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Development, Debugging, and Assessment of ParkinsonCheck Attributes Through Visualisation

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Health Monitoring and Personalized Feedback using Multimedia Data

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Abstract

Parkinson’s disease is estimated to affect between four and six million people over the age of 50 worldwide, and that number is expected to double by the year 2030. The disease often presents itself with a Parkinsonian tremor (PT) and other movement disorders and these symptoms can be similar to those of another disease, the essential tremor (ET)—the most prevalent movement disorder. Spirography is a method involving drawing, usually of spirals, which are then analysed for various distinguishing features to detect signs of various tremors. Spiral drawing as assessment of tremor is recommended by the Movement Disorder Society. This chapter describes the inner making of ParkinsonCheck, a mobile application for self-checking for signs of PT and ET. ParkinsonCheck uses digitalised spirography on smartphones and tablets to detect the signs. The chapter focuses primarily on spirography and the knowledge extraction, formulation, debugging, and assessment for ParkinsonCheck through the use of visualisation.

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Notes

  1. 1.

    A web service version is available at http://www.parkinsoncheck.net/pc.

References

  1. Alberio, T., & Fasano, M. (2011). Proteomics in parkinson’s disease: An unbiased approach towards peripheral biomarkers and new therapies. Journal of Biotechnology, 156(4), 325–337. Special issue: {IBS} 2010 - Industrial Biotechnology.

    Google Scholar 

  2. Alusi, S. H., Worthington, J., Glickman, S., Findley, L. J., & Bain, P. G. (2000). Evaluation of three different ways of assessing tremor in multiple sclerosis. Journal of Neurology, Neurosurgery & Psychiatry, 68(6), 756–760.

    Article  Google Scholar 

  3. Bain, P. G., & Findley, L. J. (1993). Assessing tremor severity: A clinical handbook. Standards in Neurology. London: Smith-Gordon.

    Google Scholar 

  4. Clark, P., & Boswell, R. (1991). Rule induction with CN2: Some recent improvements. In EWSL (pp. 151–163).

    Google Scholar 

  5. Deuschl, G., Bain, P., & Brin, M. (1998). Consensus statement of the movement disorder society on tremor. Movement Disorders, 13(S3), 2–23.

    Article  Google Scholar 

  6. Deuschl, G., Wenzelburger, R., Loffler, K., Raethjen, J., & Stolze, H. (2000). Essential tremor and cerebellar dysfunction clinical and kinematic analysis of intention tremor. Brain, 123(8), 1568–1580.

    Article  Google Scholar 

  7. Elble, R. J., Brilliant, M., Leffler, K., & Higgins, C. (1996). Quantification of essential tremor in writing and drawing. Movement Disorders, 11(1), 70–78.

    Article  Google Scholar 

  8. Elble, R. J., Sinha, R., & Higgins, C. (1990). Quantification of tremor with a digitizing tablet. Journal of Neuroscience Methods, 32(3),193–198.

    Article  Google Scholar 

  9. Feys, P., Helsen, W., Prinsmel, A., Ilsbroukx, S., Wang, S., & Liu, X. (2007). Digitised spirography as an evaluation tool for intention tremor in multiple sclerosis. Journal of Neuroscience Methods, 160(2), 309–316.

    Article  Google Scholar 

  10. Filipová, M., Filip, V., Macek, Z., Müllerová, S., Marková, J., Kás, S., et al. (1988.) Terguride in parkinsonism a multicenter trial. European Archives of Psychiatry and Neurological Sciences, 237(5), 298–303.

    Article  Google Scholar 

  11. Groznik, V., Guid, M., Sadikov, A., Možina, M., Georgiev, D., Kragelj, V., et al. (2013). Elicitation of neurological knowledge with argument-based machine learning. Artificial Intelligence in Medicine, 57(2), 133–144.

