A Preliminary Study of Noise Effect on Pulse Rate, Blood Pressure and EEG Signal
Bibliographic record
Abstract
This paper presents the effect of noise to pulse rate, blood pressure and Encephalography (EEG) signal. The investigation aims to find the correlation between noise exposures to pulse rate (PR), blood pressure (BP) and EEG signal. A total of 20 subjects (all male) with age range of 20-22 years old and no past medical history were studied. Subjects were exposed to noise at 90 dB for ten minutes. Noise at 90dB was generated by using INTERM M500 Power Amplifier (INTERM M500, Cunnings, UK). Pulse rate, blood pressure and EEG signal were recorded before and after noise exposure. UT 4000A Patient Monitor (UT 400A; Progetti, Italy) was used to record pulse rate and blood pressure during the experiment. EEG signals were captured by using PowerLab 4/25T Data Acquisition Systems (ML865; ADInstruments, Canada). This system is capable to classify the EEG signal into Alpha (8-12 Hz) and Beta (13-30 Hz). Statistical analysis was conducted by using SPSS Version 16 (SPSS Inc; Chicago, USA) to find the correlation between noise to pulse rate, blood pressure and Power Spectral Density (PSD) value for Alpha and Beta waves. The result shows that pulse rate and blood pressure increase after noise exposure. Besides that, the finding showed that there are significant positive difference (p<0.05) between the mean value of alpha's and beta's PSD before and after noise exposure.
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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 | 0.001 | 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 | 0.000 |
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".