SDHAR-HOME: A Sensor Dataset for Human Activity Recognition at Home.

Nowadays, one of the most important objectives in health research is the improvement of the living conditions and well-being of the elderly, especially those who live alone. These people may experience undesired or dangerous situations in their daily life at home due to physical, sensorial or cognitive limitations, such as forgetting their medication or wrong eating habits. This work focuses on the development of a database in a home, through non-intrusive technology, where several users are residing by combining: a set of non-intrusive sensors which captures events that occur in the house, a positioning system through triangulation using beacons and a system for monitoring the user's state through activity wristbands.

Daily Human Activity Recognition Using Non-Intrusive Sensors.

In recent years, Artificial Intelligence Technologies (AIT) have been developed to improve the quality of life of the elderly and their safety in the home. This work focuses on developing a system capable of recognising the most usual activities in the daily life of an elderly person in real-time to enable a specialist to monitor the habits of this person, such as taking medication or eating the correct meals of the day. To this end, a prediction model has been developed based on recurrent neural networks, specifically on bidirectional LSTM networks, to obtain in real-time the activity being carried out by the individuals in their homes, based on the information provided by a set of different sensors installed at each person's home.

Development and Usability Validation of a Social Robot Platform for Physical and Cognitive Stimulation in Elder Care Facilities.

This article shows our work for developing an elder care platform for social interaction and physical and cognitive stimulation using the Pepper robot and Android OS as clients, based on the knowledge acquired on our long-term social robotics research experience. The first results of the user's acceptance of the solution are presented in this article. The platform is able to provide different services to the user, such as information, news, games, exercises or music.

Gaze Control of a Robotic Head for Realistic Interaction With Humans.

When there is an interaction between a robot and a person, gaze control is very important for face-to-face communication. However, when a robot interacts with several people, neurorobotics plays an important role to determine the person to look at and those to pay attention to among the others. There are several factors which can influence the decision: who is speaking, who he/she is speaking to, where people are looking, if the user wants to attract attention, etc.

Integration of Computer Vision and Wireless Networks to Provide Indoor Positioning.

This work presents an integrated which makes use of WiFi signals and RGB cameras, such as surveillance cameras, to track and identify people navigating in complex indoor environments. Previous works have often been based on WiFi, but accuracy is limited. Other works use computer vision, but the problem of identifying concrete persons relies on such techniques as face recognition, which are not useful if there are many unknown people, or where the robustness decreases when individuals are seen from different points of view.

Crack Detection in Concrete Tunnels Using a Gabor Filter Invariant to Rotation.

In this article, a system for the detection of cracks in concrete tunnel surfaces, based on image sensors, is presented. Both data acquisition and processing are covered. Linear cameras and proper lighting are used for data acquisition.

Corrigendum: Virtual Avatar for Emotion Recognition in Patients with Schizophrenia: A Pilot Study.

[This corrects the article on p. 421 in vol. 10, PMID: 27616987.

Virtual Avatar for Emotion Recognition in Patients with Schizophrenia: A Pilot Study.

Persons who suffer from schizophrenia have difficulties in recognizing emotions in others' facial expressions, which affects their capabilities for social interaction and hinders their social integration. Photographic images have traditionally been used to explore emotion recognition impairments in schizophrenia patients, but they lack of the dynamism that is inherent to facial expressiveness. In order to overcome those inconveniences, over the last years different authors have proposed the use of virtual avatars.

Automated Tracking of Drosophila Specimens.

The fruit fly Drosophila Melanogaster has become a model organism in the study of neurobiology and behavior patterns. The analysis of the way the fly moves and its behavior is of great scientific interest for research on aspects such as drug tolerance, aggression or ageing in humans. In this article, a procedure for detecting, identifying and tracking numerous specimens of Drosophila by means of computer vision-based sensing systems is presented.