Heart Rate Analysis and Telemedicine: New concepts & Maths
Bibliographic record
Abstract
Our paper deals with some new aspects of ambulatory (Holter) ECG monitoring extending its indications and using for risk management purpose. Remote sensing consists of the transmittal of patient information, such as ECG, X-rays, or patient records, from a remote site to a collaborator in a distant site. Our earlier developed internet based ECG system was unique for on/off-line analysis of long-term ECG registrations. After the 5-year experience in a smaller region of Budapest, Hungary involving a municipal hospital and the surrounding outpatient cardiology departments and general practitioners, we decided to integrate into our new ECG equipment, the CardioClient the results. In the first clinical study of the four was a wavelet, non-linear heart rate analysis in sudden cardiac death patients using the Internet and the GPRS mobile communication. After the wavelet transformation by the Haar wavelet and the Daubechies 10-tap wavelet, the phase-space of the wavelet-coefficient standard deviation and the scale parameters showed an excellent separation in the scale-range of 3-6 between the two groups: in that region, the average scaling exponents was 0.14plusmn0.04 for Group-A, and 1.22plusmn0.27 for Group-B (p<0.001). In the next study, we used the Internet database of long-term ambulatory, mobile, GPRS electrocardiograms for the for risk stratification of patients through the cardiovascular continuum. From our ambulatory mobile GPRS ECG database the following a priori groups were defined after a 24 months follow-up: G1: N=227 patients (without manifest cardiovascular disease, clusterized "boxes" based on the age, sex, cholesterol level, diabetes, hypertension ); G2: N=89 patients (postinfarction group); G3: N=66 (patients with chronic heart failure) with (+) or without (-): all-cause death (acD), myocardial infarction (MI), malignant ventricular arrhythmia (MVA), sudden cardiac death (SCD). The actual vs. predicted values were analyzed with chi-square test. The best significance levels (p<0.001) were found with method in G1/MI+, G2/SCD+, G3/acD+, G3/SCD+ groups. In the third study a wavelet analysis of late potentials based on long-term, high-resolution, mobile, GPRS ECG data was performed. These pathological changes were also detected by the Haar and Daubechies_4 wavelets, but in a narrower space (110-128 ms and 180-240) and with lesser significance (p<0.01). Late potentials were found in Group-A (N=21) in 18 cases with Morlet, 16 with Haar, 19 with Daub-4 analysis, and in 15 cases using all the 3 waves; for Group-B the data were 5, 9, 8, 5, respectively. In the fourth clinical study the prognostic value of the nonlinear dynamicity measurement of atrial fibrillation waves detected by GPRS Internet long-term ECG monitoring were analyzed. The multivariate discriminant model selects the best parameters stepwise, the entry or removal based on the minimalization of the Wilks' lambda. Three variables remained finally: x1 = CI mean-value at log r=-1.0 (m9-14), x2 = CI mean-value at log r=-0.5 (m12-17), and x3 = CD_cg. The Wilks' lambda was 0.011, chi-square 299.68, significancy: p<0.001.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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".