ArticleSensors (Basel, Switzerland)2014
Mechanomyographic parameter extraction methods: an appraisal for clinical applications.
Article 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 15 papers, 2 of them syntheses that pooled it.
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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, 2 syntheses or guidelines pooled it, 54 citations in OpenAlex.
- Physiological factors affecting the mechanical performance of peripheral muscles: A perspective for long COVID patients through a systematic literature review.Frontiers in physiology · 2022Pooled it
- A systematic review of muscle activity assessment of the biceps brachii muscle using mechanomyography.Journal of musculoskeletal & neuronal interactions · 2018Pooled it
- Accessory respiratory muscles performance among people with spinal cord injury while singing songs with different musical parameters.PloS one · 2024Article
- Mechanomyographic Analysis for Muscle Activity Assessment during a Load-Lifting Task.Sensors (Basel, Switzerland) · 2023Article
- Phonomyography on Perioperative Neuromuscular Monitoring: An Overview.Sensors (Basel, Switzerland) · 2022Review
- A Coupled Piezoelectric Sensor for MMG-Based Human-Machine Interfaces.Sensors (Basel, Switzerland) · 2021Article
- Fatigue effect on cross-talk in mechanomyography signals of extensor and flexor forearm muscles during maximal voluntary isometric contractions.Journal of musculoskeletal & neuronal interactions · 2021Article
- Noninvasive Assessment of Neuromechanical Coupling and Mechanical Efficiency of Parasternal Intercostal Muscle during Inspiratory Threshold Loading.Sensors (Basel, Switzerland) · 2021Article
- A Multimodal Intention Detection Sensor Suite for Shared Autonomy of Upper-Limb Robotic Prostheses.Sensors (Basel, Switzerland) · 2020Article
- Mechanomyography-based muscle fatigue detection during electrically elicited cycling in patients with spinal cord injury.Medical & biological engineering & computing · 2019Article
- Performance Evaluation of Fixed Sample Entropy in Myographic Signals for Inspiratory Muscle Activity Estimation.Entropy (Basel, Switzerland) · 2019Article
- Mechanomyography and Torque during FES-Evoked Muscle Contractions to Fatigue in Individuals with Spinal Cord Injury.Sensors (Basel, Switzerland) · 2017Article
- Electromyography and Mechanomyography Signals During Swallowing in Healthy Adults and Head and Neck Cancer Survivors.Dysphagia · 2017Article
- Inspiratory muscle activation increases with COPD severity as confirmed by non-invasive mechanomyographic analysis.PloS one · 2017Article
- Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression.Sensors (Basel, Switzerland) · 2016Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.
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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.