Blood Coagulation Time Measurement Using a 1μL of Whole Blood on a TE Mode BAW Resonator
Bibliographic record
Abstract
This paper presents a possible way to blood coagulation time measurement using a TE (Thickness Extensions) mode BAW (Bulk Acoustic Wave) resonator which requires as low as 1 micro-liter of whole blood. The blood sample is placed on the top surface of a glass plate where a compressional ultrasonic transducer is fabricated on the bottom surface. The transducer is made of 8 μm thick zinc oxide (ZnO) thin film that has a thickness resonance frequency around 400 MHz. The transducer generates compressional (longitudinal) acoustic wave inside the piezoelectric thin film and glass substrate. The acoustic waves are mostly reflected and trapped inside the device from both sides of it; 1) the glass/liquid (blood) interface, and 2) the transducer/air interface. Most of the acoustic waves are reflected from the second interface because of the higher impedance mismatch, while the reflections from the first boundary are related to impedance (mechanical properties) of the liquid sample or blood. The acoustic impedance of blood changes due to the coagulation process. This affects the reflection coefficient and amplitude of the reflected waves from the blood/glass interface. Thus, the overall acoustic energy trapped inside the bulk film changes over the time which consequently affects the resonator parameters. The blood coagulation time was determined by monitoring the amplitude of the reflected sinusoidal acoustic waves at 400 MHz in the previous work using the same device. However, in this paper we demonstrate the resonance frequency shifts obtained by numerical modeling and practical measurements for a few liquid samples with different mechanical properties. The proposed method has a potential to be used in a low-cost portable coagulation time measurement cartridge which requires only 1μL of whole blood without centrifuging. A simple resonator can be implemented for tracking the resonating frequency to further reduce the size and cost of the device, to make it more suitable for patient self-testing applications.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".