Frequency Response of a Novel IR Based Pressure Sensitive Mat for Well-being Assessment
Bibliographic record
Abstract
The potential for pressure sensitive mats to provide a means for ambient well-being sensing and assessment when placed within beds or chairs has been widely studied although many mats have limitations in capability and cost. This paper presents the results for a novel pressure sensitive mat that combines an Infrared (IR) based emitter/detector proximity sensor device with a flexible gel material (Hexyoo Scientific Inc. Opus Gel). The performance results for a bench prototype sensor that combines layers of gel that have differing colour and structure properties with the sensors is shown. Specifically, the step response of the prototype is analyzed for step-up and step-down loads representing a pressure range typical for human body pressures. The results show that the frequency response for the two cases are both low-pass in nature and that the frequency response for the step-down response is a loss of 10dB at 6Hz while the step-up response is narrower with a 10dB loss at 2Hz. This bandwidth is sufficient to allow assessment of human motions with the sensor, while also using significantly simpler and lower cost technology compared to previously reported fibre optic mats.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".