Intelligent IoT framework for indoor healthcare monitoring of Parkinson’s disease patient

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

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


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,withanadditional29,695 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.
Original languageEnglish
Article number9186157
Pages (from-to)593-602
Number of pages10
JournalIEEE Journal on Selected Areas in Communications
Issue number2
Early online date3 Sep 2020
Publication statusPublished - Feb 2021


  • Internet of Things (IoT)
  • Parkinson's disease
  • low latency
  • machine learning
  • priority communications
  • probability of blocking

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