Internet of Things ‐ integrated IR‐UWB technology for healthcare applications
Why this work is in the frame
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Bibliographic record
Abstract
Summary Recent technology developments have produced small and smart biomedical sensors, which can be worn or implanted in the human body. These biosensors create closed wireless networks named Wireless Body Area Networks (WBAN). The WBAN will continuously observe the physiological state of patients for both diagnosis and prevention. Those include on‐body measurements such as the Electrocardiogram (ECG), Electroencephalogram (EEG), temperature, and blood pressure. Ultra‐Wide‐Band (UWB) is a technology that has received a lot of attention due to several unique features such as secure transmission, low noise, and low energy consumption. Given the fact that the patients' well‐being might be dependent on the accurate realization of such networks, a high level of design and implementation accuracy are maintained throughout the system. In this paper, we proposed an Impulse‐Radio Ultra‐Wideband system, which is composed of static biomedical nodes mounted on a patient's body to collect vital data and send it wirelessly to a central node or subsequent analysis by healthcare professionals. The performance of this network, such as the effect of node location, the number of transmitted symbols, multiuser interference, and intersymbol interference, is evaluated. We also study the physical layer and quality of service of this proposed architecture.
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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 | 0.000 |
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 it