ArticleScientific reports2019
Open-Source Remote Gait Analysis: A Post-Surgery Patient Monitoring Application.
Article in Scientific reports, 2019. 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 34 papers, 1 of them a synthesis 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.
Sensor Ankle Brace for Special Operations Rehabilitation - Phase 1
Sensor Ankle Brace for Special Operations Rehabilitation - Phase 2
Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Estimating Biomechanical Time-Series with Wearable Sensors: A Systematic Review of Machine Learning Techniques.Sensors (Basel, Switzerland) · 2019Pooled it
- Wearable Sensing for Clinical Physiology Monitoring: Emerging Paradigms.Physiology (Bethesda, Md.) · 2026Review
- Time-stratified daily walking speed measurement via smartphone and its predictive utility for mild cognitive impairment.Scientific reports · 2026Article
- Artificial intelligence in orthopaedics: Enhanced examinations, ambient intelligence and the future of clinical practice.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Review
- Laboratory Environments Mask Gait Differences Between Healthy Participants and Patients With Anterior Cruciate Ligament Reconstruction.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026Article
- Monitoring Gait Recovery After Total Knee Arthroplasty Using Wearable Sensors: Responsiveness of Gait Accelerations.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025Observational
- Review
- Augmenting a ResNet + BiLSTM Deep Learning Model with Clinical Mobility Data Helps Outperform a Heuristic Frequency-Based Model for Walking Bout Segmentation.Sensors (Basel, Switzerland) · 2025Article
- Wearables research for continuous monitoring of patient outcomes: A scoping review.PLOS digital health · 2025Article
- Correlation between gait analysis parameters and joint function prognosis during rehabilitation after anterior cruciate ligament reconstruction: a retrospective study.American journal of translational research · 2025Article
- Gait Pattern Analysis: Integration of a Highly Sensitive Flexible Pressure Sensor on a Wireless Instrumented Insole.Sensors (Basel, Switzerland) · 2024Article
- Gaitmap-An Open Ecosystem for IMU-Based Human Gait Analysis and Algorithm Benchmarking.IEEE open journal of engineering in medicine and biology · 2024Article
- Enhancing Wearable Gait Monitoring Systems: Identifying Optimal Kinematic Inputs in Typical Adolescents.Sensors (Basel, Switzerland) · 2023Article
- Challenges and advances in the use of wearable sensors for lower extremity biomechanics.Journal of biomechanics · 2023Article
- Monitoring External Workload With Wearable Technology After Anterior Cruciate Ligament Reconstruction: A Scoping Review.Orthopaedic journal of sports medicine · 2023Article
- Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities.Heliyon · 2023Review
- A scoping review of portable sensing for out-of-lab anterior cruciate ligament injury prevention and rehabilitation.NPJ digital medicine · 2023Article
- Digitalization in orthopaedics: a narrative review.Frontiers in surgery · 2023Review
- Open-porous magnesium-based scaffolds withstandBioactive materials · 2023Article
- Ensemble averaging for categorical variables: Validation study of imputing lost data in 24-h recorded postures of inpatients.Frontiers in physiology · 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
7 authors.
Funding
Abstract
Critical to digital medicine is the promise of improved patient monitoring to allow assessment and personalized intervention to occur in real-time. Wearable sensor-enabled observation of physiological data in free-living conditions is integral to this vision. However, few open-source algorithms have been developed for analyzing and interpreting these data which slows development and the realization of digital medicine. There is clear need for open-source tools that analyze free-living wearable sensor data and particularly for gait analysis, which provides important biomarkers in multiple clinical populations. We present an open-source analytical platform for automated free-living gait analysis and use it to investigate a novel, multi-domain (accelerometer and electromyography) asymmetry measure for quantifying rehabilitation progress in patients recovering from surgical reconstruction of the anterior cruciate ligament (ACL). Asymmetry indices extracted from 41,893 strides were more strongly correlated (r = -0.87, p < 0.01) with recovery time than standard step counts (r = 0.25, p = 0.52) and significantly differed between patients 2- and 17-weeks post-op (p < 0.01, effect size: 2.20-2.96), and controls (p < 0.01, effect size: 1.74-4.20). Results point toward future use of this open-source platform for capturing rehabilitation progress and, more broadly, for free-living gait analysis.
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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.