Currently, we have projects in the following areas (although these are not exclusive and new ones will be added in a near future):

  • Neuroinformatics and Clinical Neuroscience
  • Applied Neurotechnologies for Health
  • Physical Activity for Health
  • Internet of Things for Affective Computing in the Health Environment

Neuroinformatics and clinical neuroscience

Neural warning signs for eating disorders

This project focus on discovering the bio-markers that may lead us to understand the neural processes involved in the modulation of our inner thoughts as regards feelings about our own body. This is clinically important to discover novel bio-markers that can be very helpful to diagnose eating disorders in women.

Group members directly involved in this project are Dr Helge Gillmeister, Dr Javier Andreu-Perez, and Professor Hani Hagras.

Atypical and typical brain development during childhood

Brain and cognitive development during childhood is a critical process where behavioural and personality traits of an individual arise. In this project are studied the process about how the brain changes while children grow up. Neuroscience data is also combined with socio-emotional affective aspects to capture a comprehensive view about this process.

This project is led by Dr Silvia Rigato, Dr Javier Andreu-Perez, Dr Maria Laura Filippetti and Professor Hani Hagras.

Applied Neurotechnologies for Health

Robot-assisted rehabilitation for Parkinson's disease

Physiologic tremor occurs in a variety of neurologic disorders, including Parkinson’s disease (PD) and stroke, with negative effects on motor control resulting in reduced ability to conduct activities of daily living and rehabilitation exercises. In this research is proposed to study the characterization of physiologic essential tremor in the upper arm using an existing robot instrumented with smart sensors, and to investigate autonomous control methods for adaptive tremor cancellation that will be integrated in robot-assisted rehabilitation exercises, for improving the smoothness of gross motions.

This project is done in a joint collaboration between Dr Enrico Franco, Dr Ricardo Seccoli, Dr Javier Andreu-Perez.

Physical Activity for Health

Recognition of physical activity in individuals at risk of cardiovascular or autoimmune diseases

In this project we target to develop machine learning methods for the recognition of human daily-activities from wearable sensors. there is a need for investigating how to be able to perform activity recognition on patients with limited mobility and comorbidities. This recognition should account for the immense uncertainty as regards the infinity number of poses or actions an individual may perform during free living conditions. Additionally, better software interfaces that help practitioners to navigate through a person actigraphy will be investigated.

In this project are directly involved Dr Valerie Gladwell, Dr Javier Andreu-Perez, Dr Luis Garcia-Gancedo.

Internet of Things for Affective Computing in Health Environments

Smart operating theatre

This project tackles the challenge of being able to develop perceptually-enabled functionalities to improve ergonomics of surgeons at work, such as detecting and reducing mental fatigue. Sensor information collected at the operating theatre are useful to develop an affective computing system that will pave the way towards an effective ambient intelligence for this critical scenario. In this project sensor information is combined with the use of novel machine learning algorithms to predict the emotional state of the surgeon at work.

In this project is done in collaboration with the Harms-Lab at Imperial College London, and the group members Dr Javier Andreu-Perez and Dr Francisco Sepulveda are directly involved.