ArticleTranslational neuroscience2023
Translation of surface electromyography to clinical and motor rehabilitation applications: The need for new clinical figures.
Article in Translational neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gait analysis methods in people with spinal cord injury: a systematic review.Journal of neuroengineering and rehabilitation · 2026Pooled it
- Effects of Transcranial Electrical Stimulation on Intermuscular Coherence in WuShu Sprint and KAN-Based EMG-Performance Function Fitting.Sensors (Basel, Switzerland) · 2025Trial
- Examining the test-retest reliability of commonly used neuromuscular, morphological, and functional measures in aging adults.GeroScience · 2025Article
- Editorial: Surface EMG and other measurement techniques in rehabilitation research and practice: are new educational programs needed?Frontiers in rehabilitation sciences · 2025Article
- Enhanced rehabilitation after total joint replacement using a wearable high-density surface electromyography system.Frontiers in rehabilitation sciences · 2025Article
- Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies.Sensors (Basel, Switzerland) · 2024Article
- Compare the Quadriceps Activity between Mini-Midvastus and Mini-Medial Parapatellar Approach in Total Knee Arthroplasty with Electromyography.Journal of clinical medicine · 2024Article
- Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches.Sensors (Basel, Switzerland) · 2024Article
- Integrating surface electromyography into physical therapy training with the support of STEM education.Frontiers in neurology · 2024Article
- Metrology in sEMG and movement analysis: the need for training new figures in clinical rehabilitation.Frontiers in rehabilitation sciences · 2024Review
- Surface EMG in China: a report on the 2023 surface EMG symposium.Frontiers in rehabilitation sciences · 2024Article
- Exploring knowledge, perception, and use of surface electromyography in physiotherapy post graduate trainees in Italy: a single center preliminary survey.Frontiers in rehabilitation sciences · 2024Article
- Strategies for STEM and SEMG applications in clinical practice-lessons from the past.Frontiers in rehabilitation sciences · 2024Article
- STEM education needs for human movement sciences professionals.Frontiers in neurology · 2024Article
- A Narrative Review on Multi-Domain Instrumental Approaches to Evaluate Neuromotor Function in Rehabilitation.Healthcare (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advanced sensors/electrodes and signal processing techniques provide powerful tools to analyze surface electromyographic signals (sEMG) and their features, to decompose sEMG into the constituent motor unit action potential trains, and to identify synergies, neural muscle drive, and EEG-sEMG coherence. However, despite thousands of articles, dozens of textbooks, tutorials, consensus papers, and European and International efforts, the translation of this knowledge into clinical activities and assessment procedures has been very slow, likely because of lack of clinical studies and competent operators in the field. Understanding and using sEMG-based hardware and software tools requires a level of knowledge of signal processing and interpretation concepts that is multidisciplinary and is not provided by most academic curricula in physiotherapy, movement sciences, neurophysiology, rehabilitation, sport, and occupational medicine. The chasm existing between the available knowledge and its clinical applications in this field is discussed as well as the need for new clinical figures. The need for updating the training of physiotherapists, neurophysiology technicians, and clinical technologists is discussed as well as the required competences of trainers and trainees. Indications and examples are suggested and provide a basis for addressing the problem. Two teaching examples are provided in the Supplementary Material.
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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.