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Three-dimensional ring electrode arrays can provide means for highly-parallelized nanoparticle-impact electrochemistry within bulk solution.

Virtual reality environments offer great opportunities to study the performance of brain-computer interfaces (BCIs) in real-world contexts. As real-world stimuli are typically multimodal, their neuronal integration elicits complex response patterns. To investigate the effect of additional auditory cues on the processing of visual information, we used virtual reality to mimic safety-related events in an industrial environment while we concomitantly recorded electroencephalography (EEG) signals. We simulated a box traveling on a conveyor belt system where two types of stimuli – an exploding and a burning box – interrupt regular operation. The recordings from 16 subjects were divided into two subsets, a visual-only and an audio-visual experiment. In the visual-only experiment, the response patterns for both stimuli elicited a similar pattern – a visual evoked potential (VEP) followed by an event-related potential (ERP) over the occipital-parietal lobe. Moreover, we found the perceived severity of the event to be reflected in the signal amplitude. Interestingly, the additional auditory cues had a twofold effect on the previous findings: The P1 component was significantly suppressed in the case of the exploding box stimulus, whereas the N2c showed an enhancement for the burning box stimulus. This result highlights the impact of multisensory integration on the performance of realistic BCI applications. Indeed, we observed alterations in the offline classification accuracy for a detection task based on a mixed feature extraction (variance, power spectral density, and discrete wavelet transform) and a support vector machine classifier. In the case of the explosion, the accuracy slightly decreased by –1.64% p. in an audio-visual experiment compared to the visual-only. Contrarily, the classification accuracy for the burning box increased by 5.58% p. when additional auditory cues were present. Hence, we conclude, that especially in challenging detection tasks, it is favorable to consider the potential of multisensory integration when BCIs are supposed to operate under (multimodal) real-world conditions.

During the recent SARS-CoV-2 pandemic, lateral flow assays (LFAs) have written an indescribable story of success, as they provide means for decentralized, low-cost, and easy-to-use testing. However, LFAs in their most common form support only qualitative results and their sensitivity and limit of detection is significantly limited by the colorimetric readout method. In contrast, single-impact electrochemistry offers the possibility to quantify species beyond picomolar concentrations by recording individual species collisions with a biased microelectrode. Within this work, we investigate the integration of stochastic sensing into a LFA-architecture by combining a wax-patterned microchannel with a microelectrode array in order to detect silver nanoparticles by their oxidative dissolution. Here, we demonstrate the possibility to resolve individual nanoparticle collisions in a paper-based microchannel using a simplified reference-on-chip setup. Furthermore, we simulated a lateral-flow sensor, by flushing previously dried silver nanoparticles towards the electrode array, where the particles are subsequently detected. This proof-of-principle illustrates that single-impact electrochemistry might be a promising technique to extend the capability of LFAs. Especially, the integration of functionalized nanoparticle labels could enable the rapid and on-site detection of very dilute species with exceptional sensitivity.