A smartphone-based tool for assessing parkinsonian hand tremor

IEEE Journal of Biomedical and Health Informatics

Volumn 19, Issue 6, 2015, Pages 1835-1842

  Kostikis, N ^a   Hristu Varsakelis, D ^a   Arnaoutoglou, M ^b   Kotsavasiloglou, C ^b  

^a UNIVERSITY OF MACEDONIA   (Greece)

^b ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

Accelerometer; Bootstrap aggregation decision tree; Gyroscope; Machine learning; Parkinson's disease; Smartphone; Tremor quantification

Indexed keywords

ACCELEROMETERS; DECISION TREES; GYROSCOPES; LEARNING SYSTEMS; MACHINE LEARNING; NEURODEGENERATIVE DISEASES;

CLINICAL EXAMINATION; CLINICAL STUDY; HAND TREMORS; HEALTHY VOLUNTEERS; MACHINE LEARNING TECHNIQUES; PARKINSON'S DISEASE; PLATFORM INDEPENDENT; TREMOR QUANTIFICATION;

SMARTPHONES;

ACCELEROMETRY; AGED; CLUSTER ANALYSIS; DEVICES; FEMALE; HAND; HUMAN; MACHINE LEARNING; MALE; MIDDLE AGED; MOBILE APPLICATION; PARKINSON DISEASE; PATHOPHYSIOLOGY; PHYSIOLOGIC MONITORING; PHYSIOLOGY; PROCEDURES; SMARTPHONE; TREMOR; VERY ELDERLY;

ACCELEROMETRY; AGED; AGED, 80 AND OVER; CLUSTER ANALYSIS; FEMALE; HAND; HUMANS; MACHINE LEARNING; MALE; MIDDLE AGED; MOBILE APPLICATIONS; MONITORING, PHYSIOLOGIC; PARKINSON DISEASE; SMARTPHONE; TREMOR;

EID: 84959223978     PISSN: 21682194     EISSN: 21682208     Source Type: Journal    
DOI: 10.1109/JBHI.2015.2471093     Document Type: Article

References (25)

