Comparison of Mechanical Force of Manually Assisted Chiropractic Adjusting Instruments
Bibliographic record
Abstract
OBJECTIVE: To quantify the force-time and force-delivery characteristics of six commonly used handheld chiropractic adjusting devices. METHODS: Four spring-loaded instruments, the Activator Adjusting Instrument; Activator II Adjusting Instrument, Activator III Adjusting Instrument, and Activator IV Adjusting Instrument, and two electromechanical devices, the Harrison Handheld Adjusting Instrument and Neuromechanical Impulse Adjusting Instrument, were applied to a dynamic load cell. A total of 10 force-time histories were obtained at each of three force excursion settings (minimum to maximum) for each of the six adjusting instruments at preload of approximately 20 N. RESULTS: The minimum-to-maximum force excursion settings for the spring-loaded mechanical adjusting instruments produced similar minimum-to-maximum peak forces that were not appreciably different for most excursion settings. The electromechanical adjusting instruments produced short duration ( approximately 2-4 ms), with more linear minimum-to-maximum peak forces. The force-time profile of the electromechanical devices resulted in a more uniform and greater energy dynamic frequency response in comparison to the spring-loaded mechanical adjusting instruments. CONCLUSIONS: The handheld, electromechanical instruments produced substantially larger peak forces and ranges of forces in comparison to the handheld, spring-loaded mechanical devices. The electromechanical instruments produced greater dynamic frequency area ratios than their mechanical counterparts. Knowledge of the force-time history and force-frequency response characteristics of spinal manipulative instruments may provide basic benchmarks and may assist in understanding mechanical responses in the clinical setting.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".