Sakib1263/NABNet
NABNet: A Nested Attention-guided BiConvLSTM Network for a robust prediction of Blood Pressure components from reconstructed Arterial Blood Pressure waveforms using PPG and ECG Signals
This project helps medical researchers and device developers accurately reconstruct Arterial Blood Pressure (ABP) waveforms. By taking Photoplethysmogram (PPG) and Electrocardiogram (ECG) signals as input, it produces a detailed, estimated ABP waveform. This is particularly useful for those working on non-invasive blood pressure monitoring technologies or cardiovascular research.
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Use this if you need to precisely estimate full arterial blood pressure waveforms from PPG and ECG data for research or device development.
Not ideal if you only need a single blood pressure value (systolic/diastolic) rather than the full waveform, or if you don't have PPG and ECG signal inputs.
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45
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Language
Jupyter Notebook
License
MIT
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Last pushed
Mar 14, 2023
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