La COVID-19 y los desafíos de la vigilancia digital para los derechos humanos: a propósito de la app DataCOVID prevista en la Orden Ministerial SND/29/2020, de 27 de marzo / COVID-19 and the challenges of digital surveillance for human rights: Analysis of the app DataCOVID foreseen in the Ministerial Order SND/29/2020, of March 27th / La COVID-19 I els desafiaments de la vigilancia digital pels drets humans: a propòsit de l'app DataCOVID prevista a l'Ordre Ministerial SND/29/2020, del 27 de març

La pandemia de la COVID-19 ha demostrado la fragilidad del mundo globalizado y se está combatiendo mediante una combinación de técnicas y herramientas de ámbitos muy diferentes, desde clínico hasta tecnológico. La aplicación de las nuevas tecnologías ha suscitado el actual gran debate europeo sobre la privacidad. Una de sus manifestaciones es la Orden SND/29/2020, de 27 de marzo, del Ministerio de Sanidad, en la que se prevé el desarrollo de la app DataCOVID de seguimiento digital. Este trabajo tiene por objeto examinar la legalidad y alcance de estas medidas desde la perspectiva del respeto al derecho a la privacidad en el marco de las garantías para los derechos humanos y la protección de datos

The COVID-19 pandemic has demonstrated the fragility of the globalized world and is being fought through a combination of techniques and tools, among which new contact tracing technologies play a fundamental role. These new tracking technologies have sparked the current great European debate on privacy. One of its manifestations is Order SND/29/2020, of March 27, approved by the Ministry of Health of the Government of Spain, which provides for the development of a website and a contact tracing app DataCOVID. This work aims at examining the legality and scope of the measures adopted in the Ministerial Order considering its implications for the respect of the right to privacy and data protection from the perspective of human rights guarantees

La pandèmia de la COVID-19 ha demostrat la fragilitat del món globalitzat I s'està combatent mitjançant una combinació de tècniques I eines d'àmbits molt diferents, des del clínic fins al tecnològic. L'aplicació de les noves tecnologies ha suscitat l'actual gran debat europeu sobre la privacitat. Una de les seves manifestacions és l'Ordre SND/29/2020, del 27 de març, del Ministeri de Sanitat, en la qual es preveu el desenvolupament de l'app DataCOVID de seguiment digital. Aquest treball té per objecte examinar la legalitat I abast d'aquestes mesures des de la perspectiva del respecte al dret a la privacitat en el marc de les garanties pels drets humans I la protecció de dades

Discrete classification technique applied to TV advertisements liking recognition system based on low-cost EEG headsets.

BACKGROUND: In this paper a new approach is applied to the area of marketing research. The aim of this paper is to recognize how brain activity responds during the visualization of short video advertisements using discrete classification techniques. By means of low cost electroencephalography devices (EEG), the activation level of some brain regions have been studied while the ads are shown to users. We may wonder about how useful is the use of neuroscience knowledge in marketing, or what could provide neuroscience to marketing sector, or why this approach can improve the accuracy and the final user acceptance compared to other works. METHODS: By using discrete techniques over EEG frequency bands of a generated dataset, C4.5, ANN and the new recognition system based on Ameva, a discretization algorithm, is applied to obtain the score given by subjects to each TV ad. RESULTS: The proposed technique allows to reach more than 75 % of accuracy, which is an excellent result taking into account the typology of EEG sensors used in this work. Furthermore, the time consumption of the algorithm proposed is reduced up to 30 % compared to other techniques presented in this paper. CONCLUSIONS: This bring about a battery lifetime improvement on the devices where the algorithm is running, extending the experience in the ubiquitous context where the new approach has been tested.

Low energy physical activity recognition system on smartphones.

An innovative approach to physical activity recognition based on the use of discrete variables obtained from accelerometer sensors is presented. The system first performs a discretization process for each variable, which allows efficient recognition of activities performed by users using as little energy as possible. To this end, an innovative discretization and classification technique is presented based on the χ2 distribution. Furthermore, the entire recognition process is executed on the smartphone, which determines not only the activity performed, but also the frequency at which it is carried out. These techniques and the new classification system presented reduce energy consumption caused by the activity monitoring system. The energy saved increases smartphone usage time to more than 27 h without recharging while maintaining accuracy.