Movement Science Group (MSG)

About us

The Movement Science Group (MSG) focuses on the development and implementation of new methodologies to measure, map and improve mobility of people of all ages with and without neurological conditions in the community.

Our research group is led by an end-user steering group committee which meets several times a year. The committee guides a group of multidisciplinary expert researchers in their work to address real mobility problems.

The group has been involved in numerous studies in the development of new outcome measurements. Examples include: measuring rhythmic stepping for the identification of motor problems in children, identifying mobility patterns in a wide range of neurological conditions via movement and scanning of the brain using functional near infrared spectroscopy or magnetic resonance imaging.

Researcher placing gate sensor on lower back

Research impact

MRI scanner ready for in-scanner motion task for children with developmental coordination disorders

Over the past few years, we have developed a smartphone-based device which, given its ultra sensitivity, can potentially aid in the diagnosis of a range of conditions before the manifestations of obvious clinical symptoms. This unique approach is quick, accessible and could have substantial impact on international healthcare systems.

The vast range of exciting projects links us with clinical and academic experts from world renowned institutions in the UK, such as the University of Oxford and University College London, as well as internationally, such as McGill University (Canada) and Shanghai Jiao Tong University (China).


Patrick Esser

Dr Patrick Esser

Reader in Sport and Rehabilitation Technology

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Name Role Email
Dr Shelly Coe Senior Lecturer in Nutrition
Dr Johnny Collett Senior Lecturer in Clinical Exercise and Rehabilitation
Professor Helen Dawes Honorary Professor
Professor Derick Wade Professor In Neurorehabilitation


Name Thesis Title Supervisors Completed
Sam Burden Cardiac function of the left ventricle in obese adolescents with the establishment of links to metabolic health and physiological and perceptual exercise responses Dr Patrick Esser


Ed Daly Concussion characterisation using current concussion diagnosis and evaluation measures compared to novel objective testing methods Dr Adam White, Dr Patrick Esser


Daniel Newcombe The Environment Design Framework: Bridging the gap between the theoretical understanding and the practical application of constraints-led approach Dr Patrick Esser


Zoe Taylor Power training for fall rehabilitation and prevention in over 56s and comparisons of recovery mechanisms for loss of balance between fallers and non-fallers Dr Greg Walsh, Dr Mario Inacio, Dr Patrick Esser



Name Role Organisation
Dr Mario Inacio University of Maia, Portugal

Key Publications


  • TEKTONIDIS, T. G., COE, S., ESSER, P., MADDOCK, J., BUCHANAN, S., MAVROMMATI, F., SCHOTT, J. M., IZADI, H., RICHARDS, M. & DAWES, H. 2020. Diet quality in late midlife is associated with faster walking speed in later life in women, but not men: findings from a prospective British birth cohort. Br J Nutr, 123, 913-921.


  • MANSOUBI, M., ESSER, P., MEANEY, A., METZ, R., BEUNDER, K. & DAWES, H. 2019. Evaluating of the Axivity accelerometers algorithm in measurement of physical activity intensity in boys and girls.


  • VALKANOVA, V., ESSER P, DEMNITZ, N., SEXTON, C., ZSOLDOS, E., MAHMOOD, A., GRIFFANTI, L., KIVIMAKI, M., SINGH-MANOUX, A., DAWES, H. & EBMEIER, K. P. 2018. Association between gait and cognition in an elderly population based sample. Gait and Posture, in press.

    AL-YAHYA, E., MAHMOUD, W., MEESTER, D., ESSER, P. & DAWES, H. 2018. Neural Substrates of Cognitive Motor Interference During Walking; Peripheral and Central Mechanisms. Front Hum Neurosci, 12, 536.


  • CUZZOLIN, F., SAPIENZA, M., ESSER, P., SAHA, S., FRANSSEN, M. M., COLLETT, J. & DAWES, H. 2017. Metric learning for Parkinsonian identification from IMU gait measurements. Gait Posture, 54, 127-132

A coloured side and front brain scan image