In this paper we present some custom designed filters for real-time motioncapture applications. Our target application is so-called motion controllers,i.e. systems that interpret hand motion for musical interaction. In earlierresearch we found effective methods to design nearly optimal filters forreal-time applications. However, to be able to design suitable filters for ourtarget application, it is necessary to establish the typical frequency contentof the motion capture data we want to filter. This will again allow us todetermine a reasonable cutoff frequency for the filters. We have thereforeconducted an experiment in which we recorded the hand motion of 20 subjects.The frequency spectra of these data together with a method similar to theresidual analysis method were then used to determine reasonable cutofffrequencies. Based on this experiment, we propose three cutoff frequencies fordifferent scenarios and filtering needs: 5, 10 and 15 Hz, which corresponds toheavy, medium and light filtering respectively. Finally, we propose a range ofreal-time filters applicable to motion controllers. In particular, low-passfilters and low-pass differentiators of degrees one and two, which in ourexperience are the most useful filters for our target application.