Many wearable inertial systems have been used to continuously track human movement in and outside of a laboratory. The number of sensors and the complexity of the algorithms used to measure position and orientation vary according to the clinical application. To calculate changes in orientation, researchers often integrate the angular velocity. However, a relatively small error in measured angular velocity leads to large integration errors. This restricts the time of accurate measurement to a few minutes. We have combined kinematic models designed for control of robotic arms with state space methods to directly and continuously estimate the joint angles from inertial sensors. These algorithms can be applied to any combination of sensors, can easily handle malfunctions or the loss of some sensor inputs, and can be used in either a real-time or an off-line processing mode with higher accuracy.