Abstract: Training data are obtained. Each training datum includes environment characteristics obtained based on sensor data. Respective user settings corresponding to the training data are obtained. At least one respective user setting corresponds to one training datum, and a respective user setting is indicative of a user preference of at least one parameter of a hearing aid device. A machine-learning model for the hearing aid device is trained to output values for the at least one parameter. The hearing aid device is reconfigured based on an output of the machine-learning model. Reconfiguring the hearing aid device includes using current environment characteristics as an input to the machine-learning model to obtain at least one current value for the at least one parameter and configuring the hearing aid device to use at least one current value.

Abstract: Training data are obtained. Each training datum includes environment characteristics obtained based on sensor data. Respective user settings corresponding to the training data are obtained. At least one respective user setting corresponds to one training datum, and a respective user setting is indicative of a user preference of at least one parameter of a hearing aid device. A machine-learning model for the hearing aid device is trained to output values for the at least one parameter. The hearing aid device is reconfigured based on an output of the machine-learning model. Reconfiguring the hearing aid device includes using current environment characteristics as an input to the machine-learning model to obtain at least one current value for the at least one parameter and configuring the hearing aid device to use at least one current value.

Abstract: Methods for providing swimmers with performance metrics, turn detection, and stroke rate detection are disclosed.

Abstract: The present disclosure provides substantially magnetometer-free systems and methods for motion capture of a subject including 3-D localization and posture tracking by fusing inertial sensors with a localization system and a biomechanical model of the subject. Using the novel Kalman filter based fusion techniques disclosed herein, the localization data aided with the biomechanical model can eliminate the drift in inertial yaw angle estimation.

Abstract: Systems and methods are provided for estimating a walking speed of a subject. A method comprises mounting an inertial measurement unit (IMU) on a wrist of the subject, the IMU configured to generate acceleration and rate of turn signals; processing the acceleration and rate of turn signals from the IMU to generate a pitch angle and a roll angle; processing the pitch angle and the roll angle to generate a rotation matrix from a sensor frame of the IMU to a navigation frame of the subject; applying the rotation matrix to the acceleration signals and removing gravitational acceleration to generate an external acceleration signal; processing the external acceleration signal to determine a principal horizontal axis and to generate a principal component acceleration signal representing external acceleration along the principal horizontal axis; and processing the principal component acceleration signal using a regression-based method to determine an estimated walking speed of the subject.

Abstract: Systems and methods are provided for estimating a walking speed of a subject. A method comprises mounting an inertial measurement unit (IMU) on a wrist of the subject, the IMU configured to generate acceleration and rate of turn signals; processing the acceleration and rate of turn signals from the IMU to generate a pitch angle and a roll angle; processing the pitch angle and the roll angle to generate a rotation matrix from a sensor frame of the IMU to a navigation frame of the subject; applying the rotation matrix to the acceleration signals and removing gravitational acceleration to generate an external acceleration signal; processing the external acceleration signal to determine a principal horizontal axis and to generate a principal component acceleration signal representing external acceleration along the principal horizontal axis; and processing the principal component acceleration signal using a regression-based method to determine an estimated walking speed of the subject.

Abstract: Methods for providing swimmers with performance metrics, turn detection, and stroke rate detection are disclosed.

Abstract: The present disclosure provides a jump detection system for inertial measurement unit (IMU) integrated with a barometric altimeter in the same device (IMU-baro). The processor is configured to record time-series data of both a vertical component of the measured IMU-baro acceleration and the estimated vertical velocity of the IMU-baro, detect a potential jump by comparing the vertical component of the measured IMU-baro acceleration to one or more acceleration thresholds, and, validate the potential jump by comparing a difference between a maximum velocity and a minimum velocity within a vicinity of the potential jump in the time-series data of the estimated vertical velocity of the IMU-baro to a velocity threshold.

Abstract: This disclosure provides a vertical position and velocity determination system for inertial measurement unit (IMU) integrated with a barometric altimeter in the same device (IMU-baro). The system includes a rate of turn input connected to receive a measured IMU-baro rate of turn; an acceleration input connected to receive a measured IMU-baro acceleration; a barometric pressure input connected to receive a measured IMU-baro altitude; a first Kalman filter connected to the rate of turn input and to the acceleration input to estimate a roll and pitch of the IMU-baro based on the measured IMU-baro rate of turn and the measured IMU-baro acceleration; and a second Kalman filter connected to the acceleration input, to the barometric pressure input, and to the first Kalman filter.

Abstract: The present disclosure provides substantially magnetometer-free systems and methods for motion capture of a subject including 3-D localization and posture tracking by fusing inertial sensors with a localization system and a biomechanical model of the subject. Using the novel Kalman filter based fusion techniques disclosed herein, the localization data aided with the biomechanical model can eliminate the drift in inertial yaw angle estimation.

Abstract: This disclosure provides a vertical position and velocity determination system for inertial measurement unit (IMU) integrated with a barometric altimeter in the same device (IMU-baro). The system includes a rate of turn input connected to receive a measured IMU-baro rate of turn; an acceleration input connected to receive a measured IMU-baro acceleration; a barometric pressure input connected to receive a measured IMU-baro altitude; a first Kalman filter connected to the rate of turn input and to the acceleration input to estimate a roll and pitch of the IMU-baro based on the measured IMU-baro rate of turn and the measured IMU-baro acceleration; and a second Kalman filter connected to the acceleration input, to the barometric pressure input, and to the first Kalman filter.

Abstract: The present disclosure provides a jump detection system for inertial measurement unit (IMU) integrated with a barometric altimeter in the same device (IMU-baro). The processor is configured to record time-series data of both a vertical component of the measured IMU-baro acceleration and the estimated vertical velocity of the IMU-baro, detect a potential jump by comparing the vertical component of the measured IMU-baro acceleration to one or more acceleration thresholds, and, validate the potential jump by comparing a difference between a maximum velocity and a minimum velocity within a vicinity of the potential jump in the time-series data of the estimated vertical velocity of the IMU-baro to a velocity threshold.