ArticleSensors (Basel, Switzerland)2021
EMG and Joint Angle-Based Machine Learning to Predict Future Joint Angles at the Knee.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed, 49 citations in OpenAlex.
- Multi-Source Motion Inputs and FA-TA-BiLSTM for Lower-Limb Joint Angle Prediction.Sensors (Basel, Switzerland) · 2026Article
- RTGNet: A Dual-Branch Network Integrating Recurrent Texture and Temporal Dynamics from sEMG for Lower-Limb Joint Angle Prediction.Sensors (Basel, Switzerland) · 2026Article
- A Pilot Study on Motion Intention Mapping and Direct Myoelectric Control Method for Prosthetic Knee Based on LSTM Network and Human-Machine Coupling Model.Sensors (Basel, Switzerland) · 2025Article
- Evaluating the Performance of Joint Angle Estimation Algorithms on an Exoskeleton Mock-Up via a Modular Testing Approach.Sensors (Basel, Switzerland) · 2024Article
- The Effect of Sensor Feature Inputs on Joint Angle Prediction across Simple Movements.Sensors (Basel, Switzerland) · 2024Article
- A Systems Approach to Biomechanics, Mechanobiology, and Biotransport.Journal of biomechanical engineering · 2024Article
- Prediction of Joint Angles Based on Human Lower Limb Surface Electromyography.Sensors (Basel, Switzerland) · 2023Article
- Integrating intention-based systems in human-robot interaction: a scoping review of sensors, algorithms, and trust.Frontiers in robotics and AI · 2023Article
- Article
- Lower Body Joint Angle Prediction Using Machine Learning and Applied Biomechanical Inverse Dynamics.Sensors (Basel, Switzerland) · 2022Article
- An ergonomic assessment tool for evaluating the effect of back exoskeletons on injury risk.Applied ergonomics · 2022Article
- Machine Learning-Based Performance Comparison to Diagnose Anterior Cruciate Ligament Tears.Journal of healthcare engineering · 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
5 authors at 1 institution in 1 country.
Funding
Abstract
Electromyography (EMG) is commonly used to measure electrical activity of the skeletal muscles. As exoskeleton technology advances, these signals may be used to predict human intent for control purposes. This study used an artificial neural network trained and tested with knee flexion angles and knee muscle EMG signals to predict knee flexion angles during gait at 50, 100, 150, and 200 ms into the future. The hypothesis of this study was that the algorithm's prediction accuracy would only be affected by time into the future, not subject, gender or side, and that as time into the future increased, the prediction accuracy would decrease. A secondary hypothesis was that as the number of algorithm training trials increased, the prediction accuracy of the artificial neural network (ANN) would increase. The results of this study indicate that only time into the future affected the accuracy of knee flexion angle prediction (
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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.