A Feasibility Study to Assess Vibration and Sound From Zygapophyseal Joints During Motion Before and After Spinal Manipulation
Bibliographic record
Abstract
OBJECTIVE: This feasibility study used novel accelerometry (vibration) and microphone (sound) methods to assess crepitus originating from the lumbar spine before and after side-posture spinal manipulative therapy (SMT). METHODS: This study included 5 healthy and 5 low back pain (LBP) participants. Nine accelerometers and 1 specialized directional microphone were applied to the lumbar region, allowing assessment of crepitus. Each participant underwent full lumbar ranges of motion (ROM), bilateral lumbar SMT, and repeated full ROM. After full ROMs the participants received side-posture lumbar SMT on both sides by a licensed doctor of chiropractic. Accelerometer and microphone recordings were made during all pre- and post-SMT ROMs. Primary outcome was a descriptive report of crepitus prevalence (average number of crepitus events/participant). Participants were also divided into 3 age groups for comparisons (18-25, 26-45, and 46-65 years). RESULTS: Overall, crepitus prevalence decreased pre-post SMT (average pre = 1.4 crepitus/participant vs post = 0.9). Prevalence progressively increased from the youngest to oldest age groups (pre-SMT = 0.0, 1.67, and 2.0, respectively; and post-SMT = 0.5, 0.83, and 1.5). Prevalence was higher in LBP participants compared with healthy (pre-SMT-LBP = 2.0, vs pre-SMT-healthy = 0.8; post-SMT-LBP = 1.0 vs post-SMT-healthy = 0.8), even though healthy participants were older than LBP participants (40.8 years vs 27.8 years); accounting for age: pre-SMT-LBP = 2.0 vs pre-SMT-healthy = 0.0; post-SMT-LBP = 1.0 vs post-SMT-healthy = 0.3. CONCLUSIONS: Our findings indicated that a larger study is feasible. Other findings included that crepitus prevalence increased with age, was higher in participants with LBP than in healthy participants, and overall decreased after SMT. This study indicated that crepitus assessment using accelerometers has the potential of being an outcome measure or biomarker for assessing spinal joint (facet/zygapophyseal joint) function during movement and the effects of LBP treatments (eg, SMT) on zygapophyseal joint function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".