Prototype development of an electrical impedance based simultaneous respiratory and cardiac monitoring system for gated radiotherapy
Bibliographic record
Abstract
BACKGROUND: In radiotherapy, temporary translocations of the internal organs and tumor induced by respiratory and cardiac activities can undesirably lead to significantly lower radiation dose on the targeted tumor but more harmful radiation on surrounding healthy tissues. Respiratory and cardiac gated radiotherapy offers a potential solution for the treatment of tumors located in the upper thorax. The present study focuses on the design and development of simultaneous acquisition of respiratory and cardiac signal using electrical impedance technology for use in dual gated radiotherapy. METHODS: An electronic circuitry was developed for monitoring the bio-impedance change due to respiratory and cardiac motions and extracting the cardiogenic ECG signal. The system was analyzed in terms of reliability of signal acquisition, time delay, and functionality in a high energy radiation environment. The resulting signal of the system developed was also compared with the output of the commercially available Real-time Position Management™ (RPM) system in both time and frequency domains. RESULTS: The results demonstrate that the bioimpedance-based method can potentially provide reliable tracking of respiratory and cardiac motion in humans, alternative to currently available methods. When compared with the RPM system, the impedance-based system developed in the present study shows similar output pattern but different sensitivities in monitoring different respiratory rates. The tracking of cardiac motion was more susceptible to interference from other sources than respiratory motion but also provided synchronous output compared with the ECG signal extracted. The proposed hardware-based implementation was observed to have a worst-case time delay of approximately 33 ms for respiratory monitoring and 45 ms for cardiac monitoring. No significant effect on the functionality of the system was observed when it was tested in a radiation environment with the electrode lead wires directly exposed to high-energy X-Rays. CONCLUSION: The developed system capable of rendering quality signals for tracking both respiratory and cardiac motions can potentially provide a solution for simultaneous dual-gated radiotherapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".