    Article  Google Scholar 

  12. Groznik, V., Sadikov, A., Možina, M., Žabkar, J., Georgiev, D., & Bratko, I. (2014). Attribute visualisation for computer-aided diagnosis: A case study. In Proceedings of 2014 IEEE International Conference on Healthcare Informatics (ICHI 2014) (pp. 294–299). IEEE Computer Society, US Conference Publishing Services.

    Google Scholar 

  13. Gustavsson, A., Svensson, M., Jacobi, F., Allgulander, C., Alonso, J., Beghi, E., et al. (2011). Cost of disorders of the brain in Europe 2010. European Neuropsychopharmacology, 21, 718–779.

    Article  Google Scholar 

  14. Hubble, J. P., Busenbark, K. L., Wilkinson, S., Penn, R. D., Lyons, K., & Koller, W. C. (1996). Deep brain stimulation for essential tremor. Neurology, 46(4), 1150–1153.

    Article  Google Scholar 

  15. Hughes, A. J., Daniel, S. E., Kilford, L., & Lees, A. J. (1992.) Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: A clinico-pathological study of 100 cases. Journal of Neurology, Neurosurgery, and Psychiatry, 55(3), 181–184.

    Article  Google Scholar 

  16. Jueptner, M., & Weiller, C. (1998). A review of differences between basal ganglia and cerebellar control of movements as revealed by functional imaging studies. Brain, 121(8), 1437–1449.

    Article  Google Scholar 

  17. Kraus, P. H., & Hoffmann, A. (2010). Spiralometry: Computerized assessment of tremor amplitude on the basis of spiral drawing. Movement Disorders, 25(13), 2164–2170.

    Article  Google Scholar 

  18. Liu, X., Carroll, C. B., Wang, S.-Y., Zajicek, J., & Bain, P. G. (2005). Quantifying drug-induced dyskinesias in the arms using digitised spiral-drawing tasks. Journal of Neuroscience Methods, 144(1), 47–52.

    Article  Google Scholar 

  19. Longstaff, M. G., & Heath, R. A. (2006). Spiral drawing performance as an indicator of fine motor function in people with multiple sclerosis. Human Movement Science, 25(45), 474–491; Advances in graphonomics: Studies on fine motor control, its development and disorders.

    Google Scholar 

  20. Louis, E. D., Yu, Q., Floyd, A. G., Moskowitz, C, & Pullman, S. L. (2006). Axis is a feature of handwritten spirals in essential tremor. Movement Disorders, 21(8), 1294–1295.

    Article  Google Scholar 

  21. Miralles, F., Tarong, S., & Espino, A. (2006). Quantification of the drawing of an archimedes spiral through the analysis of its digitized picture. Journal of Neuroscience Methods, 152(12), 18–31.

    Article  Google Scholar 

  22. Možina, M., Guid, M., Krivec, J., Sadikov, A., & Bratko, I. (2008). Fighting knowledge acquisition bottleneck with argument based machine learning. In M. Ghallab, C. D. Spyropoulos, N. Fakotakis & N. M. Avouris (Eds.), Proceedings of the 2008 Conference on ECAI 2008: 18th European Conference on Artificial Intelligence. Frontiers in Artificial Intelligence and Applications (Vol. 178, pp. 234–238). Amsterdam, The Netherlands: IOS Press.

    Google Scholar 

  23. Možina, M., Žabkar, J., & Bratko, I. (2007). Argument based machine learning. Artificial Intelligence, 171(10/15), 922–937.

    MATH  MathSciNet  Google Scholar 

  24. Murman, D. L. (2012). Early treatment of parkinson’s disease: Opportunities for managed care. American Journal of Managed Care, 18(7), 183–188.

    Google Scholar 

  25. Pahwa, R., & Lyons, K. E. (2003). Essential tremor: Differential diagnosis and current therapy. American Journal of Medicine, 115, 134–142.

    Article  Google Scholar 

  26. Pullman, S. L. (1998). Spiral analysis: A new technique for measuring tremor with a digitizing tablet. Movement Disorders, 13(S3), 85–89.

    Article  Google Scholar 

  27. Quinn, N. P., Schneider, S. A., Schwingenschuh, P., & Bhatia, K. P. (2011). Tremor-some controversial aspects. Movement Disorders, 26(1), 18–23.

