A Taxonomy of Low-Power Techniques in Wearable Medical Devices for Healthcare Applications

Author:

Tesema Workineh12ORCID,Jimma Worku2ORCID,Khan Muhammad Iqbal1ORCID,Stiens Johan1ORCID,da Silva Bruno1ORCID

Affiliation:

1. Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussel, Belgium

2. Department of Information Science, Jimma University Institute of Technology, Jimma P.O. Box 378, Ethiopia

Abstract

Chronic diseases are the most prevalent and non-communicable health crisis globally. Most chronic disease patients require continuous physiological monitoring, using wearable technology for timely treatment, precise illness detection, and preventive healthcare. Nonetheless, efficient power management is required for such resource-constrained wearable devices. This work aims to analyze low-power techniques (LPTs) in wearable medical devices using a data-driven approach and identify novel approaches promising higher power savings. Through an intensive literature analysis, we identify the most relevant LPTs for minimizing power consumption in wearable devices for physiological monitoring while recognizing the barriers to adopting these techniques. As a result, a novel taxonomy based on the common characteristics of the LPTs is proposed, along with strategies for the combination of LPTs. Through our analysis, we propose possible enhancements in using LPTs and suggest mechanisms for the medical device industry to facilitate their adoption. Overall, our proposed strategies guide the use of LPTs on wearable medical devices toward continuous physiological monitoring.

Funder

NASCERE

Publisher

MDPI AG

Reference109 articles.

1. WHO (2024, June 03). Non Communicable Diseases. Available online: https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases.

2. Haque, A., Chowdhury, M.N.U.R., and Soliman, H. (July, January 30). Transforming Chronic Disease Management with Chatbots: Key Use Cases for Personalized and Cost-effective Care. Proceedings of the 2023 Sixth International Symposium on Computer, Consumer and Control (IS3C), Taichung, Taiwan.

3. Emergency situation monitoring service using context motion tracking of chronic disease patients;Kim;Clust. Comput.,2015

4. Continuous monitoring of Physiological parameters using PPG;Veerabhadrappa;Indian J. Sci. Technol.,2021

5. Godfrey, A., and Stuart, S. (2021). Digital Health: Exploring Use and Integration of Wearables, Academic Press.

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