JACIII Vol.23 No.5 pp. 874-882
doi: 10.20965/jaciii.2019.p0874


Feature Extraction of Mild Cognitive Impairment Using a Dual-Task of Drawing and Counting Test

Katsuya Fujiwara, Hidenori Kano, and Kazutaka Mitobe

Graduate School of Engineering Science, Akita University
1-1 Tegata-gakuen-machi, Akita, Akita 010-8502, Japan

August 25, 2018
April 4, 2019
September 20, 2019
elderly people, mild cognitive impairment, dual task, dexterous hand motion, cognitive function
Feature Extraction of Mild Cognitive Impairment Using a Dual-Task of Drawing and Counting Test

Dual-task of drawing and counting test

From the perspective of preventive care, a monitoring function that detects a decline in cognitive function would be useful as an information and communications technology (ICT) based service for watching over elderly people. We developed a system that evaluates cognitive functioning by simultaneously measuring dual tasks using a tablet computer. The tasks comprised a spiral drawing task and a color change counting task. The objective of this research is feature extraction of mild cognitive impairment (MCI) using this system. To do so, we compared the results of dual task tests for three participant groups: elderly people with suspected MCI, healthy elderly people, and healthy young people. The analyses were based on the amount of time required for drawing each section and the drawing velocity. The results indicate a significant difference between the MCI elders and the other two groups regarding the amount of time required for drawing the section close to the center of the spiral if the difficulty of the test’s sub-task is adjusted.

