Acoustical patient monitoring using a sound classifier and a microphone

When monitoring a patient, acoustic events (e.g., coughs, snores, impact sounds, verbalizations, etc.) relevant to the patient's status are detected by a microphone array (12) and timestamped. Detected event signals generated by the microphone array (12) are filtered to identify signatures such as zero crossings, corner frequencies, amplitude, pitch, etc., for classification purposes. The filtered signals are digitized and classified into one of a plurality of acoustic event classes (e.g., snore, cough, wheeze, breath, etc.) and/or subclasses. The classified events are displayed to a user (e.g., graphically, textually, etc.) with their timestamps to indicate chronology. A user can review the acoustic events, select one or more events, and listen to a recording of the selected event (s). Additionally, specified acoustic events can trigger an alarm to alert a nurse or the like that the patient requires immediate attention