Imagine a future where man and machine become one on the battlefield, where soldiers direct weapon systems through a neural implant. Research advances on brain–computer interfaces (BCIs) may eventually allow such control of arms at the speed of thought. This article sketches two modes of BCI-controlled weapon systems. In Mode A (active BCI), the soldier opens fire by actively imagining that he is pushing a button with his hand. By contrast, Mode B (reactive BCI) captures neural signals evoked instantly after having spotted a target, before the operator becomes consciously aware of it. If he deems the target lawful, the brain signal is translated into a command to fire. Arguing that such man–machine collaboration transforms the operating soldier into a means of warfare, this article conducts a weapon review in line with Article 36 of Additional Protocol I (AP I) to answer the question of whether BCIs can be lawfully used to control weapons in international armed conflict. Consequently, the two set-ups are reviewed on their compliance with the customary targeting principles of international humanitarian law. Since Mode B casts doubt on the amount of control that the soldier retains over his targeting decision, the concept of meaningful human control is transposed from the debate on lethal autonomous weapon systems and applied to BCIs. It is found that reactive BCIs cannot be meaningfully controlled and thus violate the principles of distinction and proportionality. Hence, reactive BCIs are unlawful under Article 36 of AP I.

The goal of this paper is to present a new hybrid system based on the fusion of gaze data and Steady State Visual Evoked Potentials (SSVEP) not only to command a powered wheelchair, but also to account for users distraction levels (concentrated or distracted). For this purpose, a multi-layer perception neural network was set up in order to combine relevant gazing and blinking features from gaze sequence and brainwave features from occipital and parietal brain regions. The motivation behind this work is the shortages raised from the individual use of gaze-based and SSVEP-based wheelchair command techniques. The proposed framework is based on three main modules: a gaze module to select command and activate the flashing stimuli. An SSVEP module to validate the selected command. In parallel, a distraction level module estimates the intention of the user by mean of behavioral entropy and validates/inhibits the command accordingly. An experimental protocol was set up and the prototype was tested on five paraplegic subjects and compared with standard SSVEP and gaze-based systems. The results showed that the new framework performed better than conventional gaze-based and SSVEP-based systems. Navigation performance was assessed based on navigation time and obstacles collisions.

An animal's fitness is in part based on its ability to manage the inherent risks (foraging costs, predation, exposure to disease) with the benefits (resource gain, access to mates, social interactions) of activity (Abrams 1991, Altizer et al. 2003, Lima & Bednekoff 1999, Rubenstein & Hohmann 1989, Wikelski et al. 2001). Thus, understanding an animal's pattern of activity is key to understanding behavioural and ecological processes. However, while numerous laboratory methodologies are available to continuously quantify activity over long periods of time, logistical difficulties have greatly hindered activity studies of animals in the field (DeCoursey 1990).