Abstract: This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor and/or a movement sensor produces a context of a user equipment. The techniques and systems enable the user equipment to recognize contexts when a radar system can be unreliable and should not be used for gesture-recognition, enabling the user equipment to automatically disable or “gate” the output from the radar system according to context. The user equipment prevents the radar system from transitioning to a high-power state to perform gesture-recognition in contexts where radar data detected by the radar system is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Abstract: Techniques and devices for radar-based gesture determination at long ranges are described in this document. The techniques described herein enable a computing device to detect and recognize gestures at long-range extents of up to eight meters. The computing device of this disclosure does not require the user to perform a gestural command at a specific location, in a specific orientation, contingent upon a wake-up trigger, or at a specific time, enabling the user to freely provide commands whenever and wherever is most convenient. This continual recognition of gestures may be enabled by a machine-learned model, generation of augmented data, and inclusion of negative data.

Abstract: A system of multiple radar-enabled computing devices, along with related techniques, are described in this document. These techniques are employed with this system to coordinate information and operations across multiple radar-enabled computing devices to create a seamless experience. In particular, each computing device of the computing system may have access to stored radar-signal characteristics that enable detection and distinction of users and detection and recognition of gestures. Computing devices may coordinate in-progress operations to provide continuity across multiple devices. When positioned in different locations, each device may also learn over time users, gestures, and versions of gestures associated with that location to anticipate them in the future.

Abstract: Various arrangements for performing ballistocardiography using a mobile device are presented. A radar integrated circuit of a mobile device may emit frequency-modulated continuous-wave (FMCW) radar. Reflected radio waves based on the FMCW radar being reflected off objects may be received and used to create a raw radar waterfall. The raw radar waterfall may be analyzed to create a ballistocardiography waveform. Data based on the ballistocardiography waveform may be output, such as to a machine-learning application installed on the mobile device.

Abstract: An interactive cord can include a plurality of non-conductive lines and a plurality of conductive lines arranged together in a first longitudinal portion to form a touch-sensitive area within a first longitudinal portion of the interactive cord. A non-touch-sensitive area can be formed in a second longitudinal portion such in which the plurality of conductive lines is not exposed along an outer surface of the outer layer. The plurality of conductive lines can be arranged together with the one or more of the plurality of non-conductive lines within a third longitudinal portion. The second longitudinal portion can be arranged between the first longitudinal portion and the third longitudinal portion with respect to a longitudinal direction of the interactive cord. The third longitudinal portion can be open along the longitudinal direction to form a pair longitudinal edges of the outer layer that extend in the longitudinal direction of the interactive cord.

Abstract: This document describes techniques for radio frequency (RF) based micro-motion tracking. These techniques enable even millimeter-scale hand motions to be tracked. To do so, radar signals are used from radar systems that, with conventional techniques, would only permit resolutions of a centimeter or more.

Abstract: The present disclosure is directed to servicing audiences based on object preferences displayed by the audience. The method includes receiving, by a first party computing system, a user communication from a user device associated with a user. The user communication includes a sensor identifier and a user identifier. The sensor identifier corresponds to a physical device associated with at least one item. The method include determining a user-item association based, at least in part, on the sensor identifier and the user identifier. The method includes determining an item interest level for the at least one item based, at least in part, on the user-item association. And, the method includes initiating an action based, at least in part, on the item interest level.

Abstract: The present disclosure is directed to servicing mobile devices at a point of interest. The method includes receiving a plurality of beacon broadcasts with beacon identifiers corresponding to first party beacons within a physical location associated with a merchant. The method includes detecting a triggering event associated with at least one of the one or more beacon identifiers. The method includes generating a user communication for a first party computing system associated with the merchant. The user communication includes data indicative of the at least one beacon identifier. The method includes receiving a first party advertising communication indicative of a first party item associated with the at least one beacon identifier. In response to the first party advertising communication, the method includes providing, for display, data indicative of the first party item associated with the at least one beacon identifier.

Abstract: The present disclosure is directed to inferring user intent based on physical signals. The method includes receiving physical information associated with a first party user and a physical location associated with a merchant. The physical information is indicative of a location of the first party user relative to one or more of a plurality of first party items associated with the merchant. The method includes determining an item interest level for at least one first party item of the plurality of first party items based, at least in part, on the physical information. The method includes initiating a presentation of a content item to the first party user via a user device associated with the first party user based, at least in part, on the item interest level. The content item includes information for the at least one first party item.

Abstract: The present disclosure is directed to generating insight based on physical signals. The method includes receiving contextual data associated with a first party user and at least one item. The contextual data is indicative of a physical interaction between the first party user and the at least one item. The physical interaction, for example, can include an approaching action, a picking up action, or any other action between a first party user and an item in the physical world. The method includes determining an item interest level for the at least one item based, at least in part, on the contextual data. And, the method includes initiating a presentation of a content item to the user via a user device associated with the user based, at least in part, on the item interest level for the at least one item. The content item includes information for the at least one item.

