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Some people with severe disabilities are confined in a state in which communication is virtually impossible, being reduced to communicating with their eyes or using sophisticated systems that translate thoughts into words. The EyeTrackers and Brain-Computer Interfaces (BCIs) are suitable systems for those people but their main drawback is their cost. More affordable devices are capable of detecting voluntary blinks and translating them into a binary signal that allows the selection, for example, of an ideogram on a communication board. We tested four different systems based on infrared, bioelectrical signals (Electro-Oculography (EOG) and Electro-Encephalography (EEG)), and video processing. The experiments were performed by people with/without disabilities and analyzed the systems' performances, usability, and method of voluntary blinking (long blinks or sequence of two short blinks). The best accuracy (99.3%) was obtained using Infrared-Oculography (IR-OG) and the worst with the EEG headset (85.9%) and there was a statistical influence of the technology on accuracy. Regarding the method of voluntary blinking, the use of long or double blinks had no statistical influence on accuracy, excluding EOG, and the time taken to perform double blinks was shorter, resulting in a potentially much faster interface. People with disabilities obtained similar values but with greater variability. The preferred technology and blinking methods were Video-Oculography (VOG) and long blinks, respectively. The several Open-Source Hardware (OSHW) devices have been developed and a new algorithm for detecting voluntary blinks has also been proposed, which outperforms most of the published papers in the reviewed literature.

A typical routine in many scientific studies consists of recording data from devices and identifying which segment of data corresponds with an experimental interval. However, many current applications have been designed to obtain and save data from one single device, and synchronizing data with the markers that delimit the test phases can be difficult. To address this issue, we have developed LSRec, which is based on Lab-Streaming Layer, a C++ library that allows data synchronization. LSRec is an easy-to-use, open-source, multi-platform, recording system developed on Java that can save data from several devices at the same time, while maintaining synchronization with the experimental phase markers. It supports three explicit sync methods: the first uses one-integer-channel input Lab-Streaming Layer streams. The others use TCP/UDP socket messages and allow any existing software that generates sync markers through TCP/UDP messages to be used under the same conditions. In LSRec, the markers are saved together with input data, facilitating the process of linking data with test stages. A prerequisite for recording software is to guarantee suitable timing performance, with no data loss and an easy user interface. These features were assessed for LSRec, with no data loss detected for 20 hours (25 sessions). We evaluated performance by measuring timestamp deviations for sync marker and input data. The sync methods exhibited an average of deviations of around −34µs (which is more than acceptable, e.g., in studies involving living beings), whereas the absolute value of deviation for one-channel data was lower than 40µs. Finally, we assessed the system's usability with the technology acceptance model 3 survey (6 volunteers). Subjects saw the software as useful, and intended to use it in the future. In conclusion, LSRec is a useful tool for those who need to record data from multiple sources, and maintain synchronization with experimental phases with low delay.

This paper describes a proposal for teaching the digital electronics laboratory that combines the traditional method based on the assembly of discrete components on test boards with remote teaching using the virtual teaching platform, the use of simulators and programmable logic devices. The aim is to promote autonomy and creativity and to allow greater flexibility in the organisation of learning.