Abstract: Techniques and apparatuses are described that perform audioplethysmography and motion-sensing data fusion. Fusing motion-sensing data with audioplethysmography expands the situations in which audioplethysmography can operate. In one aspect, audioplethysmography and motion-sensing data fusion can be used for motion-artifact filtering. With motion-artifact filtering, noise caused by motion of a user can be attenuated to improve sensitivity and accuracy for audioplethysmography. This performance improvement expands the ability of audioplethysmography to support use cases during situations in which the user engages in an activity. In another aspect, audioplethysmography and motion-sensing data fusion can expand a functionality of a hearable to include activity detection and/or activity classification.

Abstract: A tactile sensing system of a robot may include: a plurality of piezoelectric elements disposed at an object, and including a transmission (TX) piezoelectric element and a reception (RX) piezoelectric element; and at least one processor configured to: control the TX piezoelectric element to generate an acoustic wave having a chirp spread spectrum (CSS) at every preset time interval, along a surface of the object; receive, via the RX piezoelectric element, an acoustic wave signal corresponding to the generated acoustic wave; select frequency bands from a plurality of frequency bands of the acoustic wave signal; and estimate a location of a touch input on the surface of the object by inputting the acoustic wave signal of the selected frequency bands into a neural network configured to provide a touch prediction score for each of a plurality of predetermined locations on the surface of the object.

Abstract: Techniques and apparatuses are described that perform respiration rate sensing. Provided according to one or more preferred embodiments is a hearable, such as an earbud, that is capable of performing a novel physiological monitoring process termed herein audioplethysmography, an active acoustic method capable of sensing subtle physiologically-related changes observable at a user's outer and middle ear. Instead of relying on other auxiliary sensors, such as optical or electrical sensors, audioplethysmography involves transmitting and receiving acoustic signals to monitor a user's respiration rate. In addition to being relatively unobtrusive, some hearables can be configured to support audioplethysmography without the need for additional hardware. As such, the size, cost, and power usage of the hearable can help make health monitoring accessible to a larger group of people and improve the user experience with hearables.

Abstract: Techniques and apparatuses are described that perform audioplethysmography calibration. Provided according to one or more preferred embodiments is a hearable, such as an earbud, that is capable of performing a novel physiological monitoring process termed herein audioplethysmography, an active acoustic method capable of sensing subtle physiologically-related changes observable at a user's outer and middle ear. The hearable can utilize audioplethysmography to monitor a user's biometrics, recognize facial behaviors, and/or sense an environment using acoustic signals. The techniques for audioplethysmography calibration enable the hearable to dynamically select frequencies that improve the performance of audioplethysmography. With audioplethysmography calibration, the hearable may utilize different frequencies for different ears and these frequencies may change over time.

Abstract: A tactile sensing system of a robot may include: a plurality of piezoelectric elements disposed at an object, and including a transmission (TX) piezoelectric element and a reception (RX) piezoelectric element; and at least one processor configured to: control the TX piezoelectric element to generate an acoustic wave having a chirp spread spectrum (CSS) at every preset time interval, along a surface of the object; receive, via the RX piezoelectric element, an acoustic wave signal corresponding to the generated acoustic wave; select frequency bands from a plurality of frequency bands of the acoustic wave signal; and estimate a location of a touch input on the surface of the object by inputting the acoustic wave signal of the selected frequency bands into a neural network configured to provide a touch prediction score for each of a plurality of predetermined locations on the surface of the object.

Abstract: Techniques and apparatuses are described that perform heart rate variability detection using a hearable. A hearable, such as an earbud, is capable of performing a novel physiological monitoring process termed herein audioplethysmography, which is an active acoustic method capable of sensing subtle physiologically-related changes observable at a user's outer and middle ear. Instead of relying on other auxiliary sensors, such as optical or electrical sensors, audioplethysmography involves transmitting and receiving acoustic signals to monitor a user's biometrics, including heart rate variability and/or blood pressure. In addition to being relatively unobtrusive, some hearables can be configured to support audioplethysmography without the need for additional hardware. As such, the size, cost, and power usage of the hearable can help make health monitoring accessible to a larger group of people and improve the user experience with hearables.

Abstract: Techniques and apparatuses are described that perform voice activity detection using active acoustic sensing. By transmitting and receiving acoustic signals, a hearable can recognize changes in an acoustic circuit to perform voice activity detection. With active acoustic sensing, the hearable can detect a vocalization made by a user in a noisy and/or loud environment. As such, the hearable can support a voice user interface (VUI) by providing an indication of when the user is speaking. The hearable can also support multi-factor voice authentication to enhance security and provide robust protection from voice attacks. In addition to being relatively unobtrusive, some hearables can be configured to support voice activity detection using active acoustic sensing without the need for additional hardware.

