ArticleSensors (Basel, Switzerland)2024
Measuring Surface Electromyography with Textile Electrodes in a Smart Leg Sleeve.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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Who cites it
4 citing papers in PubMed.
- Automatic Identification of Lower-Limb Neuromuscular Activation Patterns During Gait Using a Textile Wearable Multisensor System.Sensors (Basel, Switzerland) · 2026Article
- Development and Experimental Validation of an Integrated Evaluation Framework for EMS Smartwear Electrodes.Sensors (Basel, Switzerland) · 2025Article
- Continuous biosignal acquisition beyond the limit of epidermal turnover.Materials horizons · 2025Review
- A Low-Profile High-Density Electromyography Neckband for Recording Neck Muscle Activity.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents the design, development, and validation of a novel e-textile leg sleeve for non-invasive Surface Electromyography (sEMG) monitoring. This wearable device incorporates e-textile sensors for sEMG signal acquisition from the lower limb muscles, specifically the anterior tibialis and lateral gastrocnemius. Validation was conducted by performing a comparative study with eleven healthy volunteers to evaluate the performance of the e-textile sleeve in acquiring sEMG signals compared to traditional Ag/AgCl electrodes. The results demonstrated strong agreement between the e-textile and conventional methods in measuring descriptive metrics of the signals, including area, power, mean, and root mean square. The paired data
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Registered trials
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