The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Nov. 12, 2024
Filed:
Jun. 16, 2020
Caire Diagnostics Inc., Pleasanton, CA (US);
Solomon Ssenyange, Fremont, CA (US);
Ryan Leard, Oakland, CA (US);
David Anvar, Sunnyvale, CA (US);
Brian Awabdy, Dublin, CA (US);
Todd Smith, Sunnyvale, CA (US);
Vivek Balasubramanyam, Pleasanton, CA (US);
CAIRE Diagnostics Inc., Pleasanton, CA (US);
Abstract
An asthma management system and method are disclosed for collecting environmental and individual health data to predict the onset of asthma symptoms to allow for preventative therapy tailored on an individual basis. In one embodiment a computer system is in electrical communication with an individual user interface and one or more environmental factor collection points via a communications network. The user interface is adapted to send and receive asthma-related data including asthma profile and real-time asthma status data to the computer system via the communication network, and the environmental factor collection points are adapted to send and receive data to the computer system via the communications network. The computer system further comprises one or more processors connected to memory, and are programmed with executable instructions for implementing one or more algorithms for (1) collecting and storing in memory data received from the individual user interface and from the environmental factor collection points, (2) aggregating the data received from the individual user interface and the environmental factor collection points, and (3) implementing one or more algorithms to generate an asthma symptom onset prediction based on the aggregated data. The onset prediction is then communicated to the user interface. In addition, the one or more processors are further programed with executable instructions to revise one or more asthma symptom onset prediction algorithms where the generated asthma onset prediction and an individual's real-time asthma status data indicate a prediction error.