The current work presents the development and technical validation, in terms of accuracy and latency, of a low-cost portable device that allows identifying possible risks of falling in people when they realize spinal trunk lateral movements. The device is comprised of an Inertial Measurement Unit (IMU) located on the lower back. Measurements are processed to get meaningful parameters such as rotation angles of the back when realizing lateral movements. In order to give performance feedback while doing the test, this device includes a Microcontroller as Raspberry Pi to return visual feedback to the person. The critical system feature is the latency of the system since getting the data of a movement until showing that on the feedback screen. For that reason, before to start assessing people, we propose a technical method using the Mikrolar Hexapod Robot R3000 for validating the system developed by simulating the movement of the back and recording it with a video camera to apply an offline Motion-to-Photon Latency analysis.