Efficient wireless communication in healthcare systems; design and performance evaluation
Bibliographic record
Abstract
Increasing number of ageing population and people who need continuous health monitoring and rising the costs of health care have triggered the concept of the novel wireless technology-driven human body monitoring. Human body monitoring can be performed using a network of small and intelligent wireless medical sensors which may be attached to the body surface or implanted into the tissues. It enables carers to predict, diagnose, and react to adverse events earlier than ever. The concept of Wireless Body Area Network (WBAN) was introduced to fully exploit the benefits of wireless technologies in telemedicine and m-health. The main focus of this research is the design and performance evaluation of strategies and architectures that would allow seamless and efficient interconnection of patient’s body area network and the stationary (e.g., hospital room or ward) wireless networks. I first introduce the architecture of a healthcare system which bridges WBANs and Wireless Local Area Networks (WLANs). I adopt IEEE 802.15.6 standard for the patient’s body network because it is specifically designed for WBANs. Since IEEE 802.15.6 has strict Quality of Service (QoS) and priorities to transfer the medical data to the medical server a QoS-enabled WLAN for the next hop is needed to preserve the end-to-end QoS. IEEE 802.11e standard is selected for the WLAN in the hospital room or ward because it provides prioritization for the stations in the network. I investigate in detail the requirements posed by different healthcare parameters and to analyze the performance of various alternative interconnection strategies, using the rigorous mathematical apparatus of Queuing Theory and Probabilistic Analysis; these results are independently validated through discrete event simulation models. This thesis has three main parts; performance evaluation and MAC parameters settings of IEEE 802.11e Enhanced Distributed Channel Access (EDCA), performance evaluation and tuning the MAC parameters of IEEE 802.15.6, and designing a seamless and efficient interconnection strategy which bridges IEEE 802.11e EDCA and IEEE 802.15.6 standards for a healthcare system.
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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 | 0.003 | 0.007 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".