ReviewMaterials (Basel, Switzerland)2020
EMG Characterization and Processing in Production Engineering.
Review in Materials (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- From Signal Stacking to Dynamic Coupling: A Critical Review of Wearable EEG-EMG Fusion Brain-Computer Interfaces for Stroke Rehabilitation.Micromachines · 2026Review
- EMG-Spectrogram-Empowered CNN Stroke-Classifier Model Development.Life (Basel, Switzerland) · 2026Article
- Muscle fatigue assessment using surface electromyography in farm operations performed in protected cultivation.Scientific reports · 2025Article
- Developing a Vital Signal Detection Electrode for Fabric Substrate Using a High-Performance Conductive Carbon-Based Ink.IEEE open journal of engineering in medicine and biology · 2025Article
- Development of a Wearable Electromyographic Sensor with Aerosol Jet Printing Technology.Bioengineering (Basel, Switzerland) · 2024Article
- Surface Electromyography in Dentistry-Past, Present and Future.Journal of clinical medicine · 2024Review
- Multisensory Evaluation of Muscle Activity and Human Manipulability during Upper Limb Motor Tasks.Biosensors · 2023Article
- Evaluation of Novel Embroidered Textile-Electrodes Made from Hybrid Polyamide Conductive Threads for Surface EMG Sensing.Sensors (Basel, Switzerland) · 2023Article
- Workload Assessment of Tractor Operations with Ergonomic Transducers and Machine Learning Techniques.Sensors (Basel, Switzerland) · 2023Article
- Human Motion Pattern Recognition and Feature Extraction: An Approach Using Multi-Information Fusion.Micromachines · 2022Article
- Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020).Materials (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Electromyography (EMG) signals are biomedical signals that measure electrical currents generated during muscle contraction. These signals are strongly influenced by physiological and anatomical characteristics of the muscles and represent the neuromuscular activities of the human body. The evolution of EMG analysis and acquisition techniques makes this technology more reliable for production engineering applications, overcoming some of its inherent issues. Taking as an example, the fatigue monitoring of workers as well as enriched human-machine interaction (HMI) systems used in collaborative tasks are now possible with this technology. The main objective of this research is to evaluate the current implementation of EMG technology within production engineering, its weaknesses, opportunities, and synergies with other technologies, with the aim of developing more natural and efficient HMI systems that could improve the safety and productivity within production environments.
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.