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Cited by 263

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Energy Harvesting For Wearable Devices: A Review

Chong, Yung-Wey, Ismail, Widad, Ko, Kwangman, Lee, Chen-Yi·2019·IEEE Sensors Journal

Abstract

In recent years, wearable devices have attracted attention because of their ability to enhance the quality of life. This disruptive technology has helped healthcare professionals with intervening early in chronic diseases, especially amongst independently living patients, and has facilitated real-time monitoring of patients' vital signs remotely. One of the major bottlenecks that hamper the adoption of wearable device is the continuous power supply. Most wearable devices solely depend on battery supply. When the energy stored in the battery is depleted, the operation of wearable devices is affected. To overcome this limitation, efficient energy harvesters for wearable devices are crucial. The paper primarily aims to present a comprehensive classification of different energy sources that can be capitalized to power wearable devices. In addition, this research paper deals with the key challenges that must be considered in the development of autonomous wearable devices for telemedicine applications with a proposed system design for wearable device that uses energy harvesting technology.

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Metadata

Authors
Chong, Y.-W., Ismail, W., Ko, K., & Lee, C.-Y.
Venue
IEEE Sensors Journal
Published
2019-10-15
Volume
19
Issue
20
Pages
9047-9062
ISSN
  • 1530-437X (ISSN-L)
  • 1558-1748
  • 2379-9153
OpenAlex
W2953521434
Cited by
263
References
6
FWCI
10.75
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Energy Harvesting For Wearable Devices: A Review. https://app.cochat.ai/papers/10.1109/jsen.2019.2925638
The paper
Chong, Y.-W., Ismail, W., Ko, K., & Lee, C.-Y. (2019). Energy Harvesting For Wearable Devices: A Review. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2019.2925638

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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