Visualizing “Cognitive Fingerprints” from Simple Mobile Game Play


  • Kai Gutenschwager Ostfalia University of Applied Sciences
  • Kyle Leduc-McNiven University of Manitoba
  • Mahmood McLeod University of Manitoba
  • R.D. McLeod University of Manitoba
  • Marcia Friesen University of Manitoba


Serious Games and associated data analytics of-fer the potential of a complementary means of detecting early signs of mild cognitive impairment (MCI), which is often a pre-cursor to more serious forms of dementias. As with all diseases and illnesses, the ability to mitigate the impact of the illness is directly correlated to early detection and intervention. In this work, a representative serious game is used to capture a “cogni-tive fingerprint” of a person’s play, which is then used to ana-lyze and visualize play. The long-term objective of the research is to demonstrate that data collected from serious games may be used to detect cognitive difficulties that may be pre-sympto-matic, and outside the scope of normal age related cognitive de-cline. The present work assesses the viability of the platform for this purpose and opportunities in data visualization, but does not include clinical testing for MCI.




How to Cite

K. Gutenschwager, K. Leduc-McNiven, M. McLeod, R. McLeod, and M. Friesen, “Visualizing ‘Cognitive Fingerprints’ from Simple Mobile Game Play”, CMBES Proc., vol. 42, May 2019.