REMOTE PATIENT MONITORING FOR VADs AND OTHER IMPLANTABLE DEVICES
Bibliographic record
Abstract
Purpose: Ventricular assist devices (VADs) and other implantable medical devices are increasingly being utilized outside the hospital setting, allowing patients greater mobility, autonomy, and improved quality of life. To allow remote monitoring and control of these devices, without the need to bring the patient to the hospital or clinic, a Remote Biotelemetry System was developed. Methods: The developed Remote Biotelemetry System uses an infrared simultaneous bi-directional communication link between the implanted devjce and a Remote Monitor worn by the patient (similar to a pager). Data is transferred across intact skin and tissue and without the need for percutaneous wires or cables. The Remote Monitor communicates with a Clinical User Interface (CUI) which allows the physician wireless monitoring and control capabilities. The CUI also allows distance transmission using telephone lines or other public communication systems (Internet, satellite, etc.). Results: The Remote Biotelemetry System was successfully demonstrated in September 1999, during a Canadian Government Trade Mission to Japan (Osaka & Tokyo). The system allowed personnel located in Japan to remotely monitor and control the operating parameters (beat rate, operating mode, etc.) of a totally implantable ventricular assist device (VAD) located on a simulated patient in Ottawa, Canada. Utilizing the CUI in Japan, the VAD in Canada was monitored, operating parameters were modified, and confirmation that modifications were implemented were received in real time. Patient data stored within the device was also able to be transferred from Canada to Japan. By utilizing the developed technologies it is possible to provide patient access to healthcare professionals, without having the patient physically visit the hospital. This capability could play an important role in reducing costs and improving healthcare.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".