ArticleSensors (Basel, Switzerland)2025
A Deep Learning-Based Framework Oriented to Pathological Gait Recognition with Inertial Sensors.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Safety-Driven Approaches in Human-Robot Collaborative Systems.Sensors (Basel, Switzerland) · 2026Pooled it
- Differential Effects of Abdominal Bracing and Hollowing on Scapular Muscle Activation Patterns During the Y-Raise Exercise.Journal of clinical medicine · 2026Article
- GaitIntent: A Kinematic Dataset Focusing on Steady-State to Transitional Locomotion for Lower-Limb Motion Rehabilitation.Scientific data · 2026Article
- Influence of Vamp Opening Configuration on Foot-Footwear Biomechanics: A Finite Element Analysis of Women's Low-Heeled Court Shoes.Bioengineering (Basel, Switzerland) · 2026Article
- Integrating statistical parametric mapping, functional principal component analysis, explainable machine learning, and equivalence testing for multimodal gait signal analysis.BMC biomedical engineering · 2026Article
- Radiomics and Artificial Intelligence in Ovarian Endometriosis Imaging: A Systematic Review and Critical Appraisal of Emerging Evidence.Bioengineering (Basel, Switzerland) · 2026Review
- Explainable machine learning for automated robotic surgical skill assessment using rich kinematic features.Journal of robotic surgery · 2026Article
- Distinct Roles of Muscle Strength and Postural Stability in Objective and Subjective Function in Women with Bilateral Knee Osteoarthritis.Healthcare (Basel, Switzerland) · 2026Article
- Effect of virtual reality environment complexity on tolerance and locomotor performance in healthy subjects.Scientific reports · 2026Article
- Recognition of Gait Alterations Induced by Alcohol-Impairment Simulation Goggles Using Smartphone Accelerometer Signals.Sensors (Basel, Switzerland) · 2026Article
- Validity of a Commercially Available Inertial Measurement Unit for Artificial Intelligence-Based Trick Detection and Kinematic Performance Assessment in Skateboarding.Sensors (Basel, Switzerland) · 2026Article
- Delayed Postural Responses to Fear of Falling During Gait Initiation in Low Vision: Insights from Virtual-Reality-Based Fear Simulation.Healthcare (Basel, Switzerland) · 2026Article
- From Simplified Markers to Muscle Function: A Deep Learning Approach for Personalized Cervical Biomechanics Assessment Powered by Massive Musculoskeletal Simulation.Sensors (Basel, Switzerland) · 2026Article
- Subject-independent gait activity recognition using DSAF: dual-stream IMU-EMG attention fusion with asymmetric temporal encoding and physiological complementarity weighting.Frontiers in neurorobotics · 2026Article
- Multimodal human action recognition and personalized sports health promotion: a deep learning framework integrating wearable sensor fusion.Frontiers in neurorobotics · 2026Article
- Gait Parameters of Women Before Knee Joint Arthritis-Analysis Using the MoKA System.Sensors (Basel, Switzerland) · 2025Article
- A deep learning pipeline for detecting vestibular schwannoma patients with unilateral vestibular loss based on kinematic data.Scientific reports · 2025Article
- Automated EMG-Based Classification of Upper Extremity Motor Impairment Levels in Subacute Stroke.Sensors (Basel, Switzerland) · 2025Article
- Efficient Human Posture Recognition and Assessment in Visual Sensor Systems: An Experimental Study.Sensors (Basel, Switzerland) · 2025Article
- A 1-Dimensional Physiological Signal Prediction Method Based on Composite Feature Preprocessing and Multi-Scale Modeling.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abnormal locomotor patterns may occur in case of either motor damages or neurological conditions, thus potentially jeopardizing an individual's safety. Pathological gait recognition (PGR) is a research field that aims to discriminate among different walking patterns. A PGR-oriented system may benefit from the simulation of gait disorders by healthy subjects, since the acquisition of actual pathological gaits would require either a higher experimental time or a larger sample size. Only a few works have exploited abnormal walking patterns, emulated by unimpaired individuals, to perform PGR with Deep Learning-based models. In this article, the authors present a workflow based on convolutional neural networks to recognize normal and pathological locomotor behaviors by means of inertial data related to nineteen healthy subjects. Although this is a preliminary feasibility study, its promising performance in terms of accuracy and computational time pave the way for a more realistic validation on actual pathological data. In light of this, classification outcomes could support clinicians in the early detection of gait disorders and the tracking of rehabilitation advances in real time.
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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.