The electrocardiogram (ECG) is becoming a promising technology for biometric human identification. Usually ECG is used for health measurements and this is useful for biometric applications to state that the subject under analysis is live. But an individual identification shouldn't require a classical ECG clinical analysis where several contacts are applied to the person to be identified. In literature, ECG biometric recognition is usually studied for the recognition of a subject within a group of known subjects. In this paper, a new approach is considered. The aim of our embedded wearable controller is to authorize a subject or to reject him, labeling as an intruder unknown to the system. The study used 40 healthy subjects: two authorized and 38 intruders. A one-lead ECG trace has been recorded from the wrists of subjects, features have been extracted using a combination of Autocorrelation and Discrete Cosine Transform (AC/DCT) and then classified using a Multilayer Perceptron. Results show that intruder recognition can be performed with a success rate equal to 100%.

Abstract. The memristor (a memory-resistor) is a fundamental twoterminal circuit element with a nonlinear relationship between the integral of the voltage and the charge. In the literature, the research interest in the development of new memristive systems is growing, due to the potential applications as analog memories or as synapses in neuromorphic systems. In this paper, the possibility of using an electrostatic loudspeaker as a memristor-based system is explored. This kind of loudspeakers use a thin flat polarized diaphragm, usually consisting of a plastic sheet coated with a conductive material, between two electrically conductive plates, with a small air gap between them. When an electrostatic field is applied to the plates, a force is exerted on the charged diaphragm, and its resulting movement drives the air on either side of it. To get a memristor, the deformation of the diaphragm is here converted in a resistance value using a strain gauge attached over it. A mathematical model of the system is developed. Simulation results show that the device based on the combination of an electrostatic loudspeaker and a strain gauge has all the properties of the memristive systems.