Medical problems derived from elderly or from behavioral diseases continue to pose important challenges in improving the quality of life, early identification of diseases, recognition of variations in the behavior of the limbic system and their consequences in learning, memory or in managing emotions. Nowadays, there are several computational- based approaches to gather physio-psychological data from persons, enabling determining the state of well-being or the degree of development of certain symptoms or diseases. The elements that objectively and quantifiably identify these relevant data through usable, portable, implantable or digestible devices are called digital biomarkers (DB). Although as a general rule the design of DB requires multidisciplinary work teams, the current trend is the design and development of them using Artificial Intelligence (AI) techniques.

The Computational based biomarkers for mental and emotional health track intends to provide a discussion forum for the most recent and innovative work on the study and application of digital biomarkers in the compelling scenarios of mental and emotional health. It will cover a wide spectrum of applications, from those aimed at easing and supporting healthcare professionals’ work to those devoted to improving patients’ lives.

The goals of this track are to:

  • establish synergies between researchers of digital biomarkers in mental and emotional health;
  • provide a forum for identifying important theoretical and methodological AI contributions to mental and emotional health research;
  • promote the application of digital biomarkers to mental and emotional sciences;
  • showcase applications of digital biomarkers in mental and emotional health.

This track intends to bring together computer scientists and clinicians working in mental and emotional healthcare, medicine and biomedicine, providing a presentation and discussion forum for researchers in the area, highlighting innovative and compelling healthcare applications of digital biomarkers, and defining future research directions.


The topics include, but are not limited to:

  • Digital biomarkers in mental and emotional health for decision-support systems
  • Enabling technologies for new digital biomarkers for mental and emotional health
  • Evidence-based medicine from digital biomarkers in mental and emotional health
  • Digital biomarkers and related social networks issues for mental and emotional health
  • Personalized mental and emotional medicine and patient-centered systems based on digital biomarkers
  • Digital biomarkers for empowerment and wellness in mental and emotional health

Paper submission

  • Prospective authors are invited to submit papers in any of the topics listed above.
  • Instructions for preparing the manuscript (in Word and Latex formats) are available at: Call for Papers (main track)
  • Please also check the Guidelines.
  • Papers must be submitted electronically via the web-based submission system.


  • Ainhoa Yera, University of the Basque Country, Spain
  • Joaquim Massana, University of Girona, Spain
  • José Ramón Villar, University of Oviedo, Spain

Program Committee

  • Hugo Alexander Ferreira, Faculdade de Ciências da Universidade de Lisboa, Portugal
  • Adriana Arza, École Polytechnique Fédérale de Lausanne, Switzerland
  • José Luis Arcos, Consejo Superior de Investigaciones Científicas, Spain
  • Enrique de la Cal, University of Oviedo, Spain
  • Beatriz de la Iglesia, University of East Anglia, UK
  • Laura Dubreuil, Neurosciences Innovation Department, Roche, US
  • Irene Díaz, University of Oviedo, Spain
  • Iñigo Gabilondo, Mondragon Unibertsitatea, Biocruces, Spain
  • Beatriz López, University of Girona, Spain
  • Raquel Martínez, University of the Basque Country, Spain
  • Joaquim Massana, University of Girona, Spain
  • Ernest Montañà, MJN Neuroserveis, Spain
  • Javier Muguerza, University of the Basque Country, Spain
  • Alex Mihailidis, University of Toronto, Canada
  • Gustavo Patow, University of Girona, Spain
  • Joaquín Roca, Technical University of Cartagena, Spain
  • Asier Salazar, University of the Basque Country, Spain
  • Luciano Sánchez, University of Oviedo, Spain
  • Akane Sano Rice, University, US
  • Hugo Silva, Instituto de Telecomunicações, PLUX, Portugal
  • Adrià Tausté, Pompeu Fabra University, Spain
  • Carmen Vidaurre, Public University of Navarre, Spain
  • José Ramón Villar, University of Oviedo, Spain
  • Ainhoa Yera, University of the Basque Country, Spain

Special Issues

A journal special issue will be proposed to authors with accepted papers for submitting an extended version of their work.

Agenda (June 8, 2021)

15:15-15:25Presentation of the Special Track
15:25-15:33On identification of chronodisruption-based biomarkers to estimate pregnancy attempt tim, Ana G. Rúa, Noelia Rico-Pachón, Ana Alonso, Elena Díaz and Irene Diaz
15:33-15:41Automatic Detection and filtering of artifacts from EEG signal, Fernando Moncada, Víctor M. González, Víctor Álvarez, Beatriz García and José Ramón Villar
15:41-15:49Preliminary analysis of features based on GSR/RR signals for spinal cord injury patients, Nagore Sagastibeltza, Asier Salazar-Ramirez, Raquel Martinez, Maitane Martinez-Eguiluz, Javier Muguerza, Nora Cívicos Sánchez, Montserrat Cuadrado and María Luisa Jauregui Abrisqueta
15:49-15:57Diagnosing Schizophrenia from Activity Records using Hidden Markov Model Parameters, Matthias Boeker, Michael Riegler, Hugo Lewi Hammer, Pål Halvorsen and Petter Jakobsen
15:57-16:05Understanding affective behaviour from physiological signals: Feature learning versus pattern mining, Natalia Mordvanyuk, Jaume Gauchola and Beatriz López
16:05-16:13Wearable and Continuous Prediction of Passage of Time Perception for Monitoring Mental Healt, Lara Orlandic, Adriana Arza Valdes and David Atienza
16:13-16:21Optimized alpha band patterns correlated with trait anxiety, Carmen Vidaurre, Vadim V Nikulin and Maria Herrojo Ruiz
16:30-16:50Invited Speaker’s Talk
16:50-17:20Round table (among all the participants of the session)

Invited Speaker’s Talk

Dr. Hugo Plácido da Silva, researcher at IT – Instituto de Telecomunicações, professor at Bioengineering Department of IST- Instituto Superior Técnico

Mental and Emotional Health Research Beyond the Lab

The seminal work on Affective Computing (AfC) by Rosalind Picard set the base for computing that relates to, arises from, or influences emotions. Today, AfC is a multidisciplinary field of research spanning the areas of computer science, psychology, and cognitive science. Potential applications include mental and emotional health, although AfC has gained an increasingly high interest in many other areas since its inception.

Physical sentic state manifestations are easily collected, however, they can be easily masked, and depend on the user social environment, cultural background, personality, and other factors. Psychophysiological signals, however, are prone to present a more authentic insight into the subjects’ mental and emotional state. Wearables have contributed to make psychophysiological sensing a more pervasive and integral part of people’s daily lives, with significant impact in AfC research. Nevertheless, multiple hindering factors still exist when moving beyond the lab.

In this talk we will provide an overview of the current challenges and opportunities in mental and emotional health research beyond the lab. Particular emphasis will be given to novel methodological and biomedical sensing approaches targeting the integration of AfC in people’s everyday lives. Practical examples of hardware and software tools, and their use in real-world AfC problems will be presented.