Benchmark Framework for fair evaluation of rPPG

Android Application that can estimate Heart rate, Blood pressure, Respiration rate and Oxygen rate from only the camera of the mobile

Export Mi | Xiaomi scale & Omron data to Garmin Connect

Prediction of Blood Pressure from ECG and PPG signals using regression methods.

Non-contact real-time heartbeats and respiration monitoring using Artificial Light Texture (ALT).

Cli tool to read records from omron blood-pressure bluetooth-low-energy measurement instruments

This project is cuffless cNIBP research platform with ECG(two-electrode) and PPG

Atrial Fibrillation Detection Blood Pressure Monitor (Oscillometric Method)

This is an application that uses the Flutter framework, SQFLite as a database to record blood pressure, blood sugar, BMI, or create medication reminders in multi mobile platforms You can run this project on iOS, Android

This project will focus on predicting heart disease using neural networks. Based on attributes such as blood pressure, cholestoral levels, heart rate, and other characteristic attributes, patients will be classified according to varying degrees of coronary artery disease

Portable Telemedicine Monitoring System(便携式远程医疗监控系统): The windows/winCE ECG, Blood Pressure, Pulse Oximeter displays, TCP connection between Windows and Win CE

Use health and fitness data collected from Samsung Galaxy Watch and blood pressure data from Omron to realize blood pressure prediction.

Package for imputing the arterial blood pressure (ABP) waveform from non-invasive physiological waveforms (PPG & ECG) using a deep neural network

Project on blood pressure estimation from ECG and PPG signals.

An android application used to measure vital signals such as SpO2, Heart rate, Respiratory rate and Blood Pressure.

Medinote is an offline Android app for tracking blood pressure measurements. It helps users record, visualize, and analyze their data easily.

This project is an independent approach to acquire patient data from Philips patient monitors via network interface.

Official repository of team NP Devs for Prototype 2.0 held at IIITA

Predict Arterial Blood Pressure Using ECG and PPG Data

Deep learning framework for accurate blood pressure (BP) estimation from PPG signals. Features include signal selection & enhancement, dual-path temporal/image-based feature extraction, M-SCAN attention, MSFN fusion, and D-QuEST loss with domain knowledge integration. Extensive diversity analysis ensures robustness of the work.