On July 13th, our colleague and lab member Santiago Real Valdés defended his PhD Thesis entitled “Network Design Strategies for Multisensory Human-Machine Interfaces of Navigation Systems for Blind and Visually Impaired People”. This work was carried out at B105 Electronic Systems Lab under the direction of Professor Alvaro Araujo.

The thesis defense took place at the ETSI Telecomunicación in Madrid. The work was evaluated positively earning the highest possible grade, along with the “cum laude” mention.

Overall, the research pursued design guidelines, tools, and methods for the development of networked navigation assistance systems for blind and visually impaired (BVI) individuals. Specifically, it resulted in the following contributions to the scientific community:

  • Study of the state-of-art at navigation assistance for BVI individuals. This was undertaken to re-evaluate the perspective of navigation systems for the blind and visually impaired (BVI) in a new technological-enabling context, attempting to integrate key elements of what is frequently a disaggregated multidisciplinary background.
  • Development of the Virtually Enhanced Senses (VES) System. VES is a wireless, mixed-reality platform developed to design, emulate, implement, and test complete navigation systems.
  • Development of novel Sensory Substitution Devices (SSD) and methodologies to assess navigation assistance in mixed reality environments. Novel and representative SSD were implemented building on previous solutions, design guidelines and recommendations. Thereafter, new methodologies and performance markers were developed to quantify the performance of the SSD under various network architectures and operation conditions.
  • Novel relations between Quality-of-Experience (QoE) and Quality-of-Service (QoS) in navigation assistance for BVI individuals were found.  Overall, a tradeoff was observed between the user’s spatial data acquisition and sensorimotor coupling degradation due to motion-to-photon delay.

Further information on the open-access VES system can be found at the following link. Also, the latest results were disseminated through the media:

MINA-CM: Madrid Innovative Neurotech Alliance

Neurotechnologies are achieving spectacular advances both in the treatment of pathologies of the
nervous system (with the reduction of enormous social and economic costs associated with these
diseases; with disability and mortality rates of 21M disabled, 1.2M deceased per year respectively in
Europe, costs >4% of GDP) as well as in other important areas, such as empowerment and extension
of brain capacities, brain-machine and brain-brain interfaces. The applications of these technologies
are immense, from the clinical aspects related with the prevention, diagnosis and treatment of
neurological pathologies to the development of new computation systems, improvement of learning,
integration and connection of advanced devices with the nervous system.

The main goal of Madrid Innovative Neurotech Alliance (MINA-CM) is the innovation, development and application of advanced neurotechnological solutions in the Comunidad de Madrid.

The main objectives of MINA-CM are:
The development of multidisciplinary and interinstitutional biomedical R+D+i in neurotechnologies for
pathologies of the nervous system and improvement of brain capacities and interconnection through
physical and functional interfaces.
The attraction and incorporation of exceptional young researchers to R+D+i in neurotechnology in the Comunidad de Madrid.
The reinforcement and enhancement of the participation of the Comunidad de Madrid in international
networks and consortiums of R+D+I in neurotechnology.
The reinforcement, potentiation and integration of companies, in particular SMEs of high technology in a network of R+D+i in neurotechnology in the Comunidad de Madrid to favor international and national funding.

Title: MINA-CM – Madrid Innovative Neurotech Alliance
Duration: January 2023 – December 2026
Financing entity: Comunidad de Madrid, Programas de actividades de I+D entre grupos de investigación de la Comunidad de Madrid en Biomedicina 2022 (P2022/BMD-7236)

Visita del CIDAT

Como podrán apreciar los lectores frecuentes de nuestro blog, las lineas de investigación de nuestro grupo abordan temáticas muy diversas. La que trataremos en este artículo está orientada mejorar la percepción espacial por medios no visuales. Para ello, utilizamos una red de dispositivos “wearables” que generan estímulos hápticos y acústicos de acuerdo a teorías recientes en materia de sustitución sensorial.

