US 12,412,067 B2
Visualization of biosignals using machine-learning generated content
Joseph Y. Cheng, Cupertino, CA (US); Bradley W. Griffin, Aptos, CA (US); Hanlin Goh, Santa Clara, CA (US); Helen Y. Weng, San Francisco, CA (US); and Matthias R. Hohmann, Mountain View, CA (US)
Assigned to Apple Inc., Cupertino, CA (US)
Filed by Apple Inc., Cupertino, CA (US)
Filed on Dec. 13, 2022, as Appl. No. 18/080,736.
Claims priority of provisional application 63/334,073, filed on Apr. 22, 2022.
Prior Publication US 2023/0342583 A1, Oct. 26, 2023
Int. Cl. G06N 3/02 (2006.01)
CPC G06N 3/02 (2013.01) [G06T 2207/20084 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving first biosignal data measured from a user;
encoding the first biosignal data into a first vector;
generating, using a generative model and the first vector, a first image by generating first artistic content that correlates substantially with a first state of the user and a first content type selected from a plurality of content types;
providing the generated first image for display;
encoding second biosignal data measured from the user, the second biosignal data different from the first biosignal data, into a second vector; and
generating, using the generative model and the second vector, a second image with second artistic content, different from the first artistic content, that correlates with the first content type selected from the plurality of content types.