Using an In-Ear Microphone Within an Earphone as a Fitness and Health Tracker

Trained machine learning models can be used for analysis of signals obtained through an in-ear or on-body device. Signals can be analyzed to determine information related to activities such as eating, chewing, drinking, coughing, or sneezing. In addition, data from an in-ear thermometer or other dat...

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Bibliographische Detailangaben
Hauptverfasser:	Oztaskent, Ant, Volovich, Yaroslav
Format:	Patent
Sprache:	eng
Schlagworte:	ACOUSTICS DEAF-AID SETS DIAGNOSIS ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKEACOUSTIC ELECTROMECHANICAL TRANSDUCERS MEDICAL OR VETERINARY SCIENCE MUSICAL INSTRUMENTS PHYSICS PUBLIC ADDRESS SYSTEMS SPEECH ANALYSIS OR SYNTHESIS SPEECH OR AUDIO CODING OR DECODING SPEECH OR VOICE PROCESSING SPEECH RECOGNITION SURGERY
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Beschreibung
Zusammenfassung:	Trained machine learning models can be used for analysis of signals obtained through an in-ear or on-body device. Signals can be analyzed to determine information related to activities such as eating, chewing, drinking, coughing, or sneezing. In addition, data from an in-ear thermometer or other data sensors can be analyzed in conjunction with the machine learning models to provide data or recommendations to a user on a user device or initiate an action.