05904860 (Effects of Backward vs Forward Gait Training With Auditory Feedback in Patients With Stroke), which is not on this map. Cited by 41 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.
Effects of Backward vs Forward Gait Training With Auditory Feedback in Patients With Stroke
Who cites it
41 citing papers in PubMed, 2 syntheses or guidelines pooled it, 89 citations in OpenAlex.
- Can wearable real-time biofeedback gait training devices improve gait speed, balance, functional mobility and activities of daily living (ADL) in individuals post-stroke? A systematic review and meta-analysis of randomized controlled trials.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Effectiveness of sensor-based interventions in improving gait and balance performance in older adults: systematic review and meta-analysis of randomized controlled trials.Journal of neuroengineering and rehabilitation · 2024Pooled it
- Targeted ankle proprioceptive training improves balance, gait, and functional mobility in chronic stroke survivors: a multicenter randomized controlled trial with longitudinal follow-up.Journal of neuroengineering and rehabilitation · 2026Trial
- Targeted Biofeedback Training to Improve Gait Parameters in Subacute Stroke Patients: A Single-Blind Randomized Controlled Trial.Sensors (Basel, Switzerland) · 2024Trial
- Robotic Technologies for Hand Recovery After Stroke: A Reflection on Research Paths in Honor of Dr. Steven Wolf.Neurorehabilitation and neural repair · 2026Article
- Gait Biomechanics with Portable EMG Biofeedback at Increasing Muscle-Activation Goals: Walking Speed, Propulsion, Braking, and Step Length.Sensors (Basel, Switzerland) · 2026Article
- Effect of Combined Visual Biofeedback and Metronome on Gait Reciprocity in Patients with Ischemic Stroke: A Pilot Study.Bioengineering (Basel, Switzerland) · 2026Article
- Effects of Gait Biofeedback Training on Spatiotemporal Gait Parameters in Stroke Survivors: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.Brain sciences · 2026Review
- Using visual biofeedback to reduce step length error at fast walking speeds is feasible after stroke.medRxiv : the preprint server for health sciences · 2026Article
- Wearable Sensor Technology and Biomechanical Gait Analysis in Post-Stroke Rehabilitation: A Review with Implications for the Saudi Healthcare System.Neurosciences (Riyadh, Saudi Arabia) · 2026Review
- Effects of delay and amplification of auditory feedback for walking: anticipation, variability, and frequency adaptation.bioRxiv : the preprint server for biology · 2026Article
- Promoting Rehabilitation Using a Multimodal Internet of Things-Based Patient Monitoring System in a Smart Hospital.IEEE journal of translational engineering in health and medicine · 2026Article
- An innovative gamified gait biofeedback interface targeting propulsion: feasibility and preliminary effects.Research square · 2025Article
- Validity of Poststroke Gait Spatiotemporal and Joint Excursion Metrics Between Inertial Measurement Units and a Marker-Based System.Journal of applied biomechanics · 2025Article
- From Qualitative to Quantitative Functional Assessment in Stroke Rehabilitation with a Focus on Ultrasound Role.Biomedicines · 2025Review
- Robotic Ankle Exoskeleton and Limb Angle Biofeedback for Assisting Stroke Gait: A Feasibility Study.IEEE robotics and automation letters · 2025Article
- Advances in hemiplegia rehabilitation: modern therapeutic interventions to enhance activities of daily living.Frontiers in neurology · 2025Review
- Assessment of the effects of rehabilitation of hand function using a biometrics device in people after stroke - a randomized controlled trial.Frontiers in neurology · 2025Article
- Real-time augmented feedback for gait training: are gait responses affected by the choice of target parameter?Frontiers in bioengineering and biotechnology · 2025Article
- Effects of Haptic Feedback Interventions in Post-Stroke Gait and Balance Disorders: A Systematic Review and Meta-Analysis.Journal of personalized medicine · 2024Review
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
Abstract
Real-time gait biofeedback is a promising rehabilitation strategy for improving biomechanical deficits in walking patterns of post-stroke individuals. Because wearable sensor technologies are creating avenues for novel applications of gait biofeedback, including use in tele-health, there is a need to evaluate the state of the current evidence regarding the effectiveness of biofeedback for post-stroke gait training. The objectives of this review are to: (1) evaluate the current state of biofeedback literature pertaining to post-stroke gait training; and (2) determine future research directions related to gait biofeedback in context of evolving technologies. Our overall goal was to determine whether gait biofeedback is effective at improving stroke gait deficits while also probing why and for whom gait biofeedback may be an efficacious treatment modality. Our literature review showed that the effects of gait biofeedback on post-stroke walking dysfunction are promising but are inconsistent in methodology and therefore results. We summarize sources of methodological heterogeneity in previous literature, such as inconsistencies in feedback target, feedback mode, dosage, practice structure, feedback structure, and patient characteristics. There is a need for larger-sample studies that directly compare different feedback parameters, employ more uniform experimental designs, and evaluate characteristics of potential responders. However, as these uncertainties in existing literature are resolved, the application of gait biofeedback has potential to extend neurorehabilitation clinicians' cues to individuals with post-stroke gait deficits during ambulation in clinical, home, and community settings, thereby increasing the quantity and quality of skilled repetitions during task-oriented stepping training. In addition to identifying gaps in previous research, we posit that future research directions should comprise an amalgam of mechanism-focused and clinical research studies, to develop evidence-informed decision-making guidelines for gait biofeedback strategies that are tailored to individual-specific gait and sensorimotor impairments. Wearable sensor technologies have the potential to transform gait biofeedback and provide greater access and wider array of options for clinicians while lowering rehabilitation costs. Novel sensing technologies will be particularly valuable for telehealth and home-based stepping exercise programs. In summary, gait biofeedback is a promising intervention strategy that can enhance efficacy of post-stroke gait rehabilitation in both clinical and tele-rehabilitation settings and warrants more in-depth research.
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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.