ArticleJournal of neural engineering2011
Accuracy assessment of CKC high-density surface EMG decomposition in biceps femoris muscle.
Article in Journal of neural engineering, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 65 citations in OpenAlex.
- Timing and Modulation of Activity in the Lower Limb Muscles During Indoor Rowing: What Are the Key Muscles to Target in FES-Rowing Protocols?Sensors (Basel, Switzerland) · 2020Trial
- Stretch versus shortening contractions subsequently decrease versus increase neural drive to the human tibialis anterior.Experimental physiology · 2026Article
- Neuromuscular adaptations in soleus and tibialis anterior muscles in persons with spinal cord injury.Journal of neuroengineering and rehabilitation · 2025Article
- Effects of blood flow restriction on motoneurons synchronization.Frontiers in neural circuits · 2025Article
- Antagonist Activation Measurement in Triceps Surae Using High-Density and Bipolar Surface EMG in Chronic Hemiparesis.Sensors (Basel, Switzerland) · 2024Article
- Decoding firings of a large population of human motor units from high-density surface electromyogram in response to transcranial magnetic stimulation.The Journal of physiology · 2023Article
- Motor Unit Number Estimation in Spastic Biceps Brachii Muscles of Chronic Stroke Survivors Before and After BoNT Injection.IEEE transactions on bio-medical engineering · 2023Article
- Startling stimuli increase maximal motor unit discharge rate and rate of force development in humans.Journal of neurophysiology · 2022Article
- Motor unit distribution and recruitment in spastic and non-spastic bilateral biceps brachii muscles of chronic stroke survivors.Journal of neural engineering · 2022Article
- Caution Is Necessary for Acceptance of Motor Units With Intermediate Matching in Surface EMG Decomposition.Frontiers in neuroscience · 2022Article
- Surface Electromyography: What Limits Its Use in Exercise and Sport Physiology?Frontiers in neurology · 2020Review
- Amplitude cancellation influences the association between frequency components in the neural drive to muscle and the rectified EMG signal.PLoS computational biology · 2019Article
- Non-invasive Decoding of the Motoneurons: A Guided Source Separation Method Based on Convolution Kernel Compensation With Clustered Initial Points.Frontiers in computational neuroscience · 2019Article
- A Novel Validation Approach for High-Density Surface EMG Decomposition in Motor Neuron Disease.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018Article
- Functional mapping of the pelvic floor and sphincter muscles from high-density surface EMG recordings.International urogynecology journal · 2016Article
- Motor unit number estimation based on high-density surface electromyography decomposition.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2016Article
- Preferential distribution of nociceptive input to motoneurons with muscle units in the cranial portion of the upper trapezius muscle.Journal of neurophysiology · 2016Article
- Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition.Neural plasticity · 2016Article
- A Novel Framework Based on FastICA for High Density Surface EMG Decomposition.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2016Article
- Estimating reflex responses in large populations of motor units by decomposition of the high-density surface electromyogram.The Journal of physiology · 2015Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 4 countries.
Funding
Abstract
The aim of this study was to assess the accuracy of the convolution kernel compensation (CKC) method in decomposing high-density surface EMG (HDsEMG) signals from the pennate biceps femoris long-head muscle. Although the CKC method has already been thoroughly assessed in parallel-fibered muscles, there are several factors that could hinder its performance in pennate muscles. Namely, HDsEMG signals from pennate and parallel-fibered muscles differ considerably in terms of the number of detectable motor units (MUs) and the spatial distribution of the motor-unit action potentials (MUAPs). In this study, monopolar surface EMG signals were recorded from five normal subjects during low-force voluntary isometric contractions using a 92-channel electrode grid with 8 mm inter-electrode distances. Intramuscular EMG (iEMG) signals were recorded concurrently using monopolar needles. The HDsEMG and iEMG signals were independently decomposed into MUAP trains, and the iEMG results were verified using a rigorous a posteriori statistical analysis. HDsEMG decomposition identified from 2 to 30 MUAP trains per contraction. 3 ± 2 of these trains were also reliably detected by iEMG decomposition. The measured CKC decomposition accuracy of these common trains over a selected 10 s interval was 91.5 ± 5.8%. The other trains were not assessed. The significant factors that affected CKC decomposition accuracy were the number of HDsEMG channels that were free of technical artifact and the distinguishability of the MUAPs in the HDsEMG signal (P < 0.05). These results show that the CKC method reliably identifies at least a subset of MUAP trains in HDsEMG signals from low force contractions in pennate muscles.
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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.