Internet of Things Gateway Edge for Movement Monitoring in a Smart Healthcare System

Author:

Al-Naime Khalid1ORCID,Al-Anbuky Adnan1,Mawston Grant2

Affiliation:

1. School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand

2. Physiotherapy Department, Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland 1010, New Zealand

Abstract

Over the past two decades, there has been a notable and swift advancement in the field of healthcare with regards to the Internet of Things (IoT). This progress has brought forth a substantial prospect for healthcare services to enhance performance, transparency, and cost effectiveness. Internet of Things gateways, such as local computational facilities, mobile devices, or custom miniature computational embedded electronics like the Raspberry Pi (RPi), are crucial in facilitating the required processing and data compression tasks as well as serving as front-end event detectors. Numerous home-based healthcare monitoring systems are currently accessible; however, they have several limitations. This paper examines the role of the Raspberry Pi gateway in the healthcare system, specifically in the context of pre-operative prehabilitation programs (PoPPs). The IoT remote monitoring system employed a Microduino integrated with various supporting boards as a wearable device. Additionally, a Raspberry Pi was utilised as a base station or mobile gateway, while ThingSpeak served as the cloud platform. The monitoring system was developed with the purpose of assisting healthcare personnel in real time, remotely monitoring patients while engaging in one or more of the nine typical physical activities that are often prescribed to individuals participating in a prehabilitation program. Furthermore, an alert notification system was designed to notify the clinician and patient if the values were abnormal (i.e., the patient had not been active for many days). The integration of IOT and Raspberry Pi technology into a pre-operative prehabilitation program yielded a promising outcome with a success rate of 78%. Consequently, this intervention is expected to facilitate the resolution of challenges encountered by healthcare providers and patients, including extended waiting periods and constraints related to staffing and infrastructure.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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