Heart Waves: A Heart Rate Feedback System Using Water Sounds
Bibliographic record
Abstract
Wearable devices of today help people track and monitor their biometric data such as heart rate. While the tracked data can help inform people of their health, many find that it adds unnecessary anxieties in the way the feedback is provided. In the case of college students, they spend most of their time in a stressful environment, leading them to an increase in the risk of mental health issues. To help with this issue, we present Heart Waves, an experimental ambient feedback system that tracks heart rate and uses water sound to provide feedback in a stressful work environment. Heart Waves uses the sound of falling water to create a relaxing atmosphere to help ease any stress they are going through. As the user's heart rate goes up, the flow of water increases, and as their heart rate goes down, the flow rate of water decreases. The purpose of this project is to automatize the processing of heart rate data so that the user does not have to analyze the data and create an ambient feedback system that adjusts to their heart rate.
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) | 0.000 | 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 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".