Abstract: A personal electronic device is provided with a feature of intelligently adjusting a sampling rate of sensors, such as barometers. Before acquiring a measurement from the sensor, the device checks other hardware for conditions that could introduce noise into the measurement. If the device does not determine that excessive noise is likely after checking the other hardware, the device proceeds to acquire the measurement from the sensor. Otherwise, the device delays the measurement. At the end of the delay, the device may check the other hardware again before acquiring the measurement from the sensor.

Abstract: A computer-implemented method for assessing a fall risk of a user is provided. The computer-implemented method includes obtaining data indicative of the user engaging in a fall risk activity. The computer-implemented method includes adjusting a fall detection threshold of a wearable computing device worn by the user based, at least in part, on the data indicative of the user engaging in the fall risk activity. The method includes providing a notification indicative of the user being at risk of falling due, at least in part, to the user engaging in the fall risk activity.

Abstract: A personal electronic device is provided with a feature of intelligently adjusting a sampling rate of sensors, such as barometers. Before acquiring a measurement from the sensor, the device checks other hardware for conditions that could introduce noise into the measurement. If the device does not determine that excessive noise is likely after checking the other hardware, the device proceeds to acquire the measurement from the sensor. Otherwise, the device delays the measurement. At the end of the delay, the device may check the other hardware again before acquiring the measurement from the sensor.

Abstract: Systems and methods for audio signal enhancement facilitated using video data are provided. In one example, a method includes receiving a multi-channel audio signal including audio inputs detected by a plurality of audio input devices. The method further includes receiving an image captured by a video input device. The method further includes determining a first signal based at least in part on the image. The first signal is indicative of a likelihood associated with a target audio source. The method further includes determining a second signal based at least in part on the multi-channel audio signal and the first signal. The second signal is indicative of a likelihood associated with an audio component attributed to the target audio source. The method further includes processing the multi-channel audio signal based at least in part on the second signal to generate an output audio signal.

Abstract: Systems and methods for audio signal enhancement facilitated using video data are provided. In one example, a method includes receiving a multi-channel audio signal including audio inputs detected by a plurality of audio input devices. The method further includes receiving an image captured by a video input device. The method further includes determining a first signal based at least in part on the image. The first signal is indicative of a likelihood associated with a target audio source. The method further includes determining a second signal based at least in part on the multi-channel audio signal and the first signal. The second signal is indicative of a likelihood associated with an audio component attributed to the target audio source. The method further includes processing the multi-channel audio signal based at least in part on the second signal to generate an output audio signal.

Abstract: A system and method for performing spoof detection are disclosed. The method includes: receiving an input image of a biometric; generating a first filtered image by applying a first convolution to the input image based on a first convolution kernel; generating a second filtered image by applying a second convolution to the input image based on a second convolution kernel; computing a gradient residual image by subtracting, for each pixel location of the first and second filtered images, a pixel value in the second filtered image from a corresponding pixel value in the first filtered image; applying a density estimation procedure to the gradient residual image to identify areas of varied density; and, determining whether the input image is a replica of the biometric based on results of the density estimation procedure.

Abstract: A system and method for performing spoof detection are disclosed. The method includes: receiving an input image of a biometric; generating a first filtered image by applying a first convolution to the input image based on a first convolution kernel; generating a second filtered image by applying a second convolution to the input image based on a second convolution kernel; computing a gradient residual image by subtracting, for each pixel location of the first and second filtered images, a pixel value in the second filtered image from a corresponding pixel value in the first filtered image; applying a density estimation procedure to the gradient residual image to identify areas of varied density; and, determining whether the input image is a replica of the biometric based on results of the density estimation procedure.