Application of Wavelet Leader Based Analysis to characterize different neurodegenerative disease
Tahmineh Azizi- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Geriatrics and Gerontology
- Neurology (clinical)
- Developmental Neuroscience
- Health Policy
- Epidemiology
Abstract
Background
Neuro‐degenerative diseases influence significantly the gait behavior and the ability to move.
Method
To explore the etiology of neuro‐degenerative disease, it would be useful to characterize gait dynamics. The purpose of this study is to classify different neuro‐degenerative diseases using fractal geometry.
Result
We noticed that neither SPD nor FD alone were sufficient to separate different classes of patients and healthy people. In addition, when WLM and scaling exponent were used as a classifier, the three classes could not be well separated. However, this study revealed that we have a wide range of exponents for some of the recordings which indicates they have multifractal structure and need to be indexed by different exponents as decomposed into different subsets. In other words, these multifractal subjects require much more exponents to characterize their scaling properties compared to monofractal gait recordings which their spectrum displays a narrow width of scaling exponent.
Conclusion
Although SPD, FD and WLM may not be able to classify gait recordings, however, they can be used as comprehensive frameworks to characterize the fractal behavior of gait recordings of different neuro‐degenerative diseases.