EN
IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS
Öz
Parkinson's is a neurodegenerative disease that, as in the case of other neurodegenerative diseases, has disruptive effects on human mobility. In this study, gait markers were obtained by using sensors under the foot, giving an output proportional to the force. Normal gait markers were compared with those of Parkinson’s patients. Thus, individuals with Parkinson's were identified by comparing the impulse model of gait markers obtained from normal individuals with those of Parkinson's patients.
Anahtar Kelimeler
Kaynakça
- [1] Beal, M.F., Lang, A.E., Ludolph, A.C., Neurodegenerative Diseases: Neurobiology, Pathogenesis and Therapeutics, Cambridge University Pres, . London, UK, 2005.
- [2] Galimberti, D., Scarpini, E., Neurodegenerative Diseases: Clinical Aspects, Molecular Genetics and Biomarkers, Springer London, 2014.
- [3] Yalcın S., Ozaras N., Gait Analysis, Avrupa Publications, Istanbul, 2001 (inTurkish).
- [4] Whittle, M.W., Gait Analysis: An Introduction, Butterworth-Heinemann, Waltham, 2007.
- [5] Gabel, M. , Gilad-Bachrach, R., Renshaw, E., Schuster, A. (2012), Full Body Gait Analysis with Kinect, Engineering in Medicine and Biology Society (EMBC), Annual International Conference of the IEEE, San Diego, CA
- [6] Hausdorff, J.M., Mitchell, S.L., Firtion, R., Peng, C.K., Cudkowicz, M.E., Wei, J.Y., Goldberger. A.L. (1997). Altered fractal dynamics of gait: reduced stride-interval correlations with aging and Huntington's disease. J. Applied Physiology, 82, 262-269.
- [7] Hausdorff, J.M., Lertratanakul, A., Cudkowicz, M.E., Peterson, A.L., Kaliton, D., Goldberger, A.L. (2000). Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis. J. Applied Physiology, 88, 2045-2053.
- [8] Budzianowska, A, Honczarenko, K. (2008). Assessment of rest tremor in Parkinson’s disease, Polish J. Neurol. Neurosurg., 42, 12 -21 .
Ayrıntılar
Birincil Dil
İngilizce
Konular
Elektrik Mühendisliği
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
1 Haziran 2020
Gönderilme Tarihi
28 Ocak 2020
Kabul Tarihi
10 Mayıs 2020
Yayımlandığı Sayı
Yıl 2020 Cilt: 10 Sayı: 1
APA
Akgün, Ö., & Akan, A. (2020). IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS. European Journal of Technique (EJT), 10(1), 153-159. https://doi.org/10.36222/ejt.681232
AMA
1.Akgün Ö, Akan A. IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS. EJT. 2020;10(1):153-159. doi:10.36222/ejt.681232
Chicago
Akgün, Ömer, ve Aydın Akan. 2020. “IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS”. European Journal of Technique (EJT) 10 (1): 153-59. https://doi.org/10.36222/ejt.681232.
EndNote
Akgün Ö, Akan A (01 Haziran 2020) IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS. European Journal of Technique (EJT) 10 1 153–159.
IEEE
[1]Ö. Akgün ve A. Akan, “IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS”, EJT, c. 10, sy 1, ss. 153–159, Haz. 2020, doi: 10.36222/ejt.681232.
ISNAD
Akgün, Ömer - Akan, Aydın. “IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS”. European Journal of Technique (EJT) 10/1 (01 Haziran 2020): 153-159. https://doi.org/10.36222/ejt.681232.
JAMA
1.Akgün Ö, Akan A. IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS. EJT. 2020;10:153–159.
MLA
Akgün, Ömer, ve Aydın Akan. “IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS”. European Journal of Technique (EJT), c. 10, sy 1, Haziran 2020, ss. 153-9, doi:10.36222/ejt.681232.
Vancouver
1.Ömer Akgün, Aydın Akan. IDENTIFICATION OF PARKINSON’S DISEASE BY AR MODELLING OF GAIT SIGNALS. EJT. 01 Haziran 2020;10(1):153-9. doi:10.36222/ejt.681232