Mobile Jump Assessment (mJump): A Descriptive and Inferential Study
Bibliographic record
Abstract
BACKGROUND: Vertical jump tests are used in athletics and rehabilitation to measure physical performance in people of different age ranges and fitness. Jumping ability can be analyzed through different variables, and the most commonly used are fly time and jump height. They can be obtained by a variety of measuring devices, but most are limited to laboratory use only. The current generation of smartphones contains inertial sensors that are able to record kinematic variables for human motion analysis, since they are tools for easy access and portability for clinical use. OBJECTIVE: The aim of this study was to describe and analyze the kinematics characteristics using the inertial sensor incorporated in the iPhone 4S, the lower limbs strength through a manual dynamometer, and the jump variables obtained with a contact mat in the squat jump and countermovement jump tests (fly time and jump height) from a cohort of healthy people. METHODS: A cross sectional study was conducted on a population of healthy young adults. Twenty-seven participants performed three trials (n=81 jumps) of squat jump and countermovement jump tests. Acceleration variables were measured through a smartphone's inertial sensor. Additionally, jump variables from a contact mat and lower limbs dynamometry were collected. RESULTS: In the present study, the kinematic variables derived from acceleration through the inertial sensor of a smartphone iPhone 4S, dynamometry of lower limbs with a handheld dynamometer, and the height and flight time with a contact mat have been described in vertical jump tests from a cohort of young healthy subjects. The development of the execution has been described, examined and identified in a squat jump test and countermovement jump test under acceleration variables that were obtained with the smartphone. CONCLUSIONS: The built-in iPhone 4S inertial sensor is able to measure acceleration variables while performing vertical jump tests for the squat jump and countermovement jump in healthy young adults. The acceleration kinematics variables derived from the smartphone's inertial sensor are higher in the countermovement jump test than the squat jump test.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".