公开(公告)号：US11045095B2

公开(公告)日：2021-06-29

申请号：US16083052

申请日：2017-03-08

Applicant: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY ,  Nongjian Tao ,  Dangdang Shao

Inventor： Nongjian Tao ,  Dangdang Shao

IPC: G06K9/00 ,  A61B5/0205 ,  A61B5/00 ,  A61B5/021 ,  A61B5/024 ,  A61B5/11 ,  G06T7/20

Abstract: Various embodiments of systems and methods for tracking ballistocardiogram, photoplethysmogram, blood pressure and abnormal heart rhythm based on optical imaging of a human body are disclosed. Ballistocardiogram and photoplethysmogram signals from a similar region of the human body are simultaneously obtained, and the time delay between the two signals is used to determine the blood pressure of the subject, together with other physiological parameters of the subject, including gender, age, weight, height, heart rate, stroke volume, blood pressure and abnormal heart rhythm obtained using other methods.

公开(公告)号：US20210130868A1

公开(公告)日：2021-05-06

申请号：US16500370

申请日：2018-04-05

Applicant: Arizona Board of Regents on behalf of Arizona State University

Inventor： Nongjian Tao ,  Shaopeng Wang ,  Hui Yu

IPC: C12Q1/18 ,  G01N21/51 ,  G06T7/00 ,  G16H10/40 ,  G16H30/40 ,  G16H50/20

Abstract: A method for deep learning video microscopy-based antimicrobial susceptibility testing of a bacterial strain in a sample by acquiring image sequences of individual bacterial cells of the bacterial strain in a subject sample before, during, and after exposure to each antibiotic at different concentrations. The image sequences are compressed into static images while preserving essential phenotypic features. Data representing the static images is input into a pre-trained deep learning (DL) model which generates output data; and antimicrobial susceptibility for the bacterial strain is determined from the output data.

公开(公告)号：US10663442B2

公开(公告)日：2020-05-26

申请号：US16279698

申请日：2019-02-19

Applicant: Arizona Board of Regents on behalf of Arizona State University

Inventor： Erica Forzani ,  Nongjian Tao ,  Di Zhao ,  Francis Tsow

IPC: G01N31/00 ,  G01N33/00 ,  A61B5/08 ,  G01N21/84 ,  G01N33/497 ,  A61B5/00 ,  G01N1/22

Abstract: A method for CO2 detection includes obtaining a gas sample; exposing a CO2 sensor to the gas sample, where the sensor includes a reversible and selective pH-sensitive nanocomposite sensor element for CO2 detection, and a hydrophobic surface; compensating for humidity and temperature; coupling at least one light source to receive signals from the CO2 sensor and respond to color changes in the sensor by transducing the color change into a light intensity change; measuring flow; and receiving signals from the at least one light source by at least one photodiode which responds to light intensity changes by transducing the light intensity changes into electronic signals representing varying degrees of light intensity.