Signal processing requirements for step detection using wrist-worn IMU

This paper studies how the accuracy of the step detection algorithm of a pedestrian dead-reckoning (PDR) system is affected by the sampling frequency and the filtering of the data gathered from a wrist-worn inertial measurement unit (IMU). On the one hand, results show that sensors sampling rate can be reduced and a similar accuracy can still be obtained, what it is very interesting for energy saving purposes. However, a low sampling frequency requires a finer tuning of the algorithm´s parameters. On the other hand, the application of a filter to the data gathered from the sensors is always recommended, in order to get some performance improvement. Different types of filters can be used in function of the value of the sampling frequency.