El objetivo principal es que una persona con discapacidad visual grave o ceguera tenga menos dificultades a la hora de desplazarse por la ciudad, en interiores, etc. Nuestro primer prototipo, Virtually Enhanced Senses (VES), virtualiza las características más importantes de un escenario real desde una perspectiva de orientación y movilidad, y proporciona la información al usuario de forma intuitiva.

Recientemente hemos tenido la suerte de contar con personal del CIDAT para la evaluación y posterior perfeccionamiento del prototipo. Durante las reuniones y demostraciones de la tecnología, los usuarios finales pudieron experimentar de primera mano el sistema tanto en escenarios virtuales como reales.

Desde aquí queríamos agradecer a nuestros invitados por su tiempo, esfuerzo e ilusión, esperando vernos de nuevo en un futuro próximo.

TFM: Design strategies for detecting action potentials in actions based on movements

This work is located in the studies of the brain and their signals. The puspose is to know when someone wants to make a movement. Thus, it might help to people that actually are not able to move a member of their body or more. Mainly, it is focused in the design of strategies for detection of action potentials or spikes when a movement wants to be made. This study is not looking for action potentials form, it is looking for patterns and characteristics that allow to recognize the movement. Although there are action potentials covered by the signals taken from the electrodes, but they are unavailable.

To accomplish the objective, it is used the EEG signals of a public data base. It is selected the ones related to the movement of the hands, concretely, the movement of open and close the fist. Signal sources of noise that dirty the signal are analyzed, they are called artifacts, and then, filtering stage comes, giving the signals of below for movement and no movement.


Now, possible algorithms are checked. It is decided to use the Wavelet transform and the way in which it obtains the energy of the signal. Thanks to the calculation of Wavelet energy in 22 subjects, it is reached to the conclusion that Wavelet energy for movement is higher than for no movement. So, electrodes that comply with this condition at 100% are 4.

The final algorithm is implemented three features: correlation, a parameter that gives a relation between two signals, their energy range and their energy average. It could be said that algorithm has two parts: a training stage and a decision stage. Inside decision part, there are three algorithms: ProMove, ProMove + improve and Logic. The basic difference among ProMove and Logic is an or (||) and an and (&). The improve is based on empiric knowledge.




Final conclusions show that the signals between subjects are very changing. Therefore, same algorithm is not useful for everybody. To some subjects, the successful probability is very high (92,86% – 1 fail), while for others is more low than what is expected (50% – 7 fail). With these test, the importance in the length of the signals is reflected, because if signals for subjects with more than 3 fails are inversely processed, the fails are reduced. The most useful algorithm for a larger number of subjects is ProMove + improve.

A WSN-Based Intrusion Alarm System to Improve Safety in Road Work Zones

Title: A WSN-Based Intrusion Alarm System to Improve Safety in Road Work Zones
Authors: Jose Martin, Alba Rozas, and Alvaro Araujo
Published in: Journal of Sensors
Date of Publication: Jun 2016
Digital Object Identifier : 10.1155/2016/7048141

Road traffic accidents are one of the main causes of death and disability worldwide. Workers responsible for maintaining and repairing roadways are especially prone to suffer these events, given their exceptional exposure to traffic. Since these actuations usually coexist with regular traffic, an errant driver can easily intrude the work area and provoke a collision. Some authors have proposed mechanisms aimed at detecting breaches in the work zone perimeter and alerting workers, which are collectively called intrusion alarm systems. However, they have several limitations and have not yet fulfilled the necessities of these scenarios. In this paper, we propose a new intrusion alarm system based on a Wireless Sensor Network (WSN). Our system is comprised of two main elements: vehicle detectors that form a virtual barrier and detect perimeter breaches by means of an ultrasonic beam and individual warning devices that transmit alerts to the workers. All these elements have a wireless communication interface and form a network that covers the whole work area. This network is in charge of transmitting and routing the alarms and coordinates the behavior of the system. We have tested our solution under real conditions with satisfactory results.