US 11,751,796 B2
Systems and methods for neuro-feedback training using video games
Bicheng Han, Somerville, MA (US); Tianhe Wang, Revere, MA (US); Max Newlon, Allston, MA (US); Joanne Wylie, Allston, MA (US); Chengbang Zhou, Zhangqiu (CN); Jianlin Zhou, Everett, MA (US); Xiang Yu, Brighton, MA (US); Bowei Huang, Liuzhou (CN); and Zhaoyi Yang, Boston, MA (US)
Assigned to BRAINCO, INC., Somerville, MA (US)
Filed by BrainCo Inc., Somerville, MA (US)
Filed on Jan. 4, 2017, as Appl. No. 15/398,691.
Prior Publication US 2018/0184936 A1, Jul. 5, 2018
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 5/375 (2021.01); A61B 5/00 (2006.01); A63F 13/46 (2014.01); A63F 13/28 (2014.01); A63F 13/25 (2014.01); A63F 13/355 (2014.01); A63F 13/537 (2014.01); A63F 13/212 (2014.01); A61B 5/374 (2021.01); A61B 5/16 (2006.01); A61B 5/291 (2021.01)
CPC A61B 5/375 (2021.01) [A61B 5/374 (2021.01); A61B 5/6803 (2013.01); A63F 13/212 (2014.09); A63F 13/25 (2014.09); A63F 13/28 (2014.09); A63F 13/355 (2014.09); A63F 13/46 (2014.09); A63F 13/537 (2014.09); A61B 5/168 (2013.01); A61B 5/291 (2021.01); A61B 5/7203 (2013.01); A61B 5/7264 (2013.01)] 24 Claims
OG exemplary drawing
 
1. A neuro-feedback training method performed by a video game application executed by a mobile terminal, the method comprising:
repeatedly generating a plurality of types of feedback signals during a current neuro-feedback training session, the plurality of types of feedback signals comprising at least a visual cue, an audio cue, and a tactile cue;
executing a machine learning algorithm to analyze data showing a user's performance during one or more past neuro-feedback training sessions, wherein the executing of the machine learning algorithm selects a first type of feedback signals from the plurality of types of feedback signals, the selecting being based at least partially on the user's neuro-feedback training performance in response to the plurality of types of feedback signals, respectively;
generating, in the computer game, the first type of feedback signals at an increased frequency;
receiving a brainwave signal, via a communication network, the brainwave signal being measured by at least one sensor attached to the user;
determining a frequency distribution of the brainwave signal, wherein the frequency distribution comprises a first frequency band and a second frequency band;
determining a reward in the video game application, in response to:
a first value indicative of an amount of the brainwave signal within the first frequency band stays above an initial value of a first threshold for a first time period, and
a second value indicative of an amount of the brainwave signal within the second frequency band is below a second threshold during the first time period;
providing, to the user, a first feedback signal indicative of the reward, wherein the first feedback signal is one of the first type of feedback signals, and providing the first feedback signal comprises displaying, on the mobile terminal, a first animation corresponding to the first value and a second animation corresponding to the second value; and
adaptively adjusting the first threshold or the first time period, based on a determination of whether the first value stays above the initial value of the first threshold for the first time period.