Remote Monitoring Model for the Preoperative Prehabilitation Program of Patients Requiring Abdominal Surgery

Khalid Al-Naime, Adnan Al-Anbuky and Grant Mawston
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Khalid Al-Naime: School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology (AUT), Auckland 1010, New Zealand
Adnan Al-Anbuky: School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology (AUT), Auckland 1010, New Zealand
Grant Mawston: Department of Physiotherapy, Auckland University of Technology (AUT), Auckland 0627, New Zealand

Future Internet, 2021, vol. 13, issue 5, 1-15

Abstract: Physical fitness and level of activity are considered important factors for patients with cancer undergoing major abdominal surgery. Cancer patients with low fitness capacity are at greater risk of postoperative complications, longer hospital stays, and mortality. One of the main challenges facing both healthcare providers and patients is to improve the patient’s physical fitness within the available short period (four to six weeks) prior to surgery. Supervised and unsupervised physical prehabilitation programs are the most common recommended methods for enhancing postoperative outcomes in patients undergoing abdominal surgery. Due to obstacles such as geographical isolation, many patients have limited access to medical centers and facilities that provide onsite prehabilitation programs. This article presents a review of the literature and the development of a model that can remotely monitor physical activities during the prehabilitation period. The mixed prehabilitation model includes the identification of fundamental parameters of physical activities (type, intensity, frequency, and duration) over time. A mathematical model has been developed to offer a solution for both the healthcare provider and patients. This offers the opportunity for physicians or physiotherapists to monitor patients performing their prescribed physical exercises in real time. The model that has been developed is embedded within the internet of things (IoT) system, which calculates the daily and weekly efforts made by the patients and automatically stores this in a comma-separated values (CSV) file that medical staff can access. In addition, this model allows the patient to compensate for missed prescribed activity by adding additional efforts to meet the prehabilitation requirements. As a result, healthcare staff are provided with feedback on patient engagement in prescribed exercise during the period of the prehabilitation program.

Keywords: internet of things; IOT; cancer patient prehabilitation; edge computing (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
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