Analysis and Synthesis of Electrocardiogram (ECG) using Fourier and Wavelet Transform
Bibliographic record
Abstract
Electrocardiogram (ECG) is the study of the electrical signals of the human heart that are generated by the pumping action of the heart caused by the polarization and depolarization of the nodes of the heart. These signals must be interpreted with great accuracy and efficiency as they are paramount in prognosis and subsequent diagnosis of the condition of the patient. The goal of this project is to analyze the ECG signals following Fourier and Wavelet transforms, and to highlight and demonstrate the advantages of the Wavelet transform. Firstly, it involves simulating the temporal digital ECG signal and explaining the signal constituents, i.e., P, Q, R, S, T waves while staying in the time domain. Secondly, the ECG signal will be transferred into the frequency domain for quick, fast, and compressed analysis and carry out signal processing using Fourier analysis and highlight the pros and cons of this technique. Thirdly, wavelet analysis will be explored and demonstrated to mitigate the shortcoming of the former tool, i.e., Fourier. At this stage, various ECG signals, mimicking abnormalities, will be analyzed. This work will highlight the effectiveness of wavelet analysis as a tool to examine ECG signals. This work, hence, will entail, comparison of both transformation methods by utilizing the computational power of MATLAB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".