Sebastian Madgwick

TL;DR: This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications, applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity sensor arrays that also include tri- axis magnetometers.

TL;DR: A novel magnetic angular rate gravity sensor fusion algorithm for inertial measurement that fuses inertial (movement) and mechanomyography (MMG) muscle sensing to control robot arm movement and grasp simultaneously, demonstrating algorithm efficacy and capacity to interface with other physiological sensors.

TL;DR: A new algorithm, an extended complementary filter (ECF), to derive 3-D rigid body orientation from inertial sensing suites addressing these challenges, and combines computational efficiency of classic complementary filters with improved accuracy compared to popular optimization filters.

TL;DR: In this article, two schemes of measuring the linear and angular kinematics of a rigid body using a kinematically redundant array of triple-axis accelerometers with potential applications in biomechanics are presented.

TL;DR: A toolbox of gestural control mechanisms which are available when the input sensing apparatus is a pair of data gloves fitted with orientation sensors, enabling a flexible range of mappings to be explored and modified easily is presented.