The MTi data sheets mention the typical performance, in some case also the max error, of the orientation for different conditions. These conditions are marked Static or Dynamic. This article describes the differences between Static and Dynamic.
How MEMS inertial sensors are used in the sensor fusion algorithms
Data from the MEMS inertial sensors (accelerometers and gyroscopes) are combined in order to provide 3D orientation. Simplified does this mean that the gyroscope signals are integrated and the resulting orientation is then corrected by the accelerometers that use gravity as a reference (see below).
This is not the complete story, as Filter setting profiles provide assumptions on how much of the correction step should be taken into account. Filter profiles that assume a lot of dynamics will use gyroscope integration for a longer time and will regard the output of the accelerometers as less accurate or 'safe-to-use'.
Static versus dynamic in the datasheet
So what does static and dynamic mean? Static means that gravity can be fully trusted. This is the case when only gravity is measured, e.g. when the MTi is laying still. But gravity is also observable when the MTi is moving without external accelerations, e.g. when moving in a straight line in a vehicle.
Dynamic is not as black and white, as some dynamics may not seem dynamic but are really difficult for the Xsens Kalman Filter. For example, when an airplane makes a 360 deg banking turn, there are prolonged centripetal accelerations. This does may not seem that dynamic, but at some point the gravity + centripetal acceleration is assumed to be gravity only, adjusting the accelerometer bias. For these cases, Xsens has GNSS/INS products , but it shows that there is not a real distinction between dynamic and static.
All dynamic and static specifications are based on actual trials in cars in city traffic, airplanes (general aviation, 4-seat Cessna's), indoor-handheld (as if someone was holding a phone and walking) and static.