Intelligent IoT Framework for Indoor Healthcare Monitoring of Parkinson’s Disease Patient

Raza, Mohsin; Awais, Muhammad; Singh, Nishant; Imran, Muhammad; Hussain, Sajjad

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. Index Terms-Internet of things (IoT), machine learning, Parkinson's disease, probability of blocking, low latency, priority communications.

Citation

Raza, M., Awais, M., Singh, N., Imran, M., & Hussain, S. (2021). Intelligent IoT Framework for Indoor Healthcare Monitoring of Parkinson’s Disease Patient. IEEE Journal on Selected Areas in Communications, 39(2), 593-602. https://doi.org/10.1109/jsac.2020.3021571

• Journal Article Type: Article
• Acceptance Date: Apr 16, 2020
• Online Publication Date: Sep 3, 2020
• Publication Date: 2021-02
• Deposit Date: May 3, 2020
• Publicly Available Date: May 15, 2020
• Journal: IEEE Journal on Selected Areas in Communications
• Print ISSN: 0733-8716
• Electronic ISSN: 1558-0008
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 2
• Pages: 593-602
• DOI: https://doi.org/10.1109/jsac.2020.3021571
• Keywords: Internet of things (IoT); Machine learning; Parkinson’s disease; Probability of blocking; Low latency; Priority communications
• Public URL: https://hull-repository.worktribe.com/output/3503108
• Publisher URL: https://ieeexplore.ieee.org/document/9186157
• Related Public URLs: http://eprints.gla.ac.uk/214621/