公开(公告)号：US20210251558A1

公开(公告)日：2021-08-19

申请号：US17236266

申请日：2021-04-21

Applicant: Research Triangle Institute

Inventor： Kristin Hedgepath Gilchrist ,  Sonia Grego ,  Gregory Frederick Lewis ,  Meghan Sarah Hegarty-Craver

IPC: A61B5/00 ,  A61B5/352 ,  A61B5/11 ,  A61B5/0205 ,  G16H50/30

Abstract: A computer implemented method is disclosed for detecting a mild traumatic brain injury (mTBI) on a subject having recently suffered a head injury. The method includes (1) receiving first electrocardiogram (ECG) data from the subject during a first transition from a first position to a second position; and (2) determining a probability value of mTBI within the subject based at least partially on the first ECG data during the first transition. The first position may be a prone position or a supine position and the second position may be a standing position.

公开(公告)号：US20240264574A1

公开(公告)日：2024-08-08

申请号：US18433523

申请日：2024-02-06

Applicant: Research Triangle Institute

Inventor： Lynn Davis ,  Meghan Sarah Hegarty-Craver ,  Howard Jerome Walls ,  Karmann C. Riter

IPC: G05B19/042 ,  G16H40/63

CPC classification number: G05B19/042 ,  G16H40/63 ,  G05B2219/25011

Abstract: Disclosed herein are methods, systems, and devices for automated personalized control of building systems. According to one embodiment, a method is implemented on a computing system. The method includes receiving wearable device health data associated with a plurality of occupants associated with a building and determining a plurality of settings for a plurality of appliances associated with the building based on the wearable device health data.

公开(公告)号：US20240127954A1

公开(公告)日：2024-04-18

申请号：US18398623

申请日：2023-12-28

Applicant: Research Triangle Institute

Inventor： Kristin Hedgepath Gilchrist ,  Meghan Sarah Hegarty-Craver ,  Dorota Temple ,  Robert Furberg

IPC: G16H50/20 ,  A61B5/00 ,  A61B5/01 ,  A61B5/024 ,  A61B5/11 ,  A61B5/1455 ,  A61B5/28 ,  A61B5/352 ,  G16H10/60

CPC classification number: G16H50/20 ,  A61B5/0022 ,  A61B5/0024 ,  A61B5/01 ,  A61B5/02405 ,  A61B5/1102 ,  A61B5/1118 ,  A61B5/1455 ,  A61B5/28 ,  A61B5/352 ,  A61B5/4266 ,  A61B5/681 ,  A61B5/6823 ,  A61B5/742 ,  G16H10/60 ,  A61B2505/07 ,  A61B2560/045 ,  A61B2560/0462 ,  A61B2562/0219

Abstract: Disclosed herein are systems, methods, and devices of detecting illness in presymptomatic and asymptomatic infected persons using wearable sensor technology. In a first embodiment, a method is implemented on a computing device, the method includes receiving first sensor data associated with the person over a first period of time and applying the first sensor data to a multi-variate detection model. The method further includes receiving second sensor data associated with the person over a second period of time and applying the second sensor data to the multi-variate detection model. Further the method includes determining a probability value of the illness in the person using the multi-variate detection model and transmitting the probability value to a user interface (UI).