Measurement system for object detection based on multielectrode capacitive sensor

The problem of detecting objects, people and events is encountered in different forms in many application areas. In this paper we investigate the applicability of multielectrode capacitive sensors for monitoring the volume of interest by analyzing the disturbances in electrical field due to the influence of external objects. Capacitive sensors are particularly interesting as a low cost solution with minimum privacy issue concerns. The goal of this research was to characterize the performance of modern capacitance-to-digital converter (CDC) PicoCap PCap02 integrated circuit for detecting various types of objects in a multielectrode system configuration, with human detection as an example application. We present an analysis of an appropriate electrode geometry, propose a custom-designed data acquisition system which complies to the required capacitance measurement range and resolution, discuss sources of measurement errors and methods for minimization of their influence, and elaborate the applicability of the method beyond the simple object detection, by investigating the possibility of object class discrimination from acquired data.