Akademik Veri Yönetim Sistemi
10th International Conference on Image Processing, Wavelet and Applications (IWW2019), Kocaeli, Türkiye, 18 - 20 Ekim 2019, ss.58
Machine Learning is used in many areas around the world, including the
healthcare industry.It can play an essential role in predicting the presence/absence
of neurodegenerative disorder. If this information is well predicted, it may help
doctors to treat patients. Parkinson’s Disease is a worldwide health problem,
causing movement disorder and gait deficiencies. In this study, walking force
signals from the force sensitive receptors were used to separate one of the neurodegenerative Parkinson’s Disease (PD) from the normal individual. These signals
were first separated by the Daubechies 4 (db4) wavelet transform to the seventh
level. Then peak analysis was performed on the seventh level approximation
signal to find out the local maxima of the signal, the peak positions of these local
maxima, peak widths, and peaks. Then, two basic statistical characteristics were
obtained from each of these four peak features. So, a total of 16 attributes were
obtained, 8 for the left foot, and 8 for the right foot. After this stage, training data
was generated by using 50% of the data of each subject. In the next step, 87.1%
accuracy was obtained for determination of PD using the J48 algorithm.