Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for presenting a human participant with information known to stimulate a person's neural reward system. Receiving an EEG signal from a sensor coupled to the human participant in response to presenting the participant with the information, the EEG signal being associated with the participant's neural reward system. Contemporaneously with receiving the EEG signal, receiving contextual information related to the information presented to the human participant. Processing the EEG signal and the contextual information in real time using a machine learning model trained to associate depression in the person with EEG signals associated with the person's neural reward system and the presented information. Diagnosing whether the participant is experiencing depression based on an output of the machine learning model.

Abstract: A method for analyzing electroencephalogram (EEG) signals is disclosed. Information associated with two or more options is presented to a user. EEG signals from a sensor coupled to the user are received contemporaneously to the user receiving information associated with the two or more options. The EEG signals are processed in real time to determine which one of the options was selected by the user. In response to determining which one of the options was selected by the user, an action from one or more possible actions associated with the information presented to the user is selected. An output associated with the selected action is then generated.

Abstract: Examples implementations relate to determining path confidence for a vehicle. An example method includes receiving a request for a vehicle to navigate a target location. The method further includes determining a navigation path for the vehicle to traverse a first segment of the target location based on a plurality of prior navigation paths previously determined for traversal of segments similar to the first segment of the target location. The method also includes determining a confidence level associated with the navigation path. Based on the determined confidence level, the method additionally includes selecting a navigation mode for the vehicle from a plurality of navigation modes corresponding to a plurality of levels of remote assistance. The method further includes causing the vehicle to traverse the first segment of the target location using a level of remote assistance corresponding to the selected navigation mode for the vehicle.

Abstract: Systems and methods for automated release of insects are disclosed. In one embodiment, a system includes: an insect storage device defining one or more internal compartments to store a population of insects; a loading mechanism for loading the insect storage device with a population of insects; and an insect release device coupled to the loading mechanism and configured to release into an environment one or more insects from the population of insects in the insect storage device.

Abstract: Systems and methods for automated release of insects are disclosed. In one embodiment, a system includes: an insect storage device defining one or more internal compartments to store a population of insects; a loading mechanism for loading the insect storage device with a population of insects; and an insect release device coupled to the loading mechanism and configured to release into an environment one or more insects from the population of insects in the insect storage device.

Abstract: An example system includes a delivery vehicle, a sensor connected to the delivery vehicle, and a control system that determines a delivery destination for an object. The control system receives sensor data representing a physical environment of at least a portion of the delivery destination and determines a drop-off spot for the object within the delivery destination by way of an artificial neural network (ANN). The ANN is trained to determine the drop-off spot based on previously-designated drop-off spots within corresponding delivery destinations and includes an input node that receives the sensor data, hidden nodes connected to the input node, and an output node connected to the hidden nodes that provides data indicative of a location of the drop-off spot. The control system additionally causes the delivery vehicle to move to and place the object at the drop-off spot.

Abstract: Examples implementations relate to navigation path determination. An example method includes receiving, at a computing system, video data showing a demonstration path for navigating a location. The method further includes identifying, using the video data, a set of permissible surfaces at the location, wherein each permissible surface was traversed by the demonstration path. The method additionally includes determining a navigation path for a vehicle to follow at the location, wherein the navigation path includes a variation from the demonstration path such that the variation causes the vehicle to stay within one or more permissible surfaces from the set of permissible surfaces. The method also includes causing, by the computing system, the vehicle to follow the navigation path to navigate the location.

Abstract: The present disclosure relates to electromagnetic resonator antennas and methods for their manufacture. An example electromagnetic resonator antenna includes a first substrate and a first metal layer disposed on the first substrate. The first metal layer includes copper. The antenna also includes a dielectric layer disposed on the first metal layer. The dielectric layer includes a polarizable electrical insulator. The antenna additionally includes a second metal layer disposed on the dielectric layer. The second metal layer includes copper. The antenna yet further includes a second substrate disposed on the second metal layer and a feed line electrically coupled to at least one of the first metal layer or the second metal layer. At least one aspect of at least one of the first metal layer, the dielectric layer, or the second metal layer is selected based on a desired resonance frequency.

Abstract: A sensor device includes a sensor housing defining a channel extending along a channel axis through the housing from a first side of the sensor housing to a second side of the sensor housing opposite the first side, at least one contact electrode extending from the first side of the housing, an electrically-conducting lead attached to the housing in electrical communication with the at least one contact electrode, and a locking mechanism located in the channel permitting one-way axial motion of a thread threaded through the channel from the first side to the second side.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining a three-dimensional (3D) model of an operating volume for a cable-suspended robotic system, where the operating volume is defined, at least in part, by a plurality of cable support structures. Identifying a cable positioned device suspended from a plurality of cables and an object that obstructs a path of the cable positioned device within the operating volume within the 3D model. Locating the cable positioned device relative to the object using the 3D model. Controlling one or more cable motors to navigate the cable positioned device within the operating volume.

