Impact of Skin–Electrode Interface on Electrocardiogram Measurements Using Conductive Textile Electrodes
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Bibliographic record
Abstract
Physicians' understanding of biosignals as measured with medical instruments becomes the foundation of their decisions and diagnoses of patients, as they rely strongly on what the instruments show. Thus, it is critical and very important to ensure that the instruments' recordings exactly reflect what is happening in the patient's body so that the acquired signal is the real one or at least as close to the real in-body signal as possible. This is such an important issue that sometimes physicians use invasive measurements to obtain the real biosignal. Generating an in-body signal from what a measurement device shows is called “signal purification” or “reconstruction” and can be done only when we have adequate information about the interface between the body and the monitoring device. In this paper, first, we present a device that we developed for electrocardiogram (ECG) acquisition and transfer to PC. To evaluate the performance of the device, we use it to measure ECG and apply conductive textile as our ECG electrode. Then, we evaluate ECG signals captured by different electrodes, specifically traditional gel Ag/AgCl and dry golden plate electrodes, and compare the results, allowing us to investigate if ECG measured with the device is proper for applications where no skin preparation is allowed, such as ECG-assisted blood pressure monitoring devices. Next, we propose a method to reconstruct the ECG signal from the signal acquired by our device, with respect to the interface characteristics and their relation to the ECG. The interface in this paper is skin-electrode interface for conductive textiles. In the last stage of this paper, we explore the effects of pressure on skin-electrode interface impedance and its parametrical variation.
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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 it