Validation of a bluetooth-enabled load cell for objective and accessible assessment of lower extremity strength
Bibliographic record
Abstract
High magnitude loading from performing resistance-based exercise has been found to improve tendon strength and reduce symptoms of Achilles tendinopathy (AT) but is difficult to quantify without specialist equipment. Here, we assess the validity and reliability of a novel AT rehabilitation tool (the "PhysViz" system) compared to a "gold-standard" dynamometer for assessing plantarflexion maximal voluntary isometric contractions (MVIC). 41 participants aged 18-60 completed the study. A within-subject test-retest study design was used to examine and compare the validity and reliability of the two systems during plantarflexion MVICs. Test - retest reliability of the two methods were determined by calculating intra-class correlation coefficients (ICCs) and 95% confidence intervals. Method agreement was assessed with Bland - Altman Limits of Agreement (LoA) analysis. The PhysViz demonstrated excellent test-retest reliability; ICC, SEM and MDC were numerically comparable to the dynamometer (ICC 0.93 vs. 0.92; SEM 2.01 vs. 2.95 kg and MDC 5.58 vs. 8.18 kg, respectively), indicating that the novel system is valid and reliable for measuring plantarflexor MVICs. Future studies should address its utility in monitoring AT rehabilitative loading remotely over time.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".