Capacitive monitoring system for real‐time respiratory motion monitoring during radiation therapy
Bibliographic record
Abstract
This work introduces a novel capacitive-sensing technology capable of detecting respiratory motion with high temporal frequency (200 Hz). The system does not require contact with the patient and has the capacity to sense motion through clothing or plastic immobilization devices. ABSTRACT: PURPOSE: This work presents and evaluates a novel capacitive monitoring system (CMS) technology for continuous detection of respiratory motion during radiation therapy. This modular system provides real-time motion monitoring without any contact with the patient, ionizing radiation, or surrogates such as reflective markers on the skin. MATERIALS AND METHODS: The novel prototype features an array of capacitive detectors that are sensitive to the position of the body and capable of high temporal frequency readout. Performance of this system was investigated in comparison to the RPM infrared (IR) monitoring system (Varian Medical Systems). The prototype included three (5 cm × 10 cm) capacitive copper sensors in one plane, located at a distance of 8-10 cm from the volunteer. Capacitive measurements were acquired for central and lateral-to-central locations during chest free-breathing and abdominal breathing. The RPM IR data were acquired with the reflector block at corresponding positions simultaneously. The system was also tested during deep inspiration and expiration breath-hold maneuvers. RESULTS: Capacitive monitoring system data demonstrate close agreement with the RPM status quo at all locations examined. Cross-correlation analysis on RPM and CMS data showed an average absolute lag of 0.07 s (range: 0.03-0.23 s) for DIBH and DEBH data and 0.15 s (range: 0-0.43 s) for free-breathing. Amplitude difference between the normalized CMS and RPM signal during chest and abdominal breathing was within 0.15 for 94.3% of the data points after synchronization. CMS performance was not affected when the subject was clothed. CONCLUSION: This novel technology permits sensing of both free-breathing and breath-hold respiratory motion. It provides data comparable to the RPM system but without the need for an IR tracking camera in the treatment room or use of reflective markers on the patient.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".