This study generates robust clinical data to train ML/AI algorithms of the Sponsor's imPulse™ Una full-spectrum e-stethoscope for digital diagnostic feature synthesis of symptomatic SARS-CoV-2/COVID-19 biosignatures for rapid and accurate mass screening.

This study is designed to evaluate the ability of the imPulse™ Una e-stethoscope to differentiate vibroacoustic signals in inpatients with and without confirmed COVID-19 as the first step to establish the performance characteristics - sensitivity, specificity, positive and negative predictive value - of the imPulse™ Una device for early and rapid, point-of-care diagnosis of COVID-19. This will inform the utility and design of further larger-scale studies using the device.

Inclusion Criteria

• Individuals hospitalized within a Johns Hopkins-affiliated hospital
• Able to understand and willingness to comply with study procedures
• Cases - inpatients with positive COVID-19 PCR test, collected from a respiratory sample within the last 7 days, AND pulmonary symptoms within 72 hours of enrollment
• Controls - inpatients without COVID-19 diagnosis and no pulmonary diagnosis or symptoms
• Cases or Control not able to sit or stand will be allowed to participate in just the parts of the staircase exam they're capable of doing.

Exclusion Criteria

• Assisted ventilation, including high flow nasal cannula, or ventilator support
• Unable to comply with study procedures, defined at investigator's discretion
• Participants with any visible skin infections or open wounds in areas where the imPulse™ Una device would be applied

Adult men and women will be recruited from among hospitalized patients with symptomatic COVID-19 infection who are not receiving ventilator support. One hospitalized control without lung disease or pulmonary symptoms will be selected for each case.