SynthesisBiomedical engineering online2021
Assessment of muscle activity using electrical stimulation and mechanomyography: a systematic review.
Synthesis in Biomedical engineering online, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Electromechanical efficiency index of skeletal muscle and its applicability: a systematic review.Frontiers in bioengineering and biotechnology · 2024Pooled it
- 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
- Electrical stimulation reduces post-exercise muscle stiffness and enhances flexibility in hamstring muscles.European journal of applied physiology · 2026Article
- Live magnetomyography and robotic-hand proxy control using a wearable triaxial optically pumped magnetometer.Scientific reports · 2026Article
- Open-Source Tools for Neuromuscular Electrical Stimulation in Mouse Models: A Methodological Validation Study.Muscles (Basel, Switzerland) · 2026Article
- Threshold-Anchored Mechanomyography Metrics for Patient Stratification in Spinal Decompression: Associations with Early Pain Outcomes.Journal of personalized medicine · 2025Article
- Comparing the effects of 25-minute electrical muscle stimulation vs. 90-minute full-body resistance training on body composition and strength: A 20-week intervention.Journal of exercise science and fitness · 2025Article
- [Feasibility study on biomechanical indicators as supplementary evaluation to Musculoskeletal Tumor Society Scoring System for amputee patients].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2025Article
- Neuromuscular Electrical Stimulation Enhances Lower Limb Muscle Synergies During Jumping in Martial Artists Post-Anterior Cruciate Ligament Reconstruction: A Randomized Crossover Trial.Bioengineering (Basel, Switzerland) · 2025Article
- Estimation of elbow flexion torque from anthropometric and NMES MMG variables using random forest regression.Scientific reports · 2025Article
- Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression.Frontiers in rehabilitation sciences · 2025Article
- Estimation of joint torque in dynamic activities using wearable A-mode ultrasound.Nature communications · 2024Article
- Effect of Forearm Postures and Elbow Joint Angles on Elbow Flexion Torque and Mechanomyography in Neuromuscular Electrical Stimulation of the Biceps Brachii.Sensors (Basel, Switzerland) · 2023Article
- A feasibility study on AI-controlled closed-loop electrical stimulation implants.Scientific reports · 2023Article
- Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS-SVR.Sensors (Basel, Switzerland) · 2022Article
- Toward a wearable monitor of local muscle fatigue during electrical muscle stimulation using tissue Doppler imaging.Wearable technologies · 2022Article
- Mechanomyography as a novel marker of nerve dysfunction and recovery in chronic entrapment neuropathy.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This research has proved that mechanomyographic (MMG) signals can be used for evaluating muscle performance. Stimulation of the lost physiological functions of a muscle using an electrical signal has been determined crucial in clinical and experimental settings in which voluntary contraction fails in stimulating specific muscles. Previous studies have already indicated that characterizing contractile properties of muscles using MMG through neuromuscular electrical stimulation (NMES) showed excellent reliability. Thus, this review highlights the use of MMG signals on evaluating skeletal muscles under electrical stimulation. In total, 336 original articles were identified from the Scopus and SpringerLink electronic databases using search keywords for studies published between 2000 and 2020, and their eligibility for inclusion in this review has been screened using various inclusion criteria. After screening, 62 studies remained for analysis, with two additional articles from the bibliography, were categorized into the following: (1) fatigue, (2) torque, (3) force, (4) stiffness, (5) electrode development, (6) reliability of MMG and NMES approaches, and (7) validation of these techniques in clinical monitoring. This review has found that MMG through NMES provides feature factors for muscle activity assessment, highlighting standardized electromyostimulation and MMG parameters from different experimental protocols. Despite the evidence of mathematical computations in quantifying MMG along with NMES, the requirement of the processing speed, and fluctuation of MMG signals influence the technique to be prone to errors. Interestingly, although this review does not focus on machine learning, there are only few studies that have adopted it as an alternative to statistical analysis in the assessment of muscle fatigue, torque, and force. The results confirm the need for further investigation on the use of sophisticated computations of features of MMG signals from electrically stimulated muscles in muscle function assessment and assistive technology such as prosthetics control.
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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.