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.

Date of Patent:
Jun. 16, 2026

Filed:

Aug. 28, 2023
Applicant:

The Regents of the University of California, Oakland, CA (US);

Inventors:

Aydogan Ozcan, Los Angeles, CA (US);

Yi Luo, Los Angeles, CA (US);

Tairan Liu, Los Angeles, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01N 15/0227 (2024.01); G03H 1/00 (2006.01); G03H 1/04 (2006.01); G06V 10/147 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/52 (2022.01);
U.S. Cl.
CPC ...
G01N 15/0227 (2013.01); G03H 1/0005 (2013.01); G03H 1/0443 (2013.01); G03H 1/0465 (2013.01); G06V 10/147 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/52 (2022.01); G01N 2015/0233 (2013.01); G03H 2001/005 (2013.01); G03H 2001/0447 (2013.01); G03H 2001/0467 (2013.01); G03H 2210/55 (2013.01); G03H 2210/62 (2013.01); G03H 2222/12 (2013.01); G03H 2226/02 (2013.01); G03H 2226/11 (2013.01);
Abstract

A particulate matter detection device takes holographic images of flowing particulate matter concentrated by a virtual impactor, which selectively slows down and guides larger particles to fly through an imaging window. The flowing particles are illuminated by a pulsed laser diode, casting their inline holograms on a CMOS image sensor in a lens-free mobile imaging device. The illumination contains three short pulses with a negligible shift of the flowing particle within one pulse and triplicate holograms of the same particle are recorded at a single frame revealing different perspectives of each particle. A deep neural network classifies the particles based on the acquired holographic images. The device was tested using different types of pollen and achieved a blind classification accuracy of 92.91%. This mobile and cost-effective device weighs ˜700 g and can be used for label-free sensing and quantification of various bio-aerosols over extended periods.


Find Patent Forward Citations

Loading…