WCCI2018 Special Session

  8–13 July 2018
Rio de Janeiro, Brazil 
Computational Intelligence for Sensing and Predicting Human Mental and Medical State (CI-SEPHUMMES)


Computational intelligence techniques have shown to be effective in classifying human mental and medical state. This is useful for a number of applications including within mental health treatment technology and systems for monitoring and notifying about irregular medical state of elderly people living alone at home. At the same time, it is interesting to consider applying methods across the different application areas which we would like to contribute to through this special session covering two different application domains. Many different kinds of sensing technologies are relevant including sensors available in smartphones, sensor watches and ambient sensors. The latter can be applied either as fixed mount room sensors or equipped on a moveable robot companion. Other user features like speech and smartphones usage can be relevant to apply for improving prediction accuracy. There is also new compact radar technology including ultra-wideband that are able to sense medical condition remotely. A challenge of the application domain is that data is mostly of private nature and schemes for protecting privacy are important and partly dependent on the type of sensors used.    

The number of elderly people living at home is increasing, and this trend is expected to continue since the proportion of elderly people in the world is increasing. Further, the mental health challenges in our society are increasing. Thus, there is a need for technology that can support these user groups. This can potentially make the health care services more effective with reduced recovery time within mental health and making elderly in independent living get better support from caregivers. This special session will be organized for sharing knowledge about technological opportunities and challenges within the addressed domains as well be open to work addressing ethical considerations.

Scope and Topics

The aim of the special session is to provide a forum to disseminate and discuss recent and significant research within applying computation intelligence to classify, model and predict future human mental and medical state. We invite interested authors to submit their original and unpublished work to this special session.

 Topics of interest within the given application domain for the special session include (but are not limited to):

·      Ambient assisted living

·      Ambient sensor systems

· Contributions and Applications of Computational Neuroscience

·      Data analytics and visualization

·      Emotion detection

·      Medical state classification and forecasting

·      Mental disorders state classification and forecasting

·      Mobile sensing

·      Multi-sensor fusion

·      On-body sensor systems

·      Privacy in human monitoring

·      Remote sensing and monitoring

·      Robot companion sensing

·      Sensitive data collection and storage

·      Sensor networks

·      Smart home technologies

·      Temporal data analysis

·      Time series modeling and forecasting

Jim Torresen, University of Oslo, Norway
Enrique Garcia Ceja, University of Oslo, Norway
Dante Barone, Federal University of Rio Grande do Sul, Brazil