MétaCan
Menu
Back to cohort

Using continuous relative phase and modified vector coding analyses to quantify spinal coordination and coordinative variability for healthy and chronic low back pain patients: An exploratory comparative analysis

2024· article· en· W4399933474 on OpenAlexafffund
Patrick Ippersiel, Dennis J. Larson, Shawn M. Robbins

Bibliographic record

VenueJournal of Biomechanics · 2024
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsMcGill University Health CentreUniversity of WaterlooMcGill UniversityUniversité de MontréalCentre de réadaptation Lethbridge-Layton-MackayCentre for Interdisciplinary Research in Rehabilitation
FundersInstitut TransMedTechFonds de Recherche du Québec - SantéCanada First Research Excellence Fund
KeywordsLow back painLumbarRelative phaseKinematicsCoding (social sciences)Physical medicine and rehabilitationPhysical therapyMathematicsMedicinePhase (matter)StatisticsChemistryPhysicsAnatomy

Abstract

fetched live from OpenAlex

Differences in coordination and coordinative variability are common in people with low back pain. While differences may relate to the different analyses used to quantify these metrics, the preferred approach remains unclear. We aimed to compare coordination and coordinative variability, in people with and without low back pain performing a lifting/lowering task, using continuous relative phase and vector coding procedures, and to identify which technique better detects group differences. Upper lumbar (T12-L3), lower lumbar (L3-S1), and hip angular kinematics were measured using electromagnetic motion capture during 10 crate lifting/lowering repetitions from adults with (n = 47) and without (n = 17) low back pain. Coordination and coordinative variability for the Hip-Lower Lumbar and Lower Lumbar-Upper Lumbar joint pairs were quantified using mean absolute relative phase and deviation phase (continuous relative phase), and coupling angle and coupling angle variability (vector coding), respectively. T-tests examined group differences in coordination and variability. Cohen's d bootstrapping analyses identified the more sensitive technique for detecting group differences. Less in-phase and more variable behavior was observed in the low back pain group, mostly independent of joint pair and analytical technique (P < 0.05, Cohen's d range = 0.61 to 1.33). Qualitatively, the low back group limited motion at the lower lumbar spine during lifting/lowering. Continuous relative phase was more sensitive in detecting group differences in coordinative variability, while vector coding was more sensitive towards differences in coordination. These procedures convey distinct information and have their respective merits. Researchers should consider the choice of analytical techniques based on their study objectives.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.097
GPT teacher head0.429
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of BiomechanicsSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207