Hallway Gait Monitoring Using Novel Radar Signal Processing and Unsupervised Learning
Why this work is in the frame
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Bibliographic record
Abstract
We propose a novel corridor or hallway gait monitoring system based on radar signal processing, unsupervised learning, and a subject detection, association and tracking method. This paper proposes an algorithm that could be paired with any type of MIMO FMCW radar to capture human gait in a highly cluttered environment without needing radar antenna alteration. We validate algorithm functionality by capturing spatiotemporal gait values (e.g., speed, step points, step time, step length, and step count) of people walking in a long hallway. We show that our proposed algorithm yields an average absolute error for speed estimation between 0.0040 m/s to 0.0435 m/s. These preliminary results demonstrate the promising potential of our algorithm to accurately monitor gait in hallways, which increases opportunities for its applications in institutional and home environments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it