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: A wireless charging system comprises at least one wireless power transmitter at a fixed location, at least two wireless communication beacons in proximity and at known locations relative to the wireless power transmitter, and a portable electronic device in proximity to the wireless power transmitter. The portable electronic device comprises a wireless power receiver connected to charge a battery through a tunable power electronic circuit, a wireless communication receiver, a 3-axis accelerometer, a 3-axis magnetometer, a 3-axis gyroscope, and a controller configured to determine the position and orientation of the wireless power receiver with respect to the wireless power transmitter and tune the tunable power electronic circuit based on the determined orientation.

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.