State of the art review: Intravaginal probes for recording electromyography from the pelvic floor muscles
Bibliographic record
Abstract
AIM: To survey commercially available intravaginal probes designed to record electromyography (EMG) from the pelvic floor muscles (PFMs), and to discuss the strengths and limitations of current technology. METHODS: The MEDLINE EMBASE, CINAHL, PEDRO, and Cochrane databases were searched for articles in which intravaginal probes were described as having been used to record EMG from the PFMs. The World Wide Web was also searched using the Google search engine to find devices used to record EMG from the PFMs. Finally, a Canadian distributer of intravaginal probes was contacted to identify intravaginal EMG probes not identified through other methods. The specifications of each probe were determined through the manufacturer or their website, and each device was acquired by the investigators to verify the specifications and electrode configuration. The devices were evaluated against international standards for recording EMG data. RESULTS: Sixteen different models of commercially available intravaginal probes were identified: seven from published research papers, seven using the World Wide Web, and two through communication with a distributer. The probes vary in shape, dimensions, electrode positioning, and electrode configuration, with many designs prone to recording motion artifact, crosstalk, and/or inappropriate EMG signals. CONCLUSION: All commercially available intravaginal probes had deficiencies in their design such as problems with probe geometry, electrode size, location, and/or configuration. Improved intravaginal EMG probes should be developed for use in research and clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".