Optimization of memory space for long time data collection by adaptive sampling: application to a new strain sensor for hip join

In vivo measurements are necessary for the validation of a hip bone strain sensor. The memory capacity of the associated telemetry data acquisition systems is limited. In order to correctly evaluate the reliability of the sensor, long time data measurement are necessary. They may last several days and are performed with a constant sampling frequency on a sheep. The goal of our project is the optimization of the memory space. We therefore propose to adapt the sampling frequency to the variation of the collected signal, which is correlated with the sheep's walk.