Enabling the ActiGraph GT9X Link’s Idle Sleep Mode and Inertial Measurement Unit Settings Directly Impacts Data Acquisition
Bibliographic record
Abstract
The ActiGraph GT9X has been implemented in clinical trials to track physical activity and sleep. Given recent incidental findings from our laboratory, the overall aim of this study was to notify academic and clinical researchers of the idle sleep mode (ISM) and inertial measurement unit (IMU)’s interaction, as well as their subsequent effect on data acquisition. Investigations were undertaken using a hexapod robot to test the X, Y and Z sensing axes of the accelerometers. Seven GT9X were tested at frequencies ranging from 0.5 to 2 Hz. Testing was performed for three sets of setting parameters: Setting Parameter 1 (ISMONIMUON), Setting Parameter 2 (ISMOFFIMUON), Setting Parameter 3 (ISMONIMUOFF). The minimum, maximum and range of outputs were compared between the settings and frequencies. Findings indicated that Setting Parameters 1 and 2 were not significantly different, but both were significantly different from Setting Parameter 3. Upon inspection, it was discovered that the ISM was only active during Setting Parameter 3 testing, despite it being enabled in Setting Parameter 1. Researchers should be aware of this when conducting future research using the GT9X.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".