US 11,744,508 B2
Biological marker and methods
Bruce J. Gluckman, State College, PA (US); Fatemeh Bahari, State College, PA (US); and Steven J. Schiff, State College, PA (US)
Assigned to The Penn State Research Foundation, University Park (PA)
Filed by The Penn State Research Foundation, University Park, PA (US)
Filed on Sep. 7, 2021, as Appl. No. 17/468,398.
Application 17/468,398 is a continuation of application No. 16/396,316, filed on Apr. 26, 2019, granted, now 11,141,097.
Claims priority of provisional application 62/663,213, filed on Apr. 26, 2018.
Prior Publication US 2021/0401356 A1, Dec. 30, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 5/00 (2006.01); A61B 5/0205 (2006.01); A61B 5/316 (2021.01); A61B 5/352 (2021.01); A61B 5/374 (2021.01)
CPC A61B 5/4094 (2013.01) [A61B 5/0205 (2013.01); A61B 5/316 (2021.01); A61B 5/352 (2021.01); A61B 5/374 (2021.01); A61B 5/7275 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method of evaluating the effectiveness of an intervention measure, comprising:
estimating the risk of occurrence of a physiological event in a mammal, wherein said estimating comprises:
obtaining brain activity data that describes brain activity of the mammal over a first period of time;
obtaining peripheral activity data that describes peripheral activity of the mammal over a second period of time;
receiving, by at least one device, brain data from a brain activity measurement device that describes brain activity of a mammal over the first period of time;
receiving, by the at least one device, periphery data from a peripheral activity measurement device that describes peripheral activity of a mammal over the second period of time;
generating, by the at least one device, one or more brain feature representations based on the brain data;
generating, by the at least one device, one or more periphery feature representations based on the periphery data;
generating, by the at least one device, one or more brain statistical distributions of the one or more brain feature representations;
generating, by the at least one device, one or more periphery statistical distributions of the one or more periphery feature representations;
identifying, by the at least one device, one or more brain feature representations that fall outside of a predetermined range in the brain statistical distribution to generate a set of one or more target brain feature representations;
identifying, by the at least one device, one or more periphery feature representations that fall outside of a predetermined range in the periphery statistical distribution to generate a set of one or more target periphery feature representations;
determining, by the at least one device, a brain-periphery temporal association between the one or more target brain feature representations and the one or more target periphery feature representations;
determining, by the at least one device, an estimate of risk of a future physiological event based on the brain-periphery temporal association; and
providing, by the at least one device, an indication of the estimate of risk of the future physiological event;
applying at least one intervention measure that is commensurate with the prevention of the physiological event; and
determining the effectiveness of the intervention measure.