Research Area

Ageing and Assisted Living

Ageing and Assisted Living is a cross-disciplinary research area, established to promote innovative, multi-disciplinary research in ageing and assisted living with the aim of improving the health and quality of life of older people and people with disabilities.

The UK’s population is ageing. More of us are living into old age and rising numbers of people with chronic illness will place unsustainable pressure on our economy and health and social care systems. As the number of people with chronic illness and disability increases, the demand for assisted living technology has grown to support independent living and enhance quality of life.

Research Areas

Lifelong health, healthy ageing

Health behaviours and lifestyle choices are major determinants of life expectancy, health and wellbeing in old age. Researchers within this focus area will explore novel approaches and interventions to promote and sustain health and wellbeing across the life course into old age.

Age-related disease

Age is the single biggest risk factor for many life-threatening diseases, such as heart failure, cancer and dementia which can lead to chronic ill health and dependence. Researchers working within this focus area will examine the cause, cure and care of a range of age-related diseases and conditions.

Assisted Living

The physical environment plays a central role in determining disabled and older people’s independence, mobility and wellbeing.

Researchers within this focus area will aim to develop new tools and technologies that will enable the elderly, disabled and those with long-term conditions to live independent lives and support translation of assisted living technologies into care/home environments.

Our people

Professor Luca Citi

School of Computer Science and Electronic Engineering, University of Essex

Brain-computer interfaces, neural prostheses, physiological signal processing, computational intelligence for health-related problems.

Dr Adrian Clark

School of Computer Science and Electronic Engineering, University of Essex

Intelligent environments, embedded systems.

Professor John Gan

School of Computer Science and Electronic Engineering, University of Essex

Intelligent systems, robotics, brain-computer interfaces.

Professor Gill Green

School of Health and Social Care, University of Essex

Accessibility study for the Robochair.

Professor Dongbing Gu

School of Computer Science and Electronic Engineering, University of Essex

Intelligent systems, robotic assistive technology, human computer interaction for assisted living.

Professor Hani Hagras

School of Computer Science and Electronic Engineering, University of Essex

Intelligent buildings and environments for assisted living, intelligent autonomous systems, intelligent autonomous robots.

Professor Huosheng Hu

School of Computer Science and Electronic Engineering, University of Essex

Healthcare robotics, telecare, telehealth, telerehabilitation.

Professor Jo Jackson

School of Sports, Rehabilitation and Exercise Sciences, University of Essex

Accessibility study for the Robochair.

Professor Klaus McDonald-Maier

School of Computer Science and Electronic Engineering, University of Essex

Embedded systems for rehabilitation and assistive living.

Professor Riccardo Poli

School of Computer Science and Electronic Engineering, University of Essex

Brain-computer interface.

Professor Martin Reed

School of Computer Science and Electronic Engineering, University of Essex

Network security, management and control of optical and core networks, multimedia internet applications, multi-dimensional signal processing algorithms.

Professor Francisco Sepulveda

School of Computer Science and Electronic Engineering, University of Essex

Brain-computer interfaces, myoelectric operation of artificial limbs and robotic devices, neural prostheses, neurorehabilitation.

Dr Matthew Taylor

School of Sports, Rehabilitation and Exercise Sciences, University of Essex

Using the Nintendo Wii to improve balance and quality-of-life in recurrent elderly fallers, study of gait/movement in the elderly.

Professor Kun Yang

School of Computer Science and Electronic Engineering, University of Essex

Wireless networks and communication, wired network, pervasive (or adaptive) service engineering (mainly in wireless mobile environment), communication networks in assisted living.