Analysis of commode grab bar usage for the monitoring of older adults in the smart home environment
Bibliographic record
Abstract
The occurrence of falls inside the home is a common yet potentially hazardous issue for adults as they age. Even with the installation of physical aids such as grab bars, weight transfers on and off a toilet or bathtub can become increasingly difficult as a person's level of physical mobility and sense of balance deteriorate. Detecting this deterioration becomes an important goal in fall prevention within a smart home. This paper develops an unobtrusive method of analyzing the usage of toilet grab bars using pressure sensors embedded into the arm rests of a commode. Clinical parameters are successfully extracted automatically from a series of stand-to-sit (StSi) and sit-to-stand (SiSt) transfers performed by a trial group of young and older adults. A preliminary comparison of the parameters indicates differences between the two groups, and aligns well with published characteristics obtained using accelerometers worn on the body. The unobtrusive nature of this method provides a useful tool to be incorporated into a system of continuous monitoring of older adults within the smart home environment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".