CLASSIFICATION OF NEURODEGENERATIVE DISEASES BASED ON GAIT ANALYSIS

Authors

  • Vuk Milosavljević Autor

DOI:

https://doi.org/10.24867/26RB01Milosavljevic

Keywords:

Neurodegenerative disease, machine learning, classification

Abstract

This paper describes the profiles of some of the most well-known neurodegenerative diseases. A machine learning model is outlined that could aid in the diagnosis and monitoring of the progression of neurodegenerative diseases. The importance of reduction dimensionality in the process of forming the machine learning model is particularly emphasized. The performances of several standard classifiers are tested to classify neurodegenerative diseases based on gait, which shows the potential to replace regular hospital tests for monitoring disease progression, which can be burdensome for both patients and hospitals.

References

[1] Harvey Checkoway, Jessica I. Lundin, and Samir N. Kelada. Neurodegenerative diseases. Chapter 22
[2] Rashad Hussain, Hira Zubair, Sarah Pursell. Neurodegenerative diseases: Regenerative Mechanisms and Novel Therapeutic Approches.
DOI: https://doi.org/10.3390/brainsci8090177
[3] Jeffrey M. Hausdorff, Apinya Lertratanakul, Merit E. Cudkowicz, Amie L. Peterson. Dinamyc markers of altered gait rhytm in amyotrophic lateral sclerosis.
[4] Nosek Tijana, Brkljač Branko, Despotović Danica, Sečujski Milan, Lončar-Turukalo Tatjana - Praktikum iz mašinskog učenja.

Published

2024-05-07