Cite this article as:
K. Fujiwara, H. Kano, and K. Mitobe, “Feature Extraction of Mild Cognitive Impairment Using a Dual-Task of Drawing and Counting Test,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.5, pp. 874-882, 2019.
Data files:
  1. [1] Department of Economic and Social Affairs, United Nations, “World Population Prospects: The 2017 Revision,” United Nations Publication, 2017.
  2. [2] National Institute of Population and Social Security Research, Government of Japan, “Population Projections for Japan: 2016 to 2065,” 2017.
  3. [3] M. Marschollek, S. Mix, K.-H. Wolf, B. Effertz, R. Haux, and E. Steinhagen-Thiessen, “ICT-based health information services for elderly people: Past experiences, current trends, and future strategies,” Medical Informatics and the Internet in Medicine, Vol.32, No.4, pp. 251-261, 2007.
  4. [4] H. J. Lee, S. H. Lee, K.-S. Ha, H. C. Jang, W.-Y. Chung, J. Y. Kim, Y.-S. Chang, and D. H. Yoo, “Ubiquitous healthcare service using Zigbee and mobile phone for elderly patients,” Int. J. of Medical Informatics, Vol.78, No.3, pp. 193-198, 2009.
  5. [5] T. Koike, T. Fukaya, K. Nonaka, E. Kobayashi, M. Nishi, Y. Murayama, R. Watanabe, S. Shinkai, and Y. Fujiwara, “Usage conditions and intentions to use monitoring services for the elderly living alone,” Japanese J. of Public Health, Vol.60, No.5, pp. 285-293, 2013 (in Japanese).
  6. [6] P. Rashidi and A. Mihailidis, “A Survey on Ambient-Assisted Living Tools for Older Adults,” IEEE J. of Biomedical and Health Informatics, Vol.17, No.3, pp. 579-590, 2013.
  7. [7] L. Liu, E. Stroulia, I. Nikolaidis, A. Miguel-Cruz, and A. R. Rincon, “Smart Homes and Home Health Monitoring Technologies for Older Adults: A Systematic Review,” Int. J. of Medical Informatics, Vol.91, pp. 44-59, 2016.
  8. [8] K. Fujiwara, H. Fujii, and K. Mitobe, “Using Finger Dexterity in Elderly and Younger People to Detect Cognitive Decline,” J. Adv. Comput. Intell. Intell. Inform., Vol.21, No.2, pp. 330-336, 2017.
  9. [9] K. Fujiwara, H. Kano, and K. Mitobe, “Proposal for the dual-task assessment using drawing and counting test in elderly and young people,” The Trans. of Human Interface Society, Vol.19, No.1, pp. 25-29, 2017 (in Japanese).
  10. [10] Y. Fujiwara, H. Suzuki et al., “Brief screening tool for mild cognitive impairment in older Japanese: Validation of the Japanese version of the Montreal Cognitive Assessment,” Geriatrics and Gerontology Int., Vol.10, No.3, pp. 225-232, 2010.
  11. [11] P. Trouillas, T. Takayanagi et al., “International Cooperative Ataxia Rating Scale for Pharmacological Assessment of the Cerebellar Syndrome ,” J. of the Neurological Sciences, Vol.145, No.2, pp. 205-211, 1997.
  12. [12] J. D. Schmahmann, R. Gardner, J. MacMore, and M. G. Vangel, “Development of a Brief Ataxia Rating Scale (BARS) Based on a Modified Form of the ICARS,” Movement Disorders, Vol.24, No.12, pp. 1820-1828, 2009.
  13. [13] J. Westin, S. Ghiamati, M. Memedi et al., “A new computer method for assessing drawing impairment in Parkinson’s disease,” J. of Neuroscience Methods, Vol.190, No.1, pp. 143-148, 2010.
  14. [14] M. E. Isenkul, B. E. Sakar, and O. Kursun, “Improved spiral test using digitized graphics tablet for monitoring Parkinson’s disease,” The 2nd Int. Conf. on E-Health and Telemedicine (ICEHTM) 2014, pp. 171-175, 2014.
  15. [15] T. Yoshii, Y. Matsumoto, S. Hirakawa et al., “A basic study of tremor evaluation system development using spiral drawing task,” IEICE Technical Report, Vol.105, No.304, MBE2005-67, pp. 47-50, 2005 (in Japanese).
  16. [16] M. Yamada, S. Murata, H. Otao, and J. Murata, “Attention Function is Involved in Walking Ability Under the Dual-Task Condition among the Elderly People Living in the Community,” Japanese J. of Physical Therapy Science, Vol.23, No.3, pp. 435-439, 2008 (in Japanese).
  17. [17] Y. Yokokawa, A. Soyano, and I. Kai, “Dual-task gait performance among healthy elderly community dwellers,” Japanese J. of Public Health, Vol.60, No.1, pp. 30-36, 2014 (in Japanese).
  18. [18] A. Tsuboi, M. Monma, Y. Kono, Y. Nakamura, M. Arai, T. Hayashi, and M. Onuki, “Relationship Between Hand Dexterity and Cognitive Function in Healthy People,” J. of Health and Welfare Statistics, Vol.60, No.1, pp. 10-16, 2013 (in Japanese).
  19. [19] J.-Y. Yoon, T. Okura, K. Tsunoda, T. Tsuji, Y. Kohda, Y. Mitsuishi, C. Hasegawa, and H. Kim, “Relationship Between Cognitive Function and Physical Performance in Older Adults,” Japanese J. of Physical Fitness and Sports Medicine, Vol.59, No.3, pp. 313-322, 2010 (in Japanese).
  20. [20] Z. S. Nasreddine, N. A. Phillips, V. Bédirian, S. Charbonneau, V. Whitehead, I. Collin, J. L. Cummings, and H. Chertkow, “The Montreal Cognitive Assessment, MoCA: A Brief Screening Tool For Mild Cognitive Impairment,” J. of the American Geriatrics Society, Vol.53, No.4, pp. 695-699, 2005.
  21. [21] H. Chertkow, Z. Nasreddine, E. Johns, N. Phillips, and C. McHenry, “The Montreal cognitive assessment (MoCA): Validation of alternate forms and new recommendations for education corrections,” Alzheimer’s & Dementia, The J. of the Alzheimer’s Association, Vol.7, No.4, p. S157, 2011.
  22. [22] A. S. Costa, B. Fimm, P. Friesen, H. Soundjock, C. Rottschy, T. Gross, F. Eitner, A. Reich, J. B. Schulz, Z. S. Nasreddine, and K. Reetz, “Alternate-Form Reliability of the Montreal Cognitive Assessment Screening Test in a Clinical Setting,” Dementia and Geriatric Cognitive Disorders, Vol.33, No.6, pp. 379-384, 2012.
  23. [23] E. Lebedeva, M. Huang, and L. Koski, “Comparison of Alternate and Original Items on the Montreal Cognitive Assessment,” Canadian Geriatrics J., Vol.19, No.1, pp. 15-18, 2016.

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Last updated on Nov. 19, 2019