A concurrent comparison of inertia sensor-based walking speed estimation methods
Bibliographic record
Abstract
This study performed a concurrent comparison of two walking speed estimation methods using shank- and foot-mounted inertial measurement units (IMUs). Based on the cyclic gait pattern of the stance leg during walking, data was segmented into a series of individual stride cycles. The angular velocity and linear accelerations of the shank and foot over each of these cycles were then integrated to determine the walking speed. The evaluation was performed on 10 healthy subjects during treadmill walking where known treadmill speeds were compared with the estimated walking speeds under normal and toe-out walking conditions. Results from the shank-mounted IMU sensor yielded more accurate walking speed estimates, with a maximum root mean square estimation error (RMSE) of 0.09 m/s in normal walking and 0.10 m/s in toe-out conditions; while the foot-mounted IMU sensors yielded a maximum RMSE of 0.14 m/s in normal walking and 0.26 m/s in toe-out conditions. Shank-mounted IMU sensors may prove to be of great benefit in accurately estimating walking speeds in patients whose gait is characterized by abnormal foot motions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".