The photoplethysmogram (PPG) signal properties can reflect the pressure signal. Therefore, the PPG signal will be used to extract the blood pressure information using optical sensors supported by signal processing techniques. The objectives can be classified as follows:

• Designing and constructing a real-time optical sensory system to measure the PPG signal.
• Designing and constructing an instrumentation system to measure the Electrocardiogram (ECG) signal.
• Optimizing the performance of both systems (i.e. PPG and ECG) for reliable raw data measurements.
• Designing relevant protocol for data collection to perform a clinical study according to standard criteria.
• Analyzing the raw data using signal processing techniques for feature extraction, the target is to correlate the embedded features in PPG and ECG signal to blood pressure and heart diseases (ex. cardiovascular diseases and cardiac arrhythmia).
• Applying a suitable classifier to automatically detect the heart diseases.
• Building a portable prototype for monitoring blood pressure noninvasively.

Outcomes:

• Synthesizing the main embedded features in the physiological signals that directly reflect the blood pressure.
• Providing a measurement system for monitoring blood pressure noninvasively.
• Providing a machine learning system able to classify specific heat diseases using physiological signals (i.e. PTT principle).
• Applying the achieved results and developed systems in practice for clinical applications and home healthcare to monitor blood pressure and determine the cardiovascular diseases (specifically the heart diseases).
• Publishing the results of the project in related peer-reviewed respected journals