Electronic stethoscope

A stethoscope configured to mechanically capture chest sounds, said stethoscope comprising:

• a sound capture component, a sound processing component, a communications component, and an output data display component;
• wherein the sound capture component comprises:
• a bell fitted with a diaphragm configured to mechanically capture sound waves produced within an upper torso region of a human subject;
• a plurality of microphones configured to capture sound waves amplified by the diaphragm and to convert said amplified sound waves into electronic wave forms;
• a plurality of vibration transducers, wherein said microphones and vibration transducers together form a 3-dimensional array of transducers, and wherein said vibration transducers are configured to pick up vibrations generated by a human body and to convert said bodily vibrations into electronic wave forms;
• wherein the sound capture component is configured for automatic sound capturing as soon as the diaphragm and/or the bell is touching a person's chest region using either touch-based technology or signal processing software to trigger a start and stop of said sound capturing or a hybrid of both;
• wherein the sound processing component is configured to receive said electronic wave forms from the sound capture component, to analyze said electronic wave forms using digital signal processing techniques and by means of AI/ML models that have been build using standardized wave forms which have been clinically correlated to different disease states comparing these wave forms with said standardized wave forms;
• wherein the communications component is configured to transfer said electronic wave forms to a remote repository to be saved or to communicate with a remote repository containing said Al/ML models corresponding to differential diagnoses of diseases and medical conditions that produce distinctive sound waves within an upper torso region of a human subject;
• and
• wherein the data display component is configured to display a differential diagnosis based on a prediction of the sound waves against the deployed Al/ML models.