Abstract: This document relates to employing tongue gestures to control a computing device, and training machine learning models to detect tongue gestures. One example relates to a method or technique that can include receiving one or more motion signals from an inertial sensor. The method or technique can also include detecting a tongue gesture based at least on the one or more motion signals, and outputting the tongue gesture.

Abstract: This document relates to employing physiological feedback to aid a user in targeting objects using a computing device. One example relates to a method or technique that can include receiving a user attention signal conveying where a user directs attention. The method or technique can also include, based on the user attention signal, identifying a predicted object that the user intends to target with a targeting mechanism and outputting a visual identification of the predicted object. The method or technique can also include receiving a user reaction signal conveying a physiological reaction of the user to the visual identification of the predicted object. The method or technique can also include, in an instance when the physiological reaction of the user indicates an error, identifying another predicted object that the user intends to target with the targeting mechanism.

Abstract: This document relates to employing tongue gestures to control a computing device, and training machine learning models to detect tongue gestures. One example relates to a method or technique that can include receiving one or more motion signals from an inertial sensor. The method or technique can also include detecting a tongue gesture based at least on the one or more motion signals, and outputting the tongue gesture.

Abstract: This document relates to employing physiological feedback to aid a user in targeting objects using a computing device. One example relates to a method or technique that can include receiving a user attention signal conveying where a user directs attention. The method or technique can also include, based on the user attention signal, identifying a predicted object that the user intends to target with a targeting mechanism and outputting a visual identification of the predicted object. The method or technique can also include receiving a user reaction signal conveying a physiological reaction of the user to the visual identification of the predicted object. The method or technique can also include, in an instance when the physiological reaction of the user indicates an error, identifying another predicted object that the user intends to target with the targeting mechanism.

Abstract: This document relates to employing biosignals to evaluate predictions made by predictive models. For example, user attention can be inferred from a user attention signal such as gaze. When the user directs attention to a prediction output by a given predictive model, a user reaction signal such as an electroencephalogram or pupillary diameter measurement can be processed to determine whether the user perceives an error. If the user perceives an error, an error indication can be output. Error indications can be used to evaluate the predictive model, replace predictions generated by the predictive model, train the predictive model, etc.

Abstract: The production method to accomplish synchronous resonance of electrical molecules includes: restructuring mineral elements to form an activated mineral element featuring molecular synchronous resonance; building a molecular synchronous resonance device using the activated mineral element as a technical feature; and transferring the molecular resonance wave frequency of 1014 times per minute into an electronic device or component in the form of waves through said molecular synchronous resonance device.

Abstract: The description relates to self-dispensing electrodes. One example can include a curved hollow tube configured to hold a flowable conductive material and a selective retention mechanism positioned on the curved hollow tube and configured to retain the flowable conductive material in the hollow tube unless a force is imparted on the curved hollow tube.

Abstract: A wearable device worn at a head region of a user includes electrodes for measuring a signal evoked by a visual stimulus. The electrodes include a first dry electrode configured to contact the skin around an car of the user. The se electrodes additionally include a second dry electrode configured to provide a reference signal for the measurement of the signal evoked by the visual stimulus.

Abstract: This document relates to employing tongue gestures to control a computing device, and training machine learning models to detect tongue gestures. One example relates to a method or technique that can include receiving one or more motion signals from an inertial sensor. The method or technique can also include detecting a tongue gesture based at least on the one or more motion signals, and outputting the tongue gesture.

Abstract: This document relates to employing tongue gestures to control a computing device, and training machine learning models to detect tongue gestures. One example relates to a method or technique that can include receiving one or more motion signals from an inertial sensor. The method or technique can also include detecting a tongue gesture based at least on the one or more motion signals, and outputting the tongue gesture.

Abstract: A semi-dry electrode combines advantages of wet electrodes and dry electrodes by use of a rotatable ball to apply a conductive gel at the tip of the electrode in a manner similar to how a ballpen applies ink. A reservoir in the semi-dry electrode contains the conductive gel that is applied by the ball to the skin of the user. This creates a thin film of conductive gel at the tip of the semi-dry electrode which reduces impedance and increases the signal-to-noise (SNR) ratio. Directly applying the conductive gel from within the electrode itself reduces mess and improves user convenience. The semi-dry electrode may be used in a lightweight electroencephalography (EEG) monitoring device to detect brain activity. The brain activity may be used as input for a brain-computer interface (BCI).

