SynthesisSensors (Basel, Switzerland)2014
The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury.
Synthesis in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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.
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, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Strategies for Rapid Muscle Fatigue Reduction during FES Exercise in Individuals with Spinal Cord Injury: A Systematic Review.PloS one · 2016Pooled it
- Evoked EMG versus muscle torque during fatiguing functional electrical stimulation-evoked muscle contractions and short-term recovery in individuals with spinal cord injury.Sensors (Basel, Switzerland) · 2014Trial
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- Innovative stimulated muscle contraction signals based digital muscle marker: a reliable tool for assessing muscle in persons with stroke.Journal of neuroengineering and rehabilitation · 2025Article
- Recognition of Human Lower Limb Motion and Muscle Fatigue Status Using a Wearable FES-sEMG System.Sensors (Basel, Switzerland) · 2024Article
- Measuring and modeling the effects of vagus nerve stimulation on heart rate and laryngeal muscles.Bioelectronic medicine · 2023Article
- Ultrasound Echogenicity as an Indicator of Muscle Fatigue during Functional Electrical Stimulation.Sensors (Basel, Switzerland) · 2022Article
- Electrical Stimulation Frequency and Skeletal Muscle Characteristics: Effects on Force and Fatigue.European journal of translational myology · 2017Article
- A Neuromuscular Electrical Stimulation (NMES) and robot hybrid system for multi-joint coordinated upper limb rehabilitation after stroke.Journal of neuroengineering and rehabilitation · 2017Article
- Game design to measure reflexes and attention based on biofeedback multi-sensor interaction.Sensors (Basel, Switzerland) · 2015Article
- Mechanomyographic parameter extraction methods: an appraisal for clinical applications.Sensors (Basel, Switzerland) · 2014Article
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 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05) between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population.
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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.