Effects of a wireless local area network (LAN) system, a telemetry system, and electrosurgical devices on medical devices in a hospital environment.
Bibliographic record
Abstract
Concerns have been raised about interference of wireless local area network (LAN) systems and telemetry systems with medical devices in hospitals. The authors have investigated the susceptibility of 65 electromedical devices to a wireless LAN system and a telemetry system in preselected areas of a hospital. Testing was based on the American National Standards Institute Standard C63.18. The wireless LAN system operated at 2.42 GHz with an output power of 100 mW. The telemetry system operated at 466 MHz with an output power of 4 mW. Of the 65 devices tested, only two hand-held Doppler units, a Mini Doppler Model D900 (Huntleigh Healthcare Ltd) and a Ultrasonic Doppler Model 811 (Parks Medical Electronics, Inc.), were affected by the LAN system. Placed within 10 cm of the LAN system in standby mode, both units emitted periodic high-pitched beating sounds, which could be misinterpreted as normal beating sounds from the patient. These changed to random static noise during data transmission by the LAN. Under normal conditions of use, a LAN system would never be placed this close to a medical device. The quality of data transmission from the LAN system changed from "good" to "acceptable" in the colonoscopy room. This deterioration in transmission quality could have been caused by the lead shielding in the room. Electrosurgical devices operating at 0.5 to 1 MHz did not affect the LAN system at distances up to 3 m. None of the devices was affected by the telemetry system. These findings suggest that wireless LAN systems and telemetry systems can be acceptable for use in hospitals. Nevertheless, other systems should be tested on potentially susceptible devices by the hospital before use.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".