Toyota Motor Engineering & Manufacturing North America, Inc.

University of Connecticut

Muhamed K Farooq

Ercan Mehmet Dede

Chungchih Chou

Sean P Rodrigues

Hossein Hamidi Shishavan

Insoo Kim

Kia Golzari

Shailesh N Joshi

Paul Donald Schmalenberg

Ravi Rajamani

Frederico Marcolino Quintao Severgnini

Krishna R Pattipati

Ali M Bazzi

Donald Mcmenemy

John Kaminski

An emotion-aware smart refrigerator is provided which may include various sensors and presentation mechanisms to identify a user's interest in item(s) contained within the emotion-aware smart refrigerator via an evoked physiological response, such as a visual evoked potential (VEP). The user's level of interest may also be gauged by the emotion-aware smart refrigerator. With consideration given to the user's VEP as well as the user's level of interest, and other considerations such as the user's diet, desired health goals, dietary restrictions, etc., the emotion-aware smart refrigerator may present suggested items and item amounts to the user.

Emotion-aware smart refrigerator

System, methods, and other embodiments described herein relate to controlling display attributes within a visual interface for enhancing stimuli and responses of a user. In one embodiment, a method includes selecting display attributes related to a first layer of an image and a second layer of the image, and the first layer includes a symbol, the second layer represents a background of the symbol, and the image is associated with an interface to control a component. The method also includes oscillating, at first multiple of a frequency, between first values of the display attributes representing colors that are different for displaying the first layer, and the colors changing by a duty cycle associated with the first multiple of the frequency. The method also includes oscillating, at a second multiple of the frequency, between second values for displaying the second layer in parallel with the first layer until detecting a selection associated with the interface.

Systems and methods for producing stimuli in a visual interface using modulation

The disclosure is related configuring a vehicle according to a user profile, where an individual user profile can be selected from a registry containing one or more user profiles using electroencephalogram (EEG). An additional biometric, such as gait, can also be used. The user profiles can include a variety of the user preferences, such as the preferred climate, seat settings, mode of payment, route to take, and more. A mobile device can also be used to add a layer of security and privacy, where the mobile device has sole access to the user's user profile.

Passenger identification and profile mapping via brainwave monitoring

In accordance with one embodiment of the present disclosure, a method includes measuring brain activity for a target frequency and a second harmonic frequency based on a default value of display parameters for a plurality of icons, determining whether a strength of the target frequency and the second harmonic frequency are below a threshold level, and modifying one or more display parameters in response to the strength of the target frequency and the second harmonic frequency being below the threshold level.

Methods, systems, and non-transitory computer-readable mediums for SSVEP detection optimization

A method of confirming an identity of a user, including displaying a first visual indicator, where the first visual indicator is flashing at a first frequency to induce a first brainwave activity. The first brainwave activity of the user may be measured by a sensor. The measured first brainwave activity may be compared against a user profile to confirm the identity of the user.

Systems and methods for brain-machine interfaces and EEG-based driver identification

System, methods, and other embodiments described herein relate to controlling display attributes within a visual interface for enhancing stimuli and responses of a user. In one embodiment, a method includes selecting display attributes related to a first layer of an image and a second layer of the image, wherein the image is associated with an interface to control a component. The method also includes oscillating, at a frequency, between first values of the display attributes for displaying the first layer. The method also includes oscillating, at a harmonic of the frequency, between second values of the display attributes for displaying the second layer in parallel with the first layer until detecting a selection associated with the interface.

Systems and methods for producing stimuli in a visual interface

In accordance with one embodiment of the present disclosure, a method includes generating a plurality of icons, wherein each icon has a target frequency unique from each other, receiving brain activity data based on an epoch, generating a reference signal based on the epoch, calculating correlation coefficients between the brain activity data and the reference signal, wherein the correlation coefficients are calculated in a window that is within ±0.5 Hz of the target frequencies, including endpoints, determining a confidence score based on the correlation coefficients and the epoch, and determining a selected icon among the plurality of icons based on the correlation coefficients in response to the confidence score surpassing a threshold confidence score.

Methods, systems, and non-transitory computer-readable mediums for SSVEP detection

The present disclosure is related to utilizing contactless brainwave detectors to gather a user's unique electroencephalogram (EEG) data. EEG data, as well as an additional biometric, such as gait, can be used to determine whether users have access to enter a locked system, such as a door. An access list can be created and pre-registered with the EEG data and any additional biometric data of users who have access to enter the locked system. As the user nears the locked system, they can generate the EEG data to unlock the locked system by thinking of a pre-registered password stored in the access list.

Door actuation system using contactless brainwave monitoring and gait recognition

A device that uses brainwave activity to allow a user to perform hands-free tasks is disclosed. For example, the device can include a transparent display, an electroencephalogram (EEG) sensor, and a processing circuitry coupled to the transparent display and the EEG sensor. The EEG sensor can be configured to sense an EEG signal corresponding to brain activity associated with a user of the device. The processing circuitry can be configured to display a visual stimulus on the transparent display and generate a control signal associated with a task of the user based on the EEG signal. Therefore, the user can use his brainwave activity to perform hands-free tasks.

Hands-free vehicle sensing and applications as well as supervised driving system using brainwave activity

A method, system, and non-transitory computer readable medium describing an autoencoder that creates a reduced feature space from healthy power electronics devices for training. Devices under test are then encoded and compared to the encoded features of the healthy devices to determine health of the other devices. Contextual information is used to build multiple models that compare power electronics devices from similarly operated vehicles with one another.

Autoencoder utilizing vehicle contextual information

A driver support system of a vehicle that includes a neuroimaging sensor and a positioning sensor, the neuroimaging sensor detects neurological signals of an occupant and the positioning sensor detects a position of the occupant. The neuroimaging sensor is configured to be positioned within the vehicle distally from the occupant. The system further includes a processor and non-transitory computer-readable medium storing computer-readable instructions executed by the processor to generate a brainwave map based on the neurological signals, calibrate the brainwave map based on the position of the occupant, and determine a mental state of the occupant based on the calibrated-brainwave map. The processor further actuates vehicle support control in response to determining the mental state of the occupant.

Growing community of inventors

Ann Arbor, MI, United States of America

Muhamed K Farooq