MobiVitalsConnect: A Comprehensive Mobile Healthcare System for Real-Time Patient Monitoring and Data Visualization
Bibliographic record
Abstract
Abstract This paper introduces MobiVitalsConnect, a novel platform-agnostic mobile healthcare system designed for both bedside and remote monitoring of patients. Central to our system is its integration with the Vitaliti ™ wearable, equipped with biosensors for real-time monitoring of vital signs such as heart rate, blood pressure, respiratory rate, body temperature, and oxygen saturation, along with physiological signals including ECG, PPG, Respiratory waveforms, and accelerometer data. MobiVitalsConnect provides advanced visualizations, including real-time data and 15-min trend lines, facilitating rapid clinical decision-making. The system employs colour coding to enhance data interpretation and supports seamless data transfer to a backend server, making it a robust solution for personalized healthcare management and improved patient outcomes. MobiVitalsConnect distinguishes itself by providing advanced visualizations with medical data, facilitating rapid clinical decision-making through access to vital signs and trends with intuitive graphs and real-time physiological signals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.039 | 0.019 |
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".