Dr. Rajat Emanuel Singh Assistant Professor of Kinesiology
Ph.D., M.S., University of Arkansas at Little Rock
B.Tech., Punjab Technical University
Dr. Rajat Emanuel Singh has post-doctoral research experience from the Joint Department of Biomedical Engineering at North Carolina State University/University of North Carolina at Chapel Hill, and at the University of Minnesota, Minneapolis. He has also worked as a research intern at Shirley Ryan Ability Lab of Northwestern University in Chicago. His research focus is biomechanical movement—specifically, synergy analysis of movement disorders, with the goal of quantifying muscle coordination strategies when assistive technologies are being used. Dr. Singh completed his undergraduate degree in electronics and communication engineering at Punjab Technical University, India. His master’s degree and doctoral work were completed at the University of Arkansas, Little Rock. Dr. Singh’s published work has appeared, among other places, in the top international journals.
Ashar T. Abd, Rajat Emanuel Singh, Kamran Iqbal, Gannon White, (2021) “Investigation of Power Specific Motor Primitives in an Upper Limb Cyclic Rotational Motion," Journal of Motor Behavior, https://doi.org/10.1080/00222895.2021.1916424.
Rajat Emanuel Singh, Kamran Iqbal, Gannon White, (2020) “Proficiency based recruitment of muscle synergies in a highly perturbed walking task," Engineering Reports, https://doi.org/10.1002/eng2.12253.
Rajat Emanuel Singh, Gannon White, Ioannis Delis, Kamran Iqbal (2020), “Alteration of Muscle synergy structure while walking with higher postural constraints (Slacklining)," IET Cognitive Computation & Systems, https://doi.org/10.1049/ccs.2019.0021.
Rajat Emanuel Singh, Kamran Iqbal, Tarun Edgar Hutchinson, Gannon White (2018). “Muscle synergies from building blocks to neuro-rehabilitation tool," Journal of Applied Bionics and Biomechanics, https://doi.org/10.1155/2018/3615368.
Rajat Emanuel Singh, Kamran Iqbal, Gannon White, Jennifer K. Holtz (2019), A review of EMG techniques for the detection of Gait, Machine Learning in Medicine and Biology, Intech Open, DOI: 10.5772/intechopen.84403.
International Society of Electrophysiology and Kinesiology
IEEE Engineering in Medicine and Biology Society
Institute of Engineering India