hero image
Professor Ian Craddock - University of Bristol. Bristol, , GB

Professor Ian Craddock Professor Ian Craddock

Professor in data driven health | University of Bristol


Using technology to improve healthy living and healthcare practices

Areas of Expertise (9)

Health Data

Medical Profession

Healthy Living


Digital Health

Health Technology

Medical technology


Health at Home


Professor Ian Craddock is University Lead for Digital Health which sees him leading teams of researchers that are exploring how the use of technology can be used to address health and medical problems.

Projects underway include developing sensors for use in the home to diagnose and to manage health conditions, addressing heart failure through a soft robotic heart that consists of a robotic shell, using artificial muscles and sensors to enable natural motion, examining the gradual responsiveness of particular medications, and analysing patient data for better healthcare management and planning. Professor Craddock also leads on the education of medics and healthcare practitioners in the use of technology.

Professor Craddock's earlier career was focused on computational electromagnetics. He developed practical, working systems for landmine detection and the world’s first clinical radar imaging system for breast cancer detection. More recently his research has broadened to include a range of technologies for pervasive health monitoring and the emergence of more data-driven healthcare and personalised health. His team has been rated top in the Health category of the World Technology Network awards.






Ian Craddock - the implications of a 24/7 healthcare assistant Bringing healthcare to homes with IoT - Interview with Ian J. Craddock Engagement Awards 2014/15: SPHERE Dress/Sense Professor Ian Craddock. SPHERE, Dress/Sense



Education (1)

University of Bristol: B.Eng., Electronics and Communications 1995

Media Appearances (3)

University of Bristol lead project using WiFi for medical radar

TechSpark  online


“The OPERA team have set out an exciting vision of the future that connects back to the very origins of radar in the 1930s. The team will explore this potential in ways never envisaged by these pioneers, but which hold great promise to transform future healthcare,” said Prof Ian Craddock, Head of the Digital Health Engineering Research Group and Director of SPHERE-IRC based in the Faculty of Engineering.

view more

The eight-second scan that can detect breast cancer...using anti-landmine technology

Daily Mail  online


The technique uses an innovative radar system developed by a team at Bristol University, led by Professor Ian Craddock and Professor Alan Preece.

view more

'Electronic egg' to be created by climate change scientists will reveal secrets of global warming

Daily Mail  online


Professor Ian Craddock of the university's Centre for Communications Research said: 'Trying to communicate data through several kilometres of glacial ice is a major technical challenge. 'It will require highly novel solutions using a suite of communications technologies, along with innovative methods to unscramble the data.'

view more

Articles (5)

Vesta: A digital health analytics platform for a smart home in a box

Future Generation Computer Systems

2020 This paper presents Vesta, a digital health platform composed of a smart home in a box for data collection and an automated analytic system for deriving health indicators using activity recognition, sleep analysis and indoor localization. This system has been deployed in the homes of 40 patients undergoing a heart valve intervention in the United Kingdom (UK) as part of the EurValve project, measuring patients health and well-being before and after their operation.

view more

Energy-efficient activity recognition framework using wearable accelerometers

Journal of Network and Computer Applications

2020 Acceleration data for activity recognition typically are collected on battery-powered devices, leading to a trade-off between high-accuracy recognition and energy-efficient operation. We investigate this trade-off from a feature selection perspective, and propose an energy-efficient activity recognition framework with two key components: a detailed energy consumption model and a number of feature selection algorithms.

view more

Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data


2020 There is a pressing need to automatically understand the state and progression of chronic neurological diseases such as dementia. The emergence of state-of-the-art sensing platforms offers unprecedented opportunities for indirect and automatic evaluation of disease state through the lens of behavioural monitoring.

view more

TSCH Networks for Health IoT: Design, Evaluation, and Trials in the Wild

ACM Transactions on Internet of Things

2020 The emerging Internet of Things has the potential to solve major societal challenges associated with healthcare provision. Low-power wireless protocols for residential Health Internet of Things applications are characterized by high reliability requirements, the need for energy-efficient operation, and the need to operate robustly in diverse environments in the presence of external interference.

view more

Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson’s Disease in the Home or a Home-like Environment

Journal of Parkinson's Disease

2020 The emergence of new technologies measuring outcomes in Parkinson’s disease (PD) to complement the existing clinical rating scales has introduced the possibility of measurement occurring in patients’ own homes whilst they freely live and carry out normal day-to-day activities.

view more