Abstract: A force-controlled electroencephalogram (EEG) monitoring device maintains a constant pressure between electrodes and the scalp of a user thereby increasing user comfort. Arms on the EEG monitoring device position the electrodes in contact with specific regions on the head of the user. The dimension, shape, and curvature of the arms affect the amount of force with which an electrode is held in contact with the user's scalp. The amount of pressure may be different for different regions of the user's head to achieve a balance between comfort and conductivity. The amount of pressure may be further modulated by the use of spring-loaded electrode holders that allow an electrode to move relative to the holder. To further improve user comfort, the tips of the electrodes may be hemispherical rather than pointed. The EEG monitoring device can be used as input for a brain-computer interface (BCI).

Abstract: A system for vibration-driven sensing may include a wearable dimensioned to be donned by a user of an artificial reality system. The system may also include a vibration sensor that is incorporated into the wearable and generates an electrical response that corresponds to a vibration detected at the wearable. The system may further include at least one processing device communicatively coupled to the vibration sensor. The processing device may determine, based at least in part on the electrical response generated by the vibration sensor, that the user has made a specific gesture with at least one body part. In response to this determination, the processing device may generate an input command for the artificial reality system based at least in part on the specific gesture made by the user. Various other systems and methods are also disclosed.

Abstract: A brain computer interface system includes a wearable interface, an eye tracking device, and a client device for determining what object a user is looking at on an electronic display. The client device determines a region on the electronic display based on an estimated user gaze direction received from the eye tracking device. For each virtual object in the gaze region, the client device displays a visual stimulus with a unique frequency. The client device receives from the wearable interface an electrical potential signal measured at the user's brain and evoked by a visual stimulus on the electronic display. The client device identifies the object in the gaze region with a stimulus frequency matching a frequency derived from the potential signal, and executes instructions relating to the object.

Abstract: A system for vibration-driven sensing may include a wearable dimensioned to be donned by a user of an artificial reality system. The system may also include a vibration sensor that is incorporated into the wearable and generates an electrical response that corresponds to a vibration detected at the wearable. The system may further include at least one processing device communicatively coupled to the vibration sensor. The processing device may determine, based at least in part on the electrical response generated by the vibration sensor, that the user has made a specific gesture with at least one body part. In response to this determination, the processing device may generate an input command for the artificial reality system based at least in part on the specific gesture made by the user. Various other systems and methods are also disclosed.

Abstract: A brain computer interface system includes a wearable interface, an eye tracking device, and a client device for determining what object a user is looking at on an electronic display. The client device determines a region on the electronic display based on an estimated user gaze direction received from the eye tracking device. For each virtual object in the gaze region, the client device displays a visual stimulus with a unique frequency. The client device receives from the wearable interface an electrical potential signal measured at the user's brain and evoked by a visual stimulus on the electronic display. The client device identifies the object in the gaze region with a stimulus frequency matching a frequency derived from the potential signal, and executes instructions relating to the object.

Abstract: A system for vibration-driven sensing may include a wearable dimensioned to be donned by a user of an artificial reality system. The system may also include a vibration sensor that is incorporated into the wearable and generates an electrical response that corresponds to a vibration detected at the wearable. The system may further include at least one processing device communicatively coupled to the vibration sensor. The processing device may determine, based at least in part on the electrical response generated by the vibration sensor, that the user has made a specific gesture with at least one body part. In response to this determination, the processing device may generate an input command for the artificial reality system based at least in part on the specific gesture made by the user. Various other systems and methods are also disclosed.

Abstract: Techniques and systems are disclosed for implementing a brain-computer interface. In one aspect, a system for implementing a brain-computer interface includes a stimulator to provide at least one stimulus to a user to elicit at least one electroencephalogram (EEG) signal from the user. An EEG acquisition unit is in communication with the user to receive and record the at least one EEG signal elicited from the user. Additionally, a data processing unit is in wireless communication with the EEG acquisition unit to receive and process the recorded at least one EEG signal to perform at least one of: sending a feedback signal to the user, or executing an operation on the data processing unit.