Design and application of a smart diagnostic system for parkinson's patients using machine learning
Yükleniyor...
Dosyalar
Tarih
2019
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SCIENCE & INFORMATION SAI ORGANIZATION LTD
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
For analysis of Parkinson illness gait disabilities detection is essential. The only motivation behind this examination is to equitably and consequently differentiate among sound subjects and the one who is forbearing the Parkinson, utilizing IOT based indicative framework. In this examination absolute, 16 distinctive force sensors being attached with the shoes of subjects which documented the Multisignal Vertical Ground Reaction Force (VGRF). Overall sensors signals utilizing 1024 window estimate around the raw signals, utilizing the Packet wavelet change (PWT) five diverse characteristics that includes entropy, energy, variance, standard deviation and waveform length were derived and support vector machine (SVM) is to recognize Parkinson patients and healthy subjects. SVM is trained on 85% of the dataset and tested on 15% dataset. Preparation accomplice relies upon 93 patients with idiopathic PD (mean age: 66.3 years; 63% men and 37% ladies), and 73 healthy controls (mean age: 66.3 years; 55% men and 45% ladies). IOT framework included all 16 sensors, from which 8 compel sensors were appended to left side foot of subject and the rest of the 8 on the right side foot. The outcomes demonstrate that fifth sensor worn on a Medial part of the dorsum of right foot highlighted by R5 gives 903% accuracy. Henceforth this examination gives the knowledge to utilize single wearable force sensor. Hence, this examination deduce that a solitary sensor might help in differentiation amongst Parkinson and healthy subjects.
Açıklama
Anahtar Kelimeler
Parkinson patients, force sensors, machine learning, Wavelet Packet Transform (WPT)
Kaynak
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
10
Sayı
6
Künye
Channa, A., Baqai, A., Ceylan, R. Design and Application of a Smart Diagnostic System for Parkinson’s Patients using Machine Learning. International Journal of Advanced Computer Science and Applications, 10(6), 563-571.