Abstract: An apparatus for estimating a proximity direction of an obstacle includes an acoustic transmitter attached to a surface of the apparatus; a first acoustic receiver spaced apart from the surface of the apparatus; a second acoustic receiver spaced apart from the surface of the apparatus; and at least one processor configured to: control the acoustic transmitter to generate an acoustic wave along the surface; obtain first and second proximity direction signals based on first and second acoustic wave signals corresponding to the generated acoustic wave; and estimate a proximity direction of the obstacle with respect to the apparatus based on the first and second proximity direction signals.

Abstract: Various embodiments comprise systems, methods, architectures, mechanisms and apparatus providing a sensing platform wherein one or more headphone drivers are used as a versatile sensor to receive excitation signals therefrom indicative of direct or indirect pressures associated with the ear canal acoustically cooperating with the diaphragms operatively coupled to the drivers.

Abstract: A method of collision localization on a robotic device includes obtaining audio signals from a plurality of acoustic sensors spaced apart along the robotic device; identifying, based on a collision being detected, a strongest audio signal; identifying a primary onset time for an acoustic sensor producing the strongest audio signal, the primary onset time being a time at which waves propagating from the collision reach the acoustic sensor producing the strongest audio signal; generating a virtual onset time set, by shifting a calibration manifold, based on the identified primary onset time, the calibration manifold representing relative onset times from evenly spaced marker locations on the robotic device to the plurality of acoustic sensors; determining scores for the marker locations based a standard deviation of elements in the virtual onset time set; and estimating a location of the collision based on a highest score of the determined scores.

Abstract: A pose of a person is estimated using an image and audio impulse responses. The image represents a 2D scene including the person. The audio impulse responses are obtained with the present absent and present in an environment. The pose is reconstructed based on the image and the one or more audio impulse responses. The pose is a metric scale human pose.

Abstract: A tactile sensing system of a robot may include: a plurality of piezoelectric elements disposed at an object, and including a transmission (TX) piezoelectric element and a reception (RX) piezoelectric element; and at least one processor configured to: control the TX piezoelectric element to generate an acoustic wave having a chirp spread spectrum (CSS) at every preset time interval, along a surface of the object; receive, via the RX piezoelectric element, an acoustic wave signal corresponding to the generated acoustic wave; select frequency bands from a plurality of frequency bands of the acoustic wave signal; and estimate a location of a touch input on the surface of the object by inputting the acoustic wave signal of the selected frequency bands into a neural network configured to provide a touch prediction score for each of a plurality of predetermined locations on the surface of the object.

Abstract: Various embodiments comprise systems, methods, architectures, mechanisms or apparatus for wireless secret communication with a device.

Abstract: Various embodiments comprise systems, methods, architectures, mechanisms or apparatus providing far-field wireless charging of implanted medical devices, Internet of Things (IoT) and the like via a leader radio configured for receiving spread spectrum (SS) modulated radio waves from a plurality of slave radios within an area including the leader radio and a target device, for receiving from the target device backscatter radio energy associated with the (SS) modulated radio waves, and for generating slave radio control signals; the leader radio, in a charging mode of operation, being configured for determining changes in received power associated with backscatter radio energy received from the target device and responsively transmitting control signals toward the slave radios configured to cause the slave radios to modify respective radio wave transmission times such that slave radio wave transmissions are substantially phase aligned when received at the target device.

Abstract: An apparatus for collision avoidance by surface proximity detection includes a plurality of piezoelectric elements disposed adjacent to a surface of an object, a memory storing instructions, and at least one processor configured to execute the instructions to control a first one among the piezoelectric elements to generate an acoustic wave along the surface of the object, and receive, via a second one among the piezoelectric elements, an acoustic wave signal corresponding to the generated acoustic wave. The at least one processor is further configured to execute the instructions to filter the received acoustic wave signal, using a band-pass filter for reducing noise of the received acoustic wave signal, obtain a proximity signal for proximity detection, from the filtered acoustic wave signal, using a linear time-invariant filter, and detect whether an obstacle is proximate to the surface of the object by inputting the obtained proximity signal into a neural network.

Abstract: A method of collision localization on a robotic device includes obtaining audio signals from a plurality of acoustic sensors spaced apart along the robotic device; identifying, based on a collision being detected, a strongest audio signal; identifying a primary onset time for an acoustic sensor producing the strongest audio signal, the primary onset time being a time at which waves propagating from the collision reach the acoustic sensor producing the strongest audio signal; generating a virtual onset time set, by shifting a calibration manifold, based on the identified primary onset time, the calibration manifold representing relative onset times from evenly spaced marker locations on the robotic device to the plurality of acoustic sensors; determining scores for the marker locations based a standard deviation of elements in the virtual onset time set; and estimating a location of the collision based on a highest score of the determined scores.

Abstract: Various embodiments comprise systems, methods, architectures, mechanisms or apparatus for wireless secret communication with a device.