Kalman Smoothing and Wavelet Analysis for Inertial Data of Human Movement Disorder Motion
Bibliographic record
Abstract
Human movement disorders examined include essential tremor and Parkinson’s disease; both disorders feature possible uncontrollable tremor. In most literature, limited numbers of inertial sensors (accelerometers and gyroscopes) are used when examining movement disorder subjects for purposes of diagnosis and attenuation (active mitigation) and consequently a full rendering of motion (and tremor) for subjects is not possible. The examination carried out for this work utilizes six inertial sensors capable of rendering all six degrees-of-freedom of motion with the assistance of Kalman smoothing. Because of this full rendering of motion, movement patterns largely unexamined by other researchers are visible. Key findings are that the measured frequency content of motion (displayed using wavelets) is largely unaffected by the axis of measurement or by whether lateral or rotational motion is being measured, as well, accelerometers are largely unaffected by rotational tremor even though some measured frequency content would be expected due to gravity’s influence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".