A Hardware-Based Configurable Algorithm for Eye Blink Signal Detection Using a Single-Channel BCI Headset.

Eye blink artifacts in electroencephalographic (EEG) signals have been used in multiple applications as an effective method for human-computer interaction. Hence, an effective and low-cost blinking detection method would be an invaluable aid for the development of this technology. A configurable hardware algorithm, described using hardware description language, for eye blink detection based on EEG signals from a one-channel brain-computer interface (BCI) headset was developed and implemented, showing better performance in terms of effectiveness and detection time than manufacturer-provided software.

Controlling a Mouse Pointer with a Single-Channel EEG Sensor.

(1) Goals: The purpose of this study was to analyze the feasibility of using the information obtained from a one-channel electro-encephalography (EEG) signal to control a mouse pointer. We used a low-cost headset, with one dry sensor placed at the FP1 position, to steer a mouse pointer and make selections through a combination of the user's attention level with the detection of voluntary blinks. There are two types of cursor movements: spinning and linear displacement. A sequence of blinks allows for switching between these movement types, while the attention level modulates the cursor's speed. The influence of the attention level on performance was studied. Additionally, Fitts' model and the evolution of the emotional states of participants, among other trajectory indicators, were analyzed. (2) Methods: Twenty participants distributed into two groups (Attention and No-Attention) performed three runs, on different days, in which 40 targets had to be reached and selected. Target positions and distances from the cursor's initial position were chosen, providing eight different indices of difficulty (IDs). A self-assessment manikin (SAM) test and a final survey provided information about the system's usability and the emotions of participants during the experiment. (3) Results: The performance was similar to some brain-computer interface (BCI) solutions found in the literature, with an averaged information transfer rate (ITR) of 7 bits/min. Concerning the cursor navigation, some trajectory indicators showed our proposed approach to be as good as common pointing devices, such as joysticks, trackballs, and so on. Only one of the 20 participants reported difficulty in managing the cursor and, according to the tests, most of them assessed the experience positively. Movement times and hit rates were significantly better for participants belonging to the attention group. (4) Conclusions: The proposed approach is a feasible low-cost solution to manage a mouse pointer.

A Smart Sensor for Defending against Clock Glitching Attacks on the I2C Protocol in Robotic Applications.

This paper presents a study about hardware attacking and clock signal vulnerability. It considers a particular type of attack on the clock signal in the I2C protocol, and proposes the design of a new sensor for detecting and defending against this type of perturbation. The analysis of the attack and the defense is validated by means of a configurable experimental platform that emulates a differential drive robot. A set of experimental results confirm the interest of the studied vulnerabilities and the efficiency of the proposed sensor in defending against this type of situation.

Design and implementation of a new real-time frequency sensor used as hardware countermeasure.

A new digital countermeasure against attacks related to the clock frequency is presented. This countermeasure, known as frequency sensor, consists of a local oscillator, a transition detector, a measurement element and an output block. The countermeasure has been designed using a full-custom technique implemented in an Application-Specific Integrated Circuit (ASIC), and the implementation has been verified and characterized with an integrated design using a 0.35 mm standard Complementary Metal Oxide Semiconductor (CMOS) technology (Very Large Scale Implementation-VLSI implementation). The proposed solution is configurable in resolution time and allowed range of period, achieving a minimum resolution time of only 1.91 ns and an initialization time of 5.84 ns. The proposed VLSI implementation shows better results than other solutions, such as digital ones based on semi-custom techniques and analog ones based on band pass filters, all design parameters considered. Finally, a counter has been used to verify the good performance of the countermeasure in avoiding the success of an attack.