Centre for Computational Intelligence

Smart Health Technologies Group

Bringing together technology and healthcare

The Smart Health Technologies Group (SmartHealthTech) is an inter-departmental multidisciplinary research group of the Institute of Public Health and Wellbeing and associated with the Centre for Computational Intelligence. Our main purpose is to apply information and digital technologies to improve health. These challenges entail developing novel algorithms, computational models, interactive software and apps, in order to help healthcare professionals and patients.

The vision of the group is to conduct high quality research that focuses on solving problems related to health or healthcare delivery. Our research aims at leveraging digital health solutions at local, national and international levels.

The group brings together research scientists from the Department of Psychology, School of Health and Social Care, School of Sport, Rehabilitation and Exercise Sciences and the School of Computer Science and Electronic Engineering at University of Essex. It also accounts with the support of healthcare facilities provided by National Health Services (NHS) Trust in the East of England region and London and advice from consumer healthcare companies such as GlaxoSmithKline.

The Smart Health Technologies Group has five main areas of research:

Physiological sensing

Solutions to the challenges arising from physiological sensing from body sensor networks and bio-sensing platforms. Advanced Signal processing solutions for wearable and portable eHealth systems.

Neuroinformatics

Development of computational models and analytical tools for cognitive neuroscience research. Advanced computational intelligence to deal with the huge and complex neuroscientific data.

Robotics in healthcare

Development of intelligent robotic platforms for nursing and assistance as well as therapeutic and assistive robots for rehabilitation and continuing care.

IoT for health

Investigating the potential of Internet-enabled devices and sensors to seamlessly collect and analyse real-time health and fitness data. Connecting and fuse networks of medical devices.

Computer Vision in healthcare

Using computer vision techniques to enhance medical imaging to diagnose, monitor or treat medical conditions. Additionally, we also use video information as a contextual source to gain high level understanding about a health related environment.