All cardiac patients undergoing an elective cardiac ultrasound as an outpatient at UCLA may be asked to participate in the study. The investigators will identify eligible patients from their medical record. If interested, patients will be consented prior to their scheduled ultrasound.

All patients hospitalized in the cardiac ICU at UCLA with a pulmonary arterial catheterization scheduled or completed may be asked to participate in the study. The investigators will identify eligible patients from their medical record. If interested, patients will be consented during their hospital stay.

The Biostrap Wristband device is a non-invasive optical sensor that monitors changes in arterial pulse volume using Photoplethysmography (PPG). PPG is frequently used in wearable sensors to detect heart rate as well as other metrics such as heart rate variability (HRV) and respiratory rate. The raw biosignals recorded by the wristband device will be further processed to estimate the ejection fraction and cardiac output.

Patients scheduled to undergo a cardiac ultrasound will wear the Biostrap wristband for the duration of the echocardiogram (1-2 hours) and a PPG waveform will be obtained from the device. The ejection fraction (measured in units of %) will also be obtained from the echocardiogram report. Then, the Artificial Intelligence (AI) staff member will do a predictive model to try and estimate the EF based on the PPG waveform. PPG-derived outcome measures will be derived from a two-step process of raw data collection followed by application of waveform derivative algorithms. They will perform an in-depth beat shape analysis of the PPG waveform that includes identifying dozens of features and critical points of each beat to derive the Ejection fraction (calculated in units of %).

Patients scheduled to undergo a pulmonary arterial catheterization in the cardiac ICU will wear the biostrap wristband for 7 days and a PPG waveform will be obtained from the device. The cardiac output values (measured in units of mL and recorded using the PA catheter) will also be obtained from the patient's medical record. Then, the Artificial Intelligence (AI) staff member will do a predictive model to try and estimate the CO based on the PPG waveform. PPG-derived outcome measures will be derived from a two-step process of raw data collection followed by application of waveform derivative algorithms. They will perform an in-depth beat shape analysis of the PPG waveform that includes identifying dozens of features and critical points of each beat to derive the Cardiac Output (calculated in unites of mL).