Abstract: During an initialization of a head pose tracker for a spatial audio system, a spatial audio ambience bed is rotated about a boresight vector to align the boresight vector with a center channel of the ambience bed. The boresight is computed using source device motion data and headset motion data. The ambience bed includes the center channel and one or more other channels. An ambience bed reference frame is aligned with a horizontal plane of a headset reference frame, such that the ambience bed is horizontally level with a user's ears. A first estimated gravity direction is fixed (made constant) in the ambience bed reference frame. During head pose tracking, the ambience bed reference frame is rolled about the boresight vector to align a second estimated gravity direction in the headset reference frame with the first estimated gravity direction fixed in the ambience bed reference frame.

Abstract: Embodiments are disclosed for disabling/re-enabling head tracking for spatial audio applications. In an embodiment, a method comprises: obtaining, using one or more processors of an auxiliary device worn by a user, motion data; tracking, using the one or more processors, the user's head based at least in part on the motion data; determining, using the one or more processors, whether or not the user is walking based at least in part on the motion data; in accordance with determining that the user is walking, determining if a source device configured to deliver spatial audio to the auxiliary device is static for a specified period of time; and in accordance with determining that the user is walking and the source device is static for the specified period of time, disabling the head tracking.

Abstract: Systems and methods of analyzing a user's motion during a swimming session are described. One or more motions sensors can collect motion data of the user. A processor circuit can make motion analysis based on the motion data. The processor circuit can determine if the user's arm swing is a genuine swim stroke. The processor circuit can also determine whether the user is swimming or turning. The processor circuit can also classify the user's swim stroke style. The processor circuit can also determine the user's swim stroke phase. The processor circuit can also determine the user's stroke orbit consistency.

Abstract: Embodiments are disclosed for disabling/re-enabling head tracking for spatial audio applications. In an embodiment, a method comprises: obtaining, using one or more processors of an auxiliary device worn by a user, motion data; tracking, using the one or more processors, the user's head based at least in part on the motion data; determining, using the one or more processors, whether or not the user is walking based at least in part on the motion data; in accordance with determining that the user is walking, determining if a source device configured to deliver spatial audio to the auxiliary device is static for a specified period of time; and in accordance with determining that the user is walking and the source device is static for the specified period of time, disabling the head tracking.

Abstract: Embodiments are disclosed for adaptive audio centering for head tracking in spatial audio applications. In an embodiment, a method comprises: obtaining first motion data from an auxiliary device communicatively coupled to a source device, the source device configured to provide spatial audio content and the auxiliary device configured to playback the spatial audio content; obtaining second motion data from one or more motion sensors of the source device; determining whether the source device and auxiliary device are in a period of mutual quiescence based on the first and second motion data; in accordance with determining that the source device and the auxiliary device are in a period of mutual quiescence, re-centering the spatial audio in a three-dimensional virtual auditory space; and rendering the 3D virtual auditory space for playback on the auxiliary device.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: Embodiments are disclosed for user posture change detection for triggering re-centering of spatial audio. In an embodiment, a method comprises: obtaining source device motion data from a source device and headset motion data from a headset worn by a user; estimating a gravity vector from one of the source device or headset motion data; splitting the source device and headset motion data into vertical and horizontal planes, the vertical plane in the direction of the estimated gravity vector and the horizontal plane perpendicular to the estimated gravity vector; calculating similarity measures based on the source device motion data and headset motion data in the vertical and horizontal planes over a time window; detecting a posture change event based on the calculated similarity measures; and resetting a head tracker error after the detected user posture change event.

Abstract: In an embodiment, a method comprises: estimating a first gravity direction in a source device reference frame for a source device; estimating a second gravity direction in a headset reference frame for a headset; estimating a rotation transform from the headset frame into a face reference frame using the first and second estimated gravity directions, a rotation transform from a camera reference frame to the source device reference frame, and a rotation transform from the face reference frame to the camera reference frame; estimating a relative position and attitude using source device motion data, headset motion data and the rotation transform from the headset frame to the face reference frame; using the relative position and attitude to estimate a head pose; and using the estimated head pose to render spatial audio for playback on the headset.

Abstract: Embodiments are disclosed for user posture transition detection and classification. In an embodiment, a method comprises: obtaining, using one or more processors, motion data from a headset worn by a user; determining, using the one or more processors, one or more windows of motion data that indicate biomechanics of one or more phases of a user's postural transition; and classifying, using the one or more processors, as the user's postural transition based on the one or more windows of data.

