ArticleScientific data2020
High-density surface electromyography signals during isometric contractions of elbow muscles of healthy humans.
Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 33 citations in OpenAlex.
- Evaluation of Different Controllers for Sensing-Based Movement Intention Estimation and Safe Tracking in a Simulated LSTM Network-Based Elbow Exoskeleton Robot.Sensors (Basel, Switzerland) · 2026Article
- Sarcopenia: Current Insights into Molecular Mechanisms, Diagnostics, and Emerging Interventional Approaches.International journal of molecular sciences · 2025Review
- Enhancing Upper Limb Exoskeletons Using Sensor-Based Deep Learning Torque Prediction and PID Control.Sensors (Basel, Switzerland) · 2025Article
- Enhanced rehabilitation after total joint replacement using a wearable high-density surface electromyography system.Frontiers in rehabilitation sciences · 2025Article
- Improving localization and measurements of M-waves using high-density surface electromyography.Journal of neurophysiology · 2025Article
- Innovative Approaches for the Treatment of Spinal Disorders: A Comprehensive Review.Journal of orthopaedics and sports medicine · 2025Article
- Non-Invasive and Quantitative Evaluation for Disuse Muscle Atrophy Caused by Immobilization After Limb Fracture Based on Surface Electromyography Analysis.Diagnostics (Basel, Switzerland) · 2024Article
- Hand Gesture Recognition Based on High-Density Myoelectricity in Forearm Flexors in Humans.Sensors (Basel, Switzerland) · 2024Article
- Article
- Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals.Scientific reports · 2023Article
- Detection and Reconstruction of Poor-Quality Channels in High-Density EMG Array Measurements.Sensors (Basel, Switzerland) · 2023Article
- A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction.Scientific data · 2023Article
- From fibre to function: are we accurately representing muscle architecture and performance?Biological reviews of the Cambridge Philosophical Society · 2022Review
- A Preliminary Study on the Use of HD-sEMG for the Functional Imaging of Equine Superficial Muscle Activation during Dynamic Mobilization Exercises.Animals : an open access journal from MDPI · 2022Article
- High-Density Electromyography Provides Improved Understanding of Muscle Function for Those With Amputation.Frontiers in medical technology · 2021Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 4 countries.
Funding
Abstract
This paper presents a dataset of high-density surface EMG signals (HD-sEMG) designed to study patterns of sEMG spatial distribution over upper limb muscles during voluntary isometric contractions. Twelve healthy subjects performed four different isometric tasks at different effort levels associated with movements of the forearm. Three 2-D electrode arrays were used for recording the myoelectric activity from five upper limb muscles: biceps brachii, triceps brachii, anconeus, brachioradialis, and pronator teres. Technical validation comprised a signals quality assessment from outlier detection algorithms based on supervised and non-supervised classification methods. About 6% of the total number of signals were identified as "bad" channels demonstrating the high quality of the recordings. In addition, spatial and intensity features of HD-sEMG maps for identification of effort type and level, have been formulated in the framework of this database, demonstrating better performance than the traditional time-domain features. The presented database can be used for pattern recognition and MUAP identification among other uses.
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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.