global-journal-of-research-in-engineering Global Journal of Research in Engineering 0975-5861 2249-4596 Global Journals Publishing Group Incorporated 83496 Models and Algorithms for the Diagnosis of Parkinsons Disease and Their Realization on the Internet of Things Network IoT and FCNN for Early Parkinson's Voice Diagnosis Uladzimir, Vishniakou Yiwei, Xia BELARUS, Belarusian State University 26 11 2024 24 J1 43 49

This article aims to investigate an innovative approach utilizing model, algorithms and IoT technology for early Parkinson’s disease detection. It introduces the comprehensive IoT network that has the IoT platform, enabling the collection of voice data via mobile phones, extraction of relevant features and data processing. Within this process, a Fully Connected Neural Network (FCNN) model is employed to calculate the probability of Parkinson’s disease, potentially providing healthcare professionals and patients with a convenient, accurate, and early diagnostic tool. The study delves into the structure, algorithms, and the integral role of the FCNN within the IoT network, emphasizing its potential impact on the healthcare sector.

 parkinson's disease IoT technology early detection voice data noise reduction fully connected neural network IT-diagnosis. Full Text

This article aims to investigate an innovative approach utilizing model, algorithms and IoT technology for early Parkinson's disease detection. It introduces the comprehensive IoT network that has the IoT platform, enabling the collection of voice data via mobile phones, extraction of relevant features and data processing. Within this process, a Fully Connected Neural Network (FCNN) model is employed to calculate the probability of Parkinson's disease, potentially providing healthcare professionals and patients with a convenient, accurate, and early diagnostic tool. The study delves into the structure, algorithms, and the integral role of the FCNN within the IoT network, emphasizing its potential impact on the healthcare sector.