Abstract: Techniques and apparatuses are described that implement a smart-device-based radar system capable of determining characteristics of objects external to a vehicle, occupants within a vehicle, and objects proximal to an open-air vehicle. In particular, the system enables a smart device to perform many vehicle operations such as collision avoidance, occupant detection, and parking assistance in vehicle and open-air vehicle environments without integrated radar technology. By using a smart device to perform such actions, existing vehicles and open-air vehicles without integrated radar functionality may be able to leverage radar-based vehicle operations.

Abstract: This application is directed to an integrated multimodal neural network driven by a natural language prompt. A computer system obtains sensor data from a plurality of sensor devices disposed in a physical environment during a time duration. One or more information items are generated to characterize one or more signature events detected within the time duration in the sensor data. The computer system obtains a natural language prompt. In response to the natural language prompt, the computer system applies a large behavior model (e.g., a large language model, a data processing model) to process the one or more information items and the natural language prompt jointly and generate a multimodal output (e.g., textual statements, software code, an image or video, an information dashboard having a predefined format, a user interface, and a heatmap). The multimodal output associated with the sensor data is represented.

Abstract: This document describes techniques and devices for a radar recognition-aided search. Through use of a radar-based recognition system, gestures made by, and physiological information about, persons can be determined. In the case of physiological information, the techniques can use this information to refine a search. For example, if a person requests a search for a coffee shop, the techniques may refine the search to coffee shops in the direction that the person is walking. In the case of a gesture, the techniques may refine or base a search solely on the gesture. Thus, a search for information about a store, car, or tree can be made responsive to a gesture pointing at the store, car, or tree with or without explicit entry of a search query.

Abstract: This application is directed to integrated multimodal neural networks. A computer system obtains sensor data from a plurality of sensor devices during a time duration, and the plurality of sensor devices include at least two distinct senor types and are disposed in a physical environment. One or more signature events are detected in the sensor data, and one or more information items are generated to characterize the one or more signature events detected in the sensor data, independently of the sensor types of the sensor devices. A large behavior model is applied to process the one or more information items and generate a multimodal output associated with the sensor data. The multimodal output describes the signature events associated with the sensor data in one of a plurality of predefined output modalities. The multimodal output is presented according to the one of the plurality of predefined output modalities.

Abstract: This application is directed to compressing sensor data. A computer system obtains the sensor data from a plurality of sensor devices disposed in a physical environment during a time duration, and each sensor device corresponds to a temporal sequence of respective sensor samples. For each of the plurality of sensor devices, the temporal sequence of respective sensor samples is processed to generate an ordered sequence of respective sensor data features defining a respective parametric representation of the temporal sequence of respective sensor samples, independently of a sensor type of the respective sensor device. The computer system detects one or more signature events within the time duration based on the respective parametric representations of the plurality of sensor devices, and generates one or more information items characterizing the one or more signature events detected in the sensor data.

Abstract: Techniques and apparatuses are described that implement a smart-device-based radar system capable of performing location tagging. The radar system has sufficient spatial resolution to recognize different external environments associated with different locations (e.g., recognize different rooms or different locations within a same room). Using the radar system, the smart device can achieve spatial awareness and automatically activate user-programmed applications or settings associated with the different locations. In this way, the radar system enables the smart device to provide a location-specific shortcut for various applications or settings. With the location-specific shortcut, the smart device can improve the user's experience and reduce the need to repeatedly navigate cumbersome interfaces.

Abstract: This document describes techniques and devices for a radar recognition-aided search. Through use of a radar-based recognition system, gestures made by, and physiological information about, persons can be determined. In the case of physiological information, the techniques can use this information to refine a search. For example, if a person requests a search for a coffee shop, the techniques may refine the search to coffee shops in the direction that the person is walking. In the case of a gesture, the techniques may refine or base a search solely on the gesture. Thus, a search for information about a store, car, or tree can be made responsive to a gesture pointing at the store, car, or tree with or without explicit entry of a search query.

Abstract: Techniques are described herein that enable advanced gaming and virtual reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or submillimeter scale, for user control actions even when those actions are optically occluded or obscured.

Abstract: This document describes techniques and systems for radar-based gesture-recognition with context-sensitive gating and other context-sensitive controls. Sensor data from a proximity sensor and/or a movement sensor produces a context of a user equipment. The techniques and systems enable the user equipment to recognize contexts when a radar system can be unreliable and should not be used for gesture-recognition, enabling the user equipment to automatically disable or “gate” the output from the radar system according to context. The user equipment prevents the radar system from transitioning to a high-power state to perform gesture-recognition in contexts where radar data detected by the radar system is likely due to unintentional input. By so doing, the techniques conserve power, improve accuracy, or reduce latency relative to many common techniques and systems for radar-based gesture-recognition.

Abstract: This document describes apparatuses and techniques for radar-enabled sensor fusion. In some aspects, a radar field is provided and reflection signals that correspond to a target in the radar field are received. The reflection signals are transformed to provide radar data, from which a radar feature indicating a physical characteristic of the target is extracted. Based on the radar features, a sensor is activated to provide supplemental sensor data associated with the physical characteristic. The radar feature is then augmented with the supplemental sensor data to enhance the radar feature, such as by increasing an accuracy or resolution of the radar feature. By so doing, performance of sensor-based applications, which rely on the enhanced radar features, can be improved.