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Unobtrusive Sensing and Wearable Devices for Health Informatics
Open accessAbstract
The aging population, prevalence of chronic diseases, and outbreaks of infectious diseases are some of the major challenges of our present-day society. To address these unmet healthcare needs, especially for the early prediction and treatment of major diseases, health informatics, which deals with the acquisition, transmission, processing, storage, retrieval, and use of health information, has emerged as an active area of interdisciplinary research. In particular, acquisition of health-related information by unobtrusive sensing and wearable technologies is considered as a cornerstone in health informatics. Sensors can be weaved or integrated into clothing, accessories, and the living environment, such that health information can be acquired seamlessly and pervasively in daily living. Sensors can even be designed as stick-on electronic tattoos or directly printed onto human skin to enable long-term health monitoring. This paper aims to provide an overview of four emerging unobtrusive and wearable technologies, which are essential to the realization of pervasive health information acquisition, including: (1) unobtrusive sensing methods, (2) smart textile technology, (3) flexible-stretchable-printable electronics, and (4) sensor fusion, and then to identify some future directions of research.
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“We refer to a recent review for more on advances in ECG and other sensing technologies [5].”
BackgroundRecent Progress in Materials and Devices toward Printable and Flexible Sensors
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Metadata
- Authors
- Zheng, Y.-L., Ding, X.-R., Poon, C. C. Y., Lo, B. P. L., Zhang, H., Zhou, X.-L., Yang, G.-Z., Zhao, N., & Zhang, Y.-T.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2014-05
- Volume
- 61
- Issue
- 5
- Pages
- 1538-1554
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2125628414
- Cited by
- 722
- References
- 135
- FWCI
- 39.89
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
