Aim: Describe the ability to identify the movement performed by a patient in bed using four pressure sensors and assess how an algorithm describes the movements of the person in bed using data from the sensors to develop continuous assessment of pressure ulcers risk. Method: Data were collected through a standardized videotaped session in which each subject performed a series of movements/ positions in bed (figure 1). Data labeling was manually performed by comparing them with the images. Results / Discussion: Data analysis has not yet been completed for all the data collected, but that of the first 128 volunteers allows the description of some preliminary results to confirm the feasibility of the system developed and the labeling of signals coming from the sensors that were able to identify the subject's movements. The study conducted so far has demonstrated the feasibility of the system of data collection allowing us to confirm the usefulness and reliability of the data stream transmitted by the bed sensor system, the proper labeling of the originated data, and a proper implementation of the data collection scheme that has so far been used, enabling the development of an automated data labeling system (neural network) that will enable the automation of the active mobilization monitoring system of the bed-occupant. Conclusion: There are many benefits that the tool could bring to clinical practice, optimizing preventive interventions and individualizing nursing care, but completion of the study and a subsequent trial in the end-use setting by enrolling subjects from a population at risk of pressure ulcers is needed to confirm this hypothesis.