1. S. K. Van Den Eeden, C. M. Tanner, A. L. Bernstein, R. D. Fross, A. Leimpeter, D. A. Bloch, and L. M. Nelson, "Incidence of Parkinson's disease: Variation by age, gender, and race/ethnicity, " Amer. J. Epidemiology, vol. 157, pp. 1015-1022, 2003.
2. E. R. Kandel, J. H. Schwartz, and T. M. Jessell, Principles of Neural Science. New York, NY, USA: McGraw-Hill, 2000.
3. C. G. Goetz, S. Fahn, P. Martinez-Martin, W. Poewe, C. Sampaio, G. T. Stebbins, M. B. Stern, B. C. Tilley, R. Dodel, B. Dubois, R. Holloway, J. Jankovic, J. Kulisevsky, A. E. Lang, A. Lees, S. Leurgans, P. A. LeWitt, D. Nyenhuis, C. W. Olanow, O. Rascol, A. Schrag, J. A. Teresi, J. J. Van Hilten, and N. LaPelle, "Movement disorder society-sponsored revision of the unified parkinson's disease rating scale (MDS-UPDRS): Process, format, and clinimetric testing plan, " Movement Disorders, vol. 22, no. 1, pp. 41-47, Jan. 2007.
4. T. Ellis, J. T. Cavanaugh, G. M Earhart, M. P. Ford, K. B. Foreman, and L. E. Dibble, "Which measures of physical function and motor impairment best predict quality of life in Parkinson's disease?, " Parkinsonism Relat Disorders, vol. 17, pp. 693-697, 2011.
5. S. Patel, K. Lorincz, R. Hughes, N. Huggins, J. Growdon, D. Standaert, M. Akay, J. Dy, M. Welsh, and P. Bonato, "Monitoring motor fluctuations in patients with Parkinson's disease using wearable sensors, " IEEE Trans. Inform. Technol. Biomed., vol. 13, no. 6, pp. 864-873, Nov. 2009.
6. K. Lorincz, B. R. Chen, G. W. Challen, At. R. Chowdhury, S. Patel, P. Bonato, and M. Welsh, "Mercury: A wearable sensor network platform for high-fidelity motion analysis, " presented at the 7th ACM Conf. Embedded Networked Sensor Systems, Berkeley, CA, USA, Nov. 2009.
7. A. Weiss, S. Sharifi, M. Plotnik, J. P. Van Vugt, N. Giladi, and J. M. Hausdorff, "Toward automated, at-home assessment of mobility among patients with Parkinson disease, using a body-worn accelerometer, " Neuro-Rehabil. Neural Repair, vol. 25, pp. 810-818, 2011.
8. R. LeMoyne, T. Mastroianni, and W. Grundfest, "Wireless accelerometer configuration for monitoring Parkinson's disease hand tremor, " Advances Parkinson's Disease, vol. 2, no. 2, pp. 62-67, 2013.
9. J. Klucken, J. Barth, P. Kugler, J. Schlachetzki, T. Henze, F. Marxreiter, Z. Kohl, R. Steidl, J. Hornegger, B. Eskofier, and J. Winkler "Unbiased and mobile gait analysis detects motor impairment in Parkinson's disease, " PLOS ONE, vol. 8, no. 2, p. e56956, 2013.
10. R. LeMoyne, T. Mastroianni, M. Cozza, C. Coroian, and W. Grundfest, "Implementation of an iPhone for characterizing Parkinson's disease tremor through a wireless accelerometer application, " presented at the 32nd Int. Conf. Engineering Medicine Biology Society, Buenos Aires, Argentina, 2010.
11. R. Delano, B. Parise, and L. West, "iTrem, " in Proc. Int. Conf. Health Informat., Rome, Italy, 2011, pp. 26-29.
12. J. F. Daneault, B. Carignan, C. É. Codère, A. F. Sadikot, and C. Duval, "Using a smart phone as a standalone platform for detection and monitoring of pathological tremors, " Frontiers Human Neurosci., vol. 6, p. 357, 2013.
13. E. Ozdalga, A. Ozdalga, and N. Ahuja, "The smartphone in medicine: A review of current and potential use among physicians and students, " J. Med. Internet Res., vol. 14, no. 5, p. e128, 2012.
14. [Online]. Available: http://afroditi.uom.gr/itremorsense.
15. N. Kostikis, D. Hristu-Varsakelis, M. Arnaoutoglou, C. Kotsavasiloglou, and S. Baloyiannis, "Towards remote evaluation of movement disorders via smartphones, " in Proc. IEEE 33rd Int. Conf. Eng. Med. Biol. Soc., Boston, MA, USA, 2011, pp. 5240-5243.
16. N. Kostikis, D. Hristu-Varsakelis, M. Arnaoutoglou, and C. Kotsavasiloglou, "Smartphone-based evaluation of Parkinsonian hand tremor: Quantitative measurements vs clinical assessment scores, " in Proc. IEEE 36th Int. Conf. Eng. Med. Biol. Soc., Chicago, IL, USA, 2014, pp. 906-909.
17. J. Barth, J. Klucken, P. Kugler, T. Kammerer, R. Steidl, J. Winkler, J. Hornegger, and B. Eskofier, "Biometric and mobile gait analysis for early diagnosis and therapy monitoring in Parkinson's disease, " in Proc. IEEE 33rd Int. Conf. Eng. Med. Biol. Soc., Boston, MA, USA, 2011, pp. 868-871.
18. M. Brunato, R. Battiti, D. Pruitt, and E. Sar. (2013). Supervised and unsupervised machine learning for the detection, monitoring and management of Parkinson's disease from passive mobile phone data. Submission for the M. J. Fox Foundation Competition: Predicting Parkinson's Disease Progression With Smartphone Data. [Online]. Available: https://kaggle2.blob.core.windows.net/prospectorfiles/1117/958625cf-3514-4e64-b0e7-13ebd3cf9791/kaggle.pdf
19. S. Arora, V. Venkataraman, S. Donohue, K. M. Biglan, E. R. Dorsey, and M. A. Little, "High accuracy discrimination of Parkinson's disease participants from healthy controls using smartphones, " presented at the IEEE Int. Conf. Acoustics, Speech Signal Processing, Florence, Italy, 2014.
20. S. Fahn, "Classification of movement disorders, " Movement Disorders, vol. 26, pp. 947-957, 2011.
21. X. Wu, V. Kumar, J. R. Quinlan, J. Ghosh, Q. Yang, H. Motoda, G. J. McLachlan, A. Ng, B. Liu, P. S. Yu, Z. H. Zhou, M. Steinbach, D. J. Hand, and D. Steinberg, "Top 10 algorithms in data mining, " Knowl. Inf. Syst., vol. 14, pp. 1-37, 2007.
22. L. Breiman, "Random forests, " Mach. Learning, vol. 45, no. 1, pp. 5-32, 2001.
23. J. Novakovic, "The impact of feature selection on the accuracy of Naïve Bayes classifier, " presented at the Proc. 18th Telecommunications Forum, Belgrade, Sebia, 2010.
24. Apple-ResearchKit. [Online]. Available: https://www.apple.com/researchkit/.
25. M. A. Hall, "Correlation-based feature selection for machine learning, " Ph. D. dissertation, Dept. Comput. Sci., Univ. Waikato, Hamilton, New Zealand, 1999.