Abstract: A bioamplifier for analyzing electroencephalogram (EEG) signals is disclosed. The bioamplifier includes an input terminal for receiving an EEG signal from a plurality of sensors coupled to a user. The bioamplifier also includes an analogue-to-digital converter arranged to receive the EEG signal from the input terminal and convert the EEG signal to a digital EEG signal. A data processing apparatus within the bioamplifier is arranged to receive the digital EEG signal from the analogue-to-digital converter and programmed to process, in real time the digital EEG signal using a first machine learning model to generate a cleaned EEG signal having a higher signal-to-noise ratio than the digital EEG signal. The bioamplifier further includes a power source to provide electrical power to the analogue-to-digital converter and the data processing apparatus. The bioamplifier includes a housing that contains the analogue-to-digital converter, the data processing apparatus, the power source, and the sensor input.

Abstract: A method for generating an EEG signal is disclosed. Multiple signals from multiple electrodes applied to a user's scalp are measured. The signals correspond to electrical activity generated by the user's brain. Each of the signals is evaluated using a machine learning algorithm in real-time to determine a quality of each of the signals. One or more of the signals is selected based on quality in real-time to provide one or more selected signals. An EEG signal is outputted corresponding to the electrical activity based on the selected signals.

Abstract: An electroencephalogram (EEG) system is disclosed. The EEG system includes an EEG controller and an EEG sensor that includes a contact surface, the contact surface including an electrically-conductive portion in communication with the EEG controller and a sensor release element in communication with the EEG controller, the sensor release element being configured to perform, in response to a signal from the EEG controller, a release action to reduce adhesion of an electrically-conductive gel between the contact of the sensor and the user's skin.

Abstract: A method for analyzing electroencephalogram (EEG) signals is disclosed. Information associated with two or more options is presented to a user. EEG signals from a sensor coupled to the user are received contemporaneously to the user receiving information associated with the two or more options. The EEG signals are processed in real time to determine which one of the options was selected by the user. In response to determining which one of the options was selected by the user, an action from one or more possible actions associated with the information presented to the user is selected. An output associated with the selected action is then generated.

Abstract: A method for obtaining an electroencephalogram (EEG) of a user is disclosed. A reference sensor is attached to the user by connecting a first component of the reference sensor to a second component of the reference sensor, at least a portion of the first component being sub-dermally implanted on or adjacent to a mastoid process of the user. At least one active sensor is attached to the user. A first signal is detected from the reference sensor simultaneously as a second signal is detected from the at least one active sensor. The EEG is obtained based on the first signal and the second signal.

Abstract: Examples implementations relate to navigation path determination. An example method includes receiving, at a computing system, video data showing a demonstration path for navigating a location. The method further includes identifying, using the video data, a set of permissible surfaces at the location, wherein each permissible surface was traversed by the demonstration path. The method additionally includes determining a navigation path for a vehicle to follow at the location, wherein the navigation path includes a variation from the demonstration path such that the variation causes the vehicle to stay within one or more permissible surfaces from the set of permissible surfaces. The method also includes causing, by the computing system, the vehicle to follow the navigation path to navigate the location.

Abstract: An example system includes a delivery vehicle, a sensor connected to the delivery vehicle, and a control system that determines a delivery destination for an object. The control system receives sensor data representing a physical environment of at least a portion of the delivery destination and determines a drop-off spot for the object within the delivery destination by way of an artificial neural network (ANN). The ANN is trained to determine the drop-off spot based on previously-designated drop-off spots within corresponding delivery destinations and includes an input node that receives the sensor data, hidden nodes connected to the input node, and an output node connected to the hidden nodes that provides data indicative of a location of the drop-off spot. The control system additionally causes the delivery vehicle to move to and place the object at the drop-off spot.

Abstract: Examples implementations relate to determining path confidence for a vehicle. An example method includes receiving a request for a vehicle to navigate a target location. The method further includes determining a navigation path for the vehicle to traverse a first segment of the target location based on a plurality of prior navigation paths previously determined for traversal of segments similar to the first segment of the target location. The method also includes determining a confidence level associated with the navigation path. Based on the determined confidence level, the method additionally includes selecting a navigation mode for the vehicle from a plurality of navigation modes corresponding to a plurality of levels of remote assistance. The method further includes causing the vehicle to traverse the first segment of the target location using a level of remote assistance corresponding to the selected navigation mode for the vehicle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving brain activity data of a user from a brain wave sensor. Identifying Alpha wave activity from the brain activity data. Determining a synchronization timing for presenting content to the user such that the content appears on a display device during a predetermined phase of the Alpha wave activity based on the Alpha wave activity. Causing the content to be displayed on the display device according to the synchronization timing, where the content includes a first content item and a second content item that is associated with the first content item.

Abstract: Techniques and mechanisms to form a semi-rigid structure from a flexible sheet. In an embodiment, a portion of the flexible sheet includes layer portions and one or more compartments each disposed between said layer portions. The one or more compartments each having disposed therein a first fluid compound that is reactive—e.g., when exposed to oxygen, heat, ultraviolet (or other) light, or a different fluid compound—to form a solid. In another embodiment, a graphic printed on the flexible sheet indicates a location of the one or more compartments. Activation of the one or more compartments and bending of the flexible sheet portion at the activated one or more compartments aids in the formation of a shelter or other semi-rigid structure.