Intelligent IoT Framework for indoor healthcare monitoring of Parkinson's Disease Patients

Raza, Mohsin, Awais, Muhammad, Singh, Nishant, Imran, Muhammad and Hussain, Sajjad (2020) Intelligent IoT Framework for indoor healthcare monitoring of Parkinson's Disease Patients. IEEE Journal on Selected Areas in Communications. ISSN 0733-8716 (In Press)

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Abstract

Parkinson’s disease is associated with high treatment costs, primarily attributed to the needs of hospitalization and frequent care services. A study reveals annual per-person healthcare costs for Parkinson’s patients to be 21,482, with an additional 29,695 burden to society. Due to the high stakes and rapidly rising Parkinson’s patients' count, it is imperative to introduce intelligent monitoring and analysis systems. In this paper, an Internet of Things (IoT) based framework is proposed to enable remote monitoring, administration, and analysis of patient’s conditions in a typical indoor environment. The proposed infrastructure offers both static and dynamic routing, along with delay analysis and priority enabled communications. The scheme also introduces machine learning techniques to detect the progression of Parkinson’s over six months using auditory inputs. The proposed IoT infrastructure and machine learning algorithm are thoroughly evaluated and a detailed analysis is performed. The results show that the proposed scheme offers efficient communication scheduling, facilitating a high number of users with low latency. The proposed machine learning scheme also outperforms state-of-the-art techniques in accurately predicting the Parkinson’s progression.

Item Type: Article
Uncontrolled Keywords: Internet of things (IoT), machine learning, Parkinson’s disease, probability of blocking, low latency, priority communications, ultra reliable low latency communications (urllc)
Subjects: A300 Clinical Medicine
B900 Others in Subjects allied to Medicine
G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 18 May 2020 10:28
Last Modified: 18 May 2020 10:30
URI: http://nrl.northumbria.ac.uk/id/eprint/43156

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