公开(公告)号：US11747902B2

公开(公告)日：2023-09-05

申请号：US17174875

申请日：2021-02-12

Applicant: Apple Inc.

Inventor： Erdrin Azemi ,  Joseph Yitan Cheng ,  Hanlin Goh

IPC: G06F3/01 ,  G06N3/04 ,  G06N20/00

CPC classification number: G06F3/015 ,  G06N3/04 ,  G06N20/00

Abstract: Techniques are disclosed for defining a training data set to include biosignals and categorical labels representative of a context. For example, a categorical label may indicate whether a user was performing a difficult or easy mental task while the biosignal was being recorded. A set of first layers in a neural network can be trained using a portion of the training data set associated with a first set of users and at least one second layer can be trained using a portion of the training data set associated with a particular other user. The neural network can then be used to process other biosignals from the particular other user to generate predicted categorical context labels.

公开(公告)号：US12135837B2

公开(公告)日：2024-11-05

申请号：US18355659

申请日：2023-07-20

Applicant: Apple Inc.

Inventor： Erdrin Azemi ,  Joseph Yitan Cheng ,  Hanlin Goh

IPC: G06F3/01 ,  G06N3/04 ,  G06N20/00

Abstract: Techniques are disclosed for defining a training data set to include biosignals and categorical labels representative of a context. For example, a categorical label may indicate whether a user was performing a difficult or easy mental task while the biosignal was being recorded. A set of first layers in a neural network can be trained using a portion of the training data set associated with a first set of users and at least one second layer can be trained using a portion of the training data set associated with a particular other user. The neural network can then be used to process other biosignals from the particular other user to generate predicted categorical context labels.

公开(公告)号：US20220383189A1

公开(公告)日：2022-12-01

申请号：US17554895

申请日：2021-12-17

Applicant: Apple Inc.

Inventor： Joseph Yitan Cheng ,  Amruta Pai ,  Erdrin Azemi ,  Matthias R. Hohmann

IPC: G06N20/00 ,  G06N5/02

Abstract: Methods and systems are provided for predicting cognitive load. A computing device receives sensor measurements from sensors. The sensor measurements correspond to characteristics of a user during the performance of a task. For each sensor, the computing device derives, from the sensor measurements of the sensor, a set of features predictive of the cognitive load of the user; generates, from those features, a self-attention vector that characterizes each feature of the set of features relative to another feature; and defines a feature vector from the features and the self-attention vector. The computing device generates an input feature vector from the feature vector of at least one sensor. The computing device then uses a machine-learning model to generate an indication of the cognitive load of the user during the performance of a task from the feature vector.

公开(公告)号：US12282596B2

公开(公告)日：2025-04-22

申请号：US18403599

申请日：2024-01-03

Applicant: Apple Inc.

Inventor： Erdrin Azemi ,  Ali Moin ,  Christoph H. Krah ,  Joseph Yitan Cheng ,  Kaan Emre Dogrusoz ,  Mohammad Yeke Yazdandoost

IPC: G06F3/01 ,  G06F1/3203 ,  G06F1/3234 ,  G06F1/3206 ,  G06F1/3287

Abstract: A head-mounted device having a plurality of electrodes configured to detect optical events such as the movement of one or more eyes or coarse eye gestures is disclosed. In some examples, the one or more electrodes can be coupled to dielectric elastomer materials whose shape can be changed to vary contact between a user of the head-mounted device and the one or more electrodes to ensure sufficient contact and electrode signal quality. In some examples, the one or more electrodes can be coupled to pressure sensors and control circuitry to monitor and adjust the applied pressure. In some examples, the optical events can be used as triggers for operating the device, including transitioning between operational power modes. In some examples, the triggers can invoke higher resolution sensing capabilities of the head-mounted device. In some examples, the electrodes can be used as an on-head detector to wake-up and/or unlock the device.

公开(公告)号：US11874958B2

公开(公告)日：2024-01-16

申请号：US17448873

申请日：2021-09-24

Applicant: Apple Inc.

Inventor： Erdrin Azemi ,  Ali Moin ,  Christoph H. Krah ,  Joseph Yitan Cheng ,  Kaan Emre Dogrusoz ,  Mohammad Yeke Yazdandoost

IPC: G06F3/01 ,  G06F1/3203 ,  G06F1/3206 ,  G06F1/3234 ,  G06F1/3287

CPC classification number: G06F3/013 ,  G06F1/3203 ,  G06F1/325 ,  G06F3/015 ,  G06F3/017 ,  G06F1/3206 ,  G06F1/3234 ,  G06F1/3287

Abstract: A head-mounted device having a plurality of electrodes configured to detect optical events such as the movement of one or more eyes or coarse eye gestures is disclosed. In some examples, the one or more electrodes can be coupled to dielectric elastomer materials whose shape can be changed to vary contact between a user of the head-mounted device and the one or more electrodes to ensure sufficient contact and electrode signal quality. In some examples, the one or more electrodes can be coupled to pressure sensors and control circuitry to monitor and adjust the applied pressure. In some examples, the optical events can be used as triggers for operating the device, including transitioning between operational power modes. In some examples, the triggers can invoke higher resolution sensing capabilities of the head-mounted device. In some examples, the electrodes can be used as an on-head detector to wake-up and/or unlock the device.

公开(公告)号：US20240012480A1

公开(公告)日：2024-01-11

申请号：US18355659

申请日：2023-07-20

Applicant: Apple Inc.

Inventor： Erdrin Azemi ,  Joseph Yitan Cheng ,  Hanlin Goh

IPC: G06F3/01 ,  G06N3/04 ,  G06N20/00

CPC classification number: G06F3/015 ,  G06N3/04 ,  G06N20/00

Abstract: Techniques are disclosed for defining a training data set to include biosignals and categorical labels representative of a context. For example, a categorical label may indicate whether a user was performing a difficult or easy mental task while the biosignal was being recorded. A set of first layers in a neural network can be trained using a portion of the training data set associated with a first set of users and at least one second layer can be trained using a portion of the training data set associated with a particular other user. The neural network can then be used to process other biosignals from the particular other user to generate predicted categorical context labels.

公开(公告)号：US20210286429A1

公开(公告)日：2021-09-16

申请号：US17174875

申请日：2021-02-12

Applicant: Apple Inc.

Inventor： Erdrin Azemi ,  Joseph Yitan Cheng ,  Hanlin Goh

IPC: G06F3/01 ,  G06N20/00 ,  G06N3/04

Abstract: Techniques are disclosed for defining a training data set to include biosignals and categorical labels representative of a context. For example, a categorical label may indicate whether a user was performing a difficult or easy mental task while the biosignal was being recorded. A set of first layers in a neural network can be trained using a portion of the training data set associated with a first set of users and at least one second layer can be trained using a portion of the training data set associated with a particular other user. The neural network can then be used to process other biosignals from the particular other user to generate predicted categorical context labels.