Dr. Julian Rudisch
Julian Rudisch is a postdoctoral researcher at the Department of Neuromotor Behavior and Exercise at the University of Münster in Germany. He obtained his PhD in the field of neurorehabilitation in 2017, investigating bimanual coordination and motor learning in children with unilateral Cerebral Palsy from Oxford Brookes University, UK. Julian has broad research interests in the field of motor control and learning, with core topics involving: i) Understanding the neural and behavioral mechanisms of bimanual coordination; ii) Exploring the role of ageing and age-related cognitive impairments on motor control; and iii) Investigating the role of functional movement variability on motor coordination, with a focus on clinical populations with motor impairments.
Links
University Profile (incl. Bibliography)
Selected Publications
Vogel, O., Vogt, L., Niederer, D., Cordes, T., Bischoff, L., Johnen, B., Hildebrand, C., Jöllenbeck, T., Klotzbier, T. J., Korbus, H., Rudisch, J., Schoene, D., Schott, N., Weigelt, M., Wilke, J., Zwingmann, K., Voelcker-Rehage, C., & Wollesen, B. (2025, January 1). Multicomponent Exercise to Improve Physical and Cognitive Performance and Well-Being in Nursing Home Residents: The Single-Blind, Multicentre, Randomised Controlled PROCARE Trial. https://doi.org/10.2139/ssrn.5316040
Rudisch, J., Fröhlich, S., Kutz, D. F., & Voelcker-Rehage, C. (2024). Force-fluctuations during role-differentiated bimanual movements reflect cognitive impairments in older adults. A cohort sequential study. The Journals of Gerontology Series A. https://doi.org/10.1093/gerona/glae137
Rudisch, J., Jöllenbeck, T., Vogt, L., Cordes, T., Klotzbier, T. J., Vogel, O., & Wollesen, B. (2021). Agreement and consistency of five different clinical gait analysis systems in the assessment of spatiotemporal gait parameters. Gait & Posture, 85. https://doi.org/10.1016/j.gaitpost.2021.01.013
Goelz, C., Mora, K., Rudisch, J., Gaidai, R., Reuter, E., Godde, B., Reinsberger, C., Voelcker-Rehage, C., & Vieluf, S. (2021). Classification of visuomotor tasks based on electroencephalographic data depends on age-related differences in brain activity patterns. Neural Networks, 142(11001). https://doi.org/10.1016/j.neunet.2021.04.029