Photoplethysmography (PPG) is a non-invasive technique used to measure blood volume variations in tissues, presenting a huge potential for the extraction of several important physiological parameters, such as Heart Rate (HR), Respiratory Rate (RR), Blood Pressure (BP), Blood Oxygen Saturation (SpO2), Heart Rate Variability (HRV), among others. The latest developments in the field of health status monitoring based on wearable devices, present the PPG as the leading solution, characterized by increased user acceptance, with possible applications in smart environments. In this work, a practical approach was carried out regarding the estimation of HR, RR, SpO2 and HRV, based on the acquisition and analysis of the PPG signal. Furthermore, an experimental validation of the measured physiological parameters was performed. As main contributions, a new methodology is proposed for the estimation of RR, based on the analysis of the maximum peaks of the PPG signal. Another main contribution is the proposal of a dynamic model for the estimation of HRV, taking the Root Mean Square of Successive Differences (RMSSD) method, and introducing the concept of multiple timeslots with different acquisition times, thus achieving a higher accuracy. It is also important to mention the establishment of a new model for SpO2 estimation adaptable to MAX30100 PPG sensor.

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Photoplethysmography,Heart rate,Respiratory rate estimation,Blood oxygen saturation,Digital signal processing

• Computer and Information Sciences - Natural Sciences
• Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
• Medical Engineering - Engineering and Technology
• Health Sciences - Medical and Health Sciences
• Health Biotechnology - Medical and Health Sciences