Development of a Smart Seat Cushion for Heart Rate Monitoring Using Ballistocardiography
Bibliographic record
Abstract
For many individuals with cardiac conditions, long term monitoring of heart vitals is an essential part of ongoing care. Current monitoring technologies, such as wearables and medical devices, though accurate, are obtrusive, require the person to remember to use them, and need to be used correctly. Wearable monitors are, therefore, not ideal for everyone. This research developed a prototype portable seat cushion that can capture heart rate using a cardiovascular signal called the ballistocardiogram (BCG) by a person simply sitting on the cushion. The cushion uses load cells embedded inside it as well as analog and digital signal conditioning to obtain BCG, which is then processed to calculate heart rate. Results from nine participants sitting still show that the cushion is able to obtain an average accuracy of 95.1%, which is as good as or better than other similar methods reported in the literature. To the authors' knowledge, this work represents the first portable ambient device for measuring heart rate from a seated position. The smart seat cushion can easily be integrated into an Ambient Assisted Living (AAL) system and offers a zero-effort and unobtrusive alternative to wearable monitoring devices.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".