The widespread adoption of sensor devices to monitor human activity has led to the development of numerous smart applications, particularly in the field of mental health. These applications are particularly valuable as they allow non-intrusive monitoring of motor activity. However, efficient aggregation and processing of sensor-derived data remains a challenge, requiring the development of specialized mathematical models tailored to specific domains of study. In this paper, we propose a data collection and coding model based on a grid of 12 piezoelectric sensors arranged in 3 \(\,\times \,\) 4 matrices. The properties associated with motion detection and the arithmetic that enables the collection of information are explored. The grid dimension is reduced by coding with vectors that facilitate Boolean arithmetic. Presence in different degrees, absence and error states are coded. A state diagram is proposed that represents the fluctuation in time of the different degrees of presence making it possible to differentiate between states of stress and calm in users monitored by the grid. This work includes a fuzzy model for the interpretation of the diagram states.