Many people in the world are living with chronic diseases, demanding continuous monitoring, diagnosis, and treatment. Continuous physiological monitoring is key to providing preventive healthcare and accurate disease diagnosis, which leads to a growing demand for autonomous wearable technology. Wearable devices acquiring physiological information from the patient demand high-power efficiency to operate in a continuous acquisition mode. While power-saving techniques are applied in wearable devices for many application, very few are considered for biomedical applications. In this work, we explore existing techniques of power reduction for wearable medical devices. Our analysis addresses the power reduction of wearable medical devices and their generalization for different medical signal processing applications. In addition, we propose a taxonomy for power-saving techniques. The common categories of power-saving techniques are task scheduling, clock management, signal compression, and energy awareness. The presented analysis identifies the most appropriate and combined low-power techniques in wearable devices to reduce power consumption.
Gudisa, WT, da Silva, B, Hora, WJ & Stiens, J 2022, Power Saving Techniques for Wearable Devices in Medical Applications. in Power Saving Techniques for Wearable Devices in Medical Applications. IECON Proceedings (Industrial Electronics Conference), vol. 2022-October, IEEE, pp. 1-8, 48th Annual Conference of the IEEE Industrial Electronics Society, Brussels, Belgium, 17/10/22. https://doi.org/10.1109/IECON49645.2022.9968977
Gudisa, W. T., da Silva, B., Hora, W. J., & Stiens, J. (2022). Power Saving Techniques for Wearable Devices in Medical Applications. In Power Saving Techniques for Wearable Devices in Medical Applications (pp. 1-8). (IECON Proceedings (Industrial Electronics Conference); Vol. 2022-October). IEEE. https://doi.org/10.1109/IECON49645.2022.9968977
@inproceedings{49eb13f0436a40c296fea4413ea20241,
title = "Power Saving Techniques for Wearable Devices in Medical Applications",
abstract = "Many people in the world are living with chronic diseases, demanding continuous monitoring, diagnosis, and treatment. Continuous physiological monitoring is key to providing preventive healthcare and accurate disease diagnosis, which leads to a growing demand for autonomous wearable technology. Wearable devices acquiring physiological information from the patient demand high-power efficiency to operate in a continuous acquisition mode. While power-saving techniques are applied in wearable devices for many application, very few are considered for biomedical applications. In this work, we explore existing techniques of power reduction for wearable medical devices. Our analysis addresses the power reduction of wearable medical devices and their generalization for different medical signal processing applications. In addition, we propose a taxonomy for power-saving techniques. The common categories of power-saving techniques are task scheduling, clock management, signal compression, and energy awareness. The presented analysis identifies the most appropriate and combined low-power techniques in wearable devices to reduce power consumption.",
keywords = "Power Optimization, Power Saving Techniques, Continuous Monitoring, Medical applications, Wearable medical devices.Power Optimization, Power Saving Techniques, Medical applications, Continuous Monitoring, Wearable medical devices",
author = "Gudisa, {Workineh Tesema} and {da Silva}, Bruno and Hora, {Worku Jimma} and Johan Stiens",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE. Copyright: Copyright 2022 Elsevier B.V., All rights reserved.; 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 ; Conference date: 17-10-2022 Through 20-10-2022",
year = "2022",
month = dec,
day = "9",
doi = "10.1109/IECON49645.2022.9968977",
language = "English",
isbn = "978-1-6654-8026-0",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "IEEE",
pages = "1--8",
booktitle = "Power Saving Techniques for Wearable Devices in Medical Applications",
url = "https://iecon2022.org/",
}