公开(公告)号：US20190113973A1

公开(公告)日：2019-04-18

申请号：US16132242

申请日：2018-09-14

申请人： INTERAXON INC

发明人： Trevor CE COLEMAN ,  Christopher Allen AIMONE ,  Ariel Stephanie GARTEN ,  Locillo (Lou) Giuseppe PINO ,  Paul Harrison BARANOWSKI ,  Raul Rajiv RUPSINGH ,  Kapil Jay Mishra VIDYARTHI ,  Graeme MOFFAT ,  Samuel Thomas MACKENZIE

IPC分类号： G06F3/01 ,  G16H40/67 ,  G06F19/00 ,  H04L29/06 ,  H04L12/16 ,  A61B5/00 ,  A61B5/0476 ,  G06F17/30

摘要： A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided. The system includes an intelligent bio-signal processing system that is operable to: capture bio-signal data and in addition optionally non-bio-signal data; and analyze the bio-signal data and non-bio-signal data, if any, so as to: extract one or more features related to at least one individual interacting with the biofeedback computer system; classify the individual based on the features by establishing one or more brain wave interaction profiles for the individual for improving the interaction of the individual with the one or more biofeedback computer systems, and initiate the storage of the brain waive interaction profiles to a database; and access one or more machine learning components or processes for further improving the interaction of the individual with the one or more biofeedback computer systems by updating automatically the brain wave interaction profiles based on detecting one or more defined interactions between the individual and the one or more of the biofeedback computer systems. A number of additional system and computer implemented method features are also provided.

公开(公告)号：US20230309887A1

公开(公告)日：2023-10-05

申请号：US18201502

申请日：2023-05-24

申请人： INTERAXON INC.

发明人： Christopher AIMONE ,  Graeme MOFFAT ,  Hubert JACOB BANVILLE ,  Sean WOOD ,  Subash PADMANABAN ,  Sam KERR ,  Aravind RAVI

IPC分类号： A61B5/246 ,  A61B5/00 ,  A61B5/377 ,  A61B5/375 ,  G16H50/50

CPC分类号： A61B5/246 ,  A61B5/375 ,  A61B5/377 ,  A61B5/7267 ,  A61B5/7275 ,  G16H50/50

摘要： Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.

公开(公告)号：US20200218350A1

公开(公告)日：2020-07-09

申请号：US16818351

申请日：2020-03-13

申请人： INTERAXON INC

发明人： Trevor CE COLEMAN ,  Christopher Allen AIMONE ,  Ariel Stephanie GARTEN ,  Locillo (Lou) Giuseppe PINO ,  Paul Harrison BARANOWSKI ,  Raul Rajiv RUPSINGH ,  Kapil Jay Mishra VIDYARTHI ,  Graeme MOFFAT ,  Samuel Thomas MACKENZIE

IPC分类号： G06F3/01 ,  G06F16/00 ,  A61B5/00 ,  A61B5/0476 ,  H04L12/16 ,  H04L29/06 ,  G16H40/67 ,  G16H50/20 ,  G16H50/70 ,  G16H40/63 ,  A61B5/16 ,  H04L29/08 ,  G06N20/00

摘要： A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided. The system includes an intelligent bio-signal processing system that is operable to: capture bio-signal data and in addition optionally non-bio-signal data; and analyze the bio-signal data and non-bio-signal data, if any, so as to: extract one or more features related to at least one individual interacting with the biofeedback computer system; classify the individual based on the features by establishing one or more brain wave interaction profiles for the individual for improving the interaction of the individual with the one or more biofeedback computer systems, and initiate the storage of the brain waive interaction profiles to a database; and access one or more machine learning components or processes for further improving the interaction of the individual with the one or more biofeedback computer systems by updating automatically the brain wave interaction profiles based on detecting one or more defined interactions between the individual and the one or more of the biofeedback computer systems. A number of additional system and computer implemented method features are also provided.