ArticleSensors (Basel, Switzerland)2019
Towards an Inertial Sensor-Based Wearable Feedback System for Patients after Total Hip Arthroplasty: Validity and Applicability for Gait Classification with Gait Kinematics-Based Features.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 3 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
29 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- In vivo biomechanics after total hip arthroplasty: a state-of-the-art systematic review.EFORT open reviews · 2026Pooled it
- The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- From One-Size-Fits-All to Data-Driven Recovery: A Narrative Review of Wearable Technologies Toward Personalized Rehabilitation After Total Hip and Knee Arthroplasty.Journal of personalized medicine · 2026Review
- Recovery trajectories of spatiotemporal gait after bipolar hemiarthroplasty versus closed reduction and internal fixation for unstable intertrochanteric fracture: a prospective wearable-sensor study.Journal of orthopaedic surgery and research · 2026Article
- An interpretable machine learning approach for predicting and grading hip osteoarthritis using gait analysis.BMC musculoskeletal disorders · 2025Article
- Instant gait classification for hip osteoarthritis patients: a non-wearable sensor approach utilizing Pearson correlation, SMAPE, and GMM.Biomedical engineering letters · 2025Article
- A Wearable Personalised Sonification and Biofeedback Device to Enhance Movement Awareness.Sensors (Basel, Switzerland) · 2024Article
- Effect of heel lift insertion on gait function in a patient with total hip arthroplasty with patient-perceived leg length difference: a case report.Journal of physical therapy science · 2024Article
- Accuracy validation of a wearable IMU-based gait analysis in healthy female.BMC sports science, medicine & rehabilitation · 2024Article
- Perioperative nursing care for hip arthroplasty patients with concomitant hypertension: A minireview.World journal of clinical cases · 2023Review
- Visual Gait Analysis Based on UE4.Sensors (Basel, Switzerland) · 2023Article
- Inertial Sensors for Hip Arthroplasty Rehabilitation: A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
- Machine Learning and Explainable Artificial Intelligence Using Counterfactual Explanations for Evaluating Posture Parameters.Bioengineering (Basel, Switzerland) · 2023Article
- Automated recognition of asymmetric gait and fatigue gait using ground reaction force data.Frontiers in physiology · 2023Article
- Sofigait-A Wireless Inertial Sensor-Based Gait Sonification System.Sensors (Basel, Switzerland) · 2022Article
- Acquisition of Lower-Limb Motion Characteristics with a Single Inertial Measurement Unit-Validation for Use in Physiotherapy.Diagnostics (Basel, Switzerland) · 2022Article
- IMU-Based Monitoring for Assistive Diagnosis and Management of IoHT: A Review.Healthcare (Basel, Switzerland) · 2022Review
- Inertial Measurement Units and Application for Remote Health Care in Hip and Knee Osteoarthritis: Narrative Review.JMIR rehabilitation and assistive technologies · 2022Review
- Explainable Artificial Intelligence and Wearable Sensor-Based Gait Analysis to Identify Patients with Osteopenia and Sarcopenia in Daily Life.Biosensors · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Patients after total hip arthroplasty (THA) suffer from lingering musculoskeletal restrictions. Three-dimensional (3D) gait analysis in combination with machine-learning approaches is used to detect these impairments. In this work, features from the 3D gait kinematics, spatio temporal parameters (Set 1) and joint angles (Set 2), of an inertial sensor (IMU) system are proposed as an input for a support vector machine (SVM) model, to differentiate impaired and non-impaired gait. The features were divided into two subsets. The IMU-based features were validated against an optical motion capture (OMC) system by means of 20 patients after THA and a healthy control group of 24 subjects. Then the SVM model was trained on both subsets. The validation of the IMU system-based kinematic features revealed root mean squared errors in the joint kinematics from 0.24° to 1.25°. The validity of the spatio-temporal gait parameters (STP) revealed a similarly high accuracy. The SVM models based on IMU data showed an accuracy of 87.2% (Set 1) and 97.0% (Set 2). The current work presents valid IMU-based features, employed in an SVM model for the classification of the gait of patients after THA and a healthy control. The study reveals that the features of Set 2 are more significant concerning the classification problem. The present IMU system proves its potential to provide accurate features for the incorporation in a mobile gait-feedback system for patients after THA.
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.