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Classification of Methods to Reduce Clinical Alarm Signals for Remote Patient Monitoring: A Critical Review by Arora, Teena; Balasubramanian, Venki; Stranieri, Andrew; Mai, Shenhan; Buyya, Rajkumar; Islam, Sardar is a scholarly article available to read on EtoBox.

What is Classification of Methods to Reduce Clinical Alarm Signals for Remote Patient Monitoring: A Critical Review about?

Remote Patient Monitoring (RPM) is an emerging technology paradigm that helps reduce clinician workload by automated monitoring and raising intelligent alarm signals. High sensitivity and intelligent data-processing algorithms used in RPM devices result in frequent false-positive alarms, resulting in alarm fatigue. This study aims to critically review the existing literature to identify the causes of these false-positive alarms and categorize the various interventions used in the literature to eliminate these causes. That act as a catalog and helps in false alarm reduction algorithm design. A step-by-step approach to building an effective alarm signal generator for clinical use has been proposed in this work. Second, the possible causes of false-positive alarms amongst RPM applications were analyzed from the literature. Third, a critical review has been done of the various interventions used in the literature depending on causes and classification based on four major approaches: clinical knowledge, physiological data, medical sensor devices, and clinical environments. A practical clinical alarm strategy could be developed by following our pentagon approach. The first phase of this

Author

Arora, Teena; Balasubramanian, Venki; Stranieri, Andrew; Mai, Shenhan; Buyya, Rajkumar; Islam, Sardar

Published

2023

Language

EN