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Spine-Straight Device for the Treatment of Kyphosis

2002· article· en· W195149440 on OpenAlexaff
E. Lou, Jim Raso, Doug Hill, N.G. Durdle, Marc Moreau

Bibliographic record

VenueStudies in health technology and informatics · 2002
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsCapital District Health Authority
Fundersnot available
KeywordsAccelerometerBraceMedicineKyphosisPhysical therapyCalipersPhysical medicine and rehabilitationOrthodonticsComputer scienceSurgeryMathematicsRadiographyEngineering

Abstract

fetched live from OpenAlex

Kyphosis is an excessive rounding of the upper spine. Its treatment depends upon the severity, the age of the patient and the levels of the spine that are affected. Early diagnosis is a key to providing optimal treatment. In a skeletally immature patient, an exercise program or bracing is the most commonly used treatment. However, the compliance of bracing for adolescents is poor and exercise training is labor intensive. The purpose of this study is to determine whether a Spine-Straight device can help patients to correct their kyphosis themselves and there by reduce back pain without the biomechanical support of a brace. The Spine-Straight device consists of an accelerometer and a microcomputer unit. The accelerometer is used to measure the kyphotic angle and the microcomputer unit controls a pager vibrator to alert patients when their posture exceeds personalized thresholds. The system was tested in the laboratory before used by subjects. The results were compared to back data obtained from a laser scanner imaging system. The maximum angle deviation between the laser scanner and the Spine-Straight device was 1.5 degrees. Two volunteers tested the systems for 2 days. The accelerometer was placed at the T3 location and the microcomputer unit was carried during daily activities. The angle measurement was recorded at 1 minute intervals during daily activity over a period of 2 days. The preliminary trials demonstrate subjects can improve their posture when feedback signals were provided.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

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

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 head0.135
GPT teacher head0.410
Teacher spread0.275 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations13
Published2002
Admission routes1
Has abstractyes

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