Abstract: Embodiments are disclosed for head motion prediction for spatial audio applications. In an embodiment, a method comprises: obtaining motion data from a source device and a headset; obtaining transmission delays from a wireless stack of the source; estimating relative motion from the relative source device and headset motion data; calculating a first derivative of the relative motion data; forward predicting the estimated relative motion over the time delays using the first derivative and second derivative of relative motion; determining, using a head tracker, a head pose of the user based on the forward predicted relative motion data; and rendering, using the head pose, spatial audio for playback on the headset.

Abstract: Embodiments are disclosed for head tracking state detection based on correlated motion of a source device and a headset communicatively coupled to the source device. In an embodiment, a method comprises: obtaining, using one or more processors of a source device, source device motion data from a source device and headset motion data from a headset; determining, using the one or more processors, correlation measures using the source device motion data and the headset motion data; updating, using the one or more processors, a motion tracking state based on the determined correlation measures; and initiating head pose tracking in accordance with the updated motion tracking state.

Abstract: During an initialization of a head pose tracker for a spatial audio system, a spatial audio ambience bed is rotated about a boresight vector to align the boresight vector with a center channel of the ambience bed. The boresight is computed using source device motion data and headset motion data. The ambience bed includes the center channel and one or more other channels. An ambience bed reference frame is aligned with a horizontal plane of a headset reference frame, such that the ambience bed is horizontally level with a user's ears. A first estimated gravity direction is fixed (made constant) in the ambience bed reference frame. During head pose tracking, the ambience bed reference frame is rolled about the boresight vector to align a second estimated gravity direction in the headset reference frame with the first estimated gravity direction fixed in the ambience bed reference frame.

Abstract: Embodiments are disclosed for head dimension estimation for spatial audio applications. In an embodiment, a method comprises: obtaining, using one or more processors of an audio headset worn on a user's head, acceleration samples and rotation rate samples over a specified time window while the user rotates their head, the acceleration samples and rotation rate samples measured using motion sensors in the headset; determining a function that relates the acceleration samples to the rotation rate samples; comparing the function to a plurality of reference functions, where each reference function corresponds to a different head dimension in a nominal range of head dimensions; and estimating a dimension of the user's head based on the comparing.

Abstract: Systems and methods of analyzing a user's motion during a swimming session are described. One or more motions sensors can collect motion data of the user. A processor circuit can make motion analysis based on the motion data. The processor circuit can determine if the user's arm swing is a genuine swim stroke. The processor circuit can also determine whether the user is swimming or turning. The processor circuit can also classify the user's swim stroke style. The processor circuit can also determine the user's swim stroke phase. The processor circuit can also determine the user's stroke orbit consistency.

Abstract: Devices and related methods for the dynamic correction of spinal deformities are disclosed. The devices and methods are particularly useful for correcting an abnormal curvature of the spine. In one exemplary embodiment, a method for correcting deformity via a spinal implant that can include a polymer between or attached to a top and bottom plate, which can exist in a wedge-shaped configuration in order to apply asymmetric forces to the spinal column, is provided. The implant may be inserted between adjacent vertebrae comprising part of the abnormal curvature, thereby restoring the normal curvature of a spine.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting swimming activities, classifying user motion, detecting water submersion, and monitoring performance during swimming activities. By accurately and promptly detecting swimming activities and automatically distinguishing between different swimming stroke type performed during a swimming activity, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording swimming activities. In various embodiments, swimming activity detection techniques may improve the selectivity of motion based methods of identifying swimming activities identification by confirming motion analysis with water immersion and pressure data analysis that detects when the wearable device is submerged in water.

Abstract: Devices and related methods for the dynamic correction of spinal deformities are disclosed. The devices and methods are particularly useful for correcting an abnormal curvature of the spine. In one exemplary embodiment, a method for correcting deformity via a spinal implant that can include a polymer between or attached to a top and bottom plate, which can exist in a wedge-shaped configuration in order to apply asymmetric forces to the spinal column, is provided. The implant may be inserted between adjacent vertebrae comprising part of the abnormal curvature, thereby restoring the normal curvature of a spine.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: A method and a system for determining an energy expenditure of a user while practicing yoga are described. A heart rate sensing module can measure the user's heart rate. A temperature sensing module can measure ambient temperature. A motion sensing module can collect user's motion data. In some embodiments, a hot yoga session can be detected based on measured ambient temperature. In some embodiments, a yoga type can be detected based on the motion data. In some embodiments, an energy expenditure model can be applied based on the determined yoga type.