Conferences
eHealth Eurocampus Project: preparing innovative ICT professionals
authors: N. Castell1, J. Lobo2, E. Insa Calderon3, R. Picking4, Y. González5, S. Abdelaziz6, B. Voegel7, X. Tous8, C. Pattichis9, B. Rigaud10
Inter-Beat Interval Estimation from Extremely Noisy Single Lead Electrocardiograms
The advent of wearable recorders poses new challenges to electrocardiogram (ECG) analysis, such as robust feature extraction in front of long-term recordings with intervals of extreme noise. This paper proposes a robust approach to improve the estimates of one...
Visual Loop Detection in Underwater Robotics: An Unsupervised Deep Learning Approach
This paper presents a novel Deep Neural Network aimed at fast and robust visual loop detection targeted to underwater images. In order to help the proposed network to learn the features that define loop closings, a global image descriptor built upon clusters of local...
Clock Synchronization in Integrated TSN-EtherCAT Networks
Moving towards new technologies, such as Time Sensitive Networking (TSN), in industries should be gradual with a proper integration process instead of replacing the existing ones to make it beneficial in terms of cost and performance. Within this context, this paper...
Towards Visual Loop Detection in Underwater Robotics using a Deep Neural Network
{This paper constitutes a first step towards the use of Deep Neural Networks to fast and robustly detect underwater visual loops. The proposed architecture is based on an autoencoder, replacing the decoder part by a set of fully connected layers. Thanks to that it is...
Using Machine Learning and Heart Rate Variability Features to Predict Epileptic Seizures
This study constitutes a first step towards a wearable epileptic seizure prediction device. We exploit the existing correlation between epileptic pre-ictal states and heart rate variability features, since they can be measured by portable electrocardiogram recorders....