    Article  Google Scholar 

  28. Sadikov, A., Žabkar, J., Možina, M., Groznik, V., Georgiev, D., & Bratko, I. (2014). Parkinsoncheck: A decision support system for spirographic testing. Technical report, University of Ljubljana, Faculty of Computer and Information Science.

    Google Scholar 

  29. Saunders-Pullman, R., Derby, C., Stanley, K., Floyd, A., Bressman, S., Lipton, R. B., et al. (2008). Validity of spiral analysis in early Parkinson’s disease. Movement Disorders, 23(4), 531–537.

    Article  Google Scholar 

  30. Stanley, K., Hagenah, J., Brggemann, N., Reetz, K., Severt, L., Klein, C., et al. Digitized spiral analysis is a promising early motor marker for parkinson disease. Parkinsonism and Related Disorders, 16(3), 233–234.

    Google Scholar 

  31. Thanvi, B., Lo, N., & Robinson, T. (2006). Essential tremor—the most common movement disorder in older people. Age and Ageing, 35(4), 344–349.

    Article  Google Scholar 

  32. World Health Organization (2008). The global burden of disease: 2004 update. WHO Press, World Health Organization, Geneva, Switzerland.

    Google Scholar 

  33. Towey, D. J., Bain, P. G., & Nijran, K. S. (2011). Automatic classification of 123I-FP-CIT (DaTSCAN) SPECT images. Nuclear Medicine Communications, 32(8), 699–707.

    Article  Google Scholar 

  34. Wang, H., Yu, Q., Kurtis, M. M., Floyd, A. G., Smith, W. A., & Pullman, S. L.(2008). Spiral analysis improved clinical utility with center detection. Journal of Neuroscience Methods, 171(2), 264–270.

    Article  Google Scholar 

  35. Westin, J., Ghiamati, S., Memedi, M., Nyholm, D., Johansson, A., Dougherty, M., et al. (2010). A new computer method for assessing drawing impairment in parkinson’s disease. Journal of Neuroscience Methods, 190(1), 143–148.

    Article  Google Scholar 

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Acknowledgements

The research was partly funded by Slovenian Research Agency (ARRS). The development of ParkinsonCheck was partly funded by Slovenian Ministry of Education, Science and Sport and European Regional Development Fund.

Author information

Authors and Affiliations

  1. Faculty of Computer and Information Science, University of Ljubljana, Večna pot 113, Ljubljana, Slovenia

    Vida Groznik, Martin Možina, Jure Žabkar, Ivan Bratko & Aleksander Sadikov

  2. Department of Neurology, University Medical Centre Ljubljana, Zaloška cesta 2, Ljubljana, Slovenia

    Dejan Georgiev

Authors
  1. Vida Groznik
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  2. Martin Možina
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  3. Jure Žabkar
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  4. Dejan Georgiev
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  5. Ivan Bratko
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  6. Aleksander Sadikov
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Corresponding author

Correspondence to Vida Groznik .

Editor information

Editors and Affiliations

  1. Centre for Research and Technology, Hellas, Information Technologies Institute, Thermi, Thessaloniki, Greece

    Alexia Briassouli

  2. Laboratoire Bordelais de Recherche en Informatique/University Bordeaux, Talence, France

    Jenny Benois-Pineau

  3. Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Alexander Hauptmann

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Groznik, V., Možina, M., Žabkar, J., Georgiev, D., Bratko, I., Sadikov, A. (2015). Development, Debugging, and Assessment of ParkinsonCheck Attributes Through Visualisation. In: Briassouli, A., Benois-Pineau, J., Hauptmann, A. (eds) Health Monitoring and Personalized Feedback using Multimedia Data. Springer, Cham. https://doi.org/10.1007/978-3-319-17963-6_4

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  • DOI: https://doi.org/10.1007/978-3-319-17963-6_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17962-9

  • Online ISBN: 978-3-319-17963-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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