The purpose of this observational trial is to advance digital health monitoring through the analysis of Photoplethysmography (PPG) waveforms collected via RE.DOCTOR Vitals software. The study aims to collect a diverse and extensive dataset of PPG waveforms, alongside traditional physiological measurements, for the purpose of enhancing existing algorithms and machine learning models used in health monitoring. The primary focus is on improving the accuracy and reliability of algorithms in interpreting PPG data to derive meaningful insights into physiological parameters. The main questions it aims to answer are: * How can extensive datasets of PPG waveforms be utilized to enhance existing algorithms and machine learning models? * How do correlations between PPG waveforms and key physiological parameters (such as glucose levels, blood pressure, heart rate, respiration rate) contribute to refining algorithms for more accurate and reliable health predictions? Participants will be asked to: * Continuously monitor their health using smartphone applications. * Allow the collection of PPG waveforms in diverse settings. * Engage in tasks related to monitor health parameters using medically approved devices