Technology and the measurement of health

Our team are experts in developing digital health interventions that provide feedback to the public about their health and our research is exploring methods of objectively assessing physical activity and movement.

Technology has been revolutionising our society for centuries. The recent integration of digital health technology into modern life (e.g. smartphones and physical activity trackers) has led to an increased effort to apply these technologies to health improvement.

Our internationally renowned team of experts are employing cutting-edge, innovative methods to understand how to best utilise technology to increase physical activity and reduce time sedentary in the population. Our team is at the forefront of shaping how best to use these technologies within national health policy and practice.

Theme leads

Dale Esliger

Dr Dale Esliger

Reader in Digital Health

James Sanders

Dr James Sanders

Senior Research Associate in Digital Health for Lifestyle Medicine

Research spotlight


  • Sanders JP, Gokal K, Thomas JJ, Rawstorn JC, Sherar LB, Maddison R, Greaves CJ, Esliger D, Daley AJ and Snacktivity Investigators, 2023. Development of a Mobile Health SnacktivityTM App to Promote Physical Activity in Inactive Adults (SnackApp): Intervention Mapping and User Testing Study. JMIR Formative Research, 7, p.e41114. DOI: 10.2196/41114


  • Sanders, J.P., Biddle, S.J., Gokal, K., Sherar, L.B., Skrybant, M., Parretti, H.M., Ives, N., Yates, T., Mutrie, N., Daley, A.J. and Snacktivity Study Team, 2021. ‘Snacktivity™’to increase physical activity: Time to try something different?. Preventive Medicine, 2021;  153, 106851 DOI: 10.1016/j.ypmed.2021.106851

  • Snacktivity™ to promote physical activity. Funded by NIHR. Led by Amanda Daley.

  • The health benefits of Snacktivity™. Led by Jonah Thomas.

  • Measuring Engagement with mHealth tools: A systematic review of methodologies – Led by James Sanders.

  • ADAPTIVE: Context-aware ADAptive Physical acTivity interVEntions using model predictive control – Led by James Sanders.