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Review
. 2022;7(11):887-907.
doi: 10.1038/s41578-022-00460-x. Epub 2022 Jul 22.

End-to-end design of wearable sensors

Affiliations
Review

End-to-end design of wearable sensors

H Ceren Ates et al. Nat Rev Mater. 2022.

Abstract

Wearable devices provide an alternative pathway to clinical diagnostics by exploiting various physical, chemical and biological sensors to mine physiological (biophysical and/or biochemical) information in real time (preferably, continuously) and in a non-invasive or minimally invasive manner. These sensors can be worn in the form of glasses, jewellery, face masks, wristwatches, fitness bands, tattoo-like devices, bandages or other patches, and textiles. Wearables such as smartwatches have already proved their capability for the early detection and monitoring of the progression and treatment of various diseases, such as COVID-19 and Parkinson disease, through biophysical signals. Next-generation wearable sensors that enable the multimodal and/or multiplexed measurement of physical parameters and biochemical markers in real time and continuously could be a transformative technology for diagnostics, allowing for high-resolution and time-resolved historical recording of the health status of an individual. In this Review, we examine the building blocks of such wearable sensors, including the substrate materials, sensing mechanisms, power modules and decision-making units, by reflecting on the recent developments in the materials, engineering and data science of these components. Finally, we synthesize current trends in the field to provide predictions for the future trajectory of wearable sensors.

Keywords: Bioinspired materials; Biosensors; Diagnostic devices; Sensors and biosensors; Synthetic biology.

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Conflict of interest statement

Competing interestsJ.J.C. is a cofounder and director of Sherlock Biosciences. F.G. is a cofounder and sharefolder of Spyras. The other authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Timeline of major milestones in the development of wearable sensors and a summary of their building blocks.
a | Major commercial and research-stage milestones in the development of wearable devices for health-care monitoring,,,,,,–. Advances in telecommunication technologies, materials science, bioengineering, electronics and data analysis, together with the rapidly increasing interest in monitoring health and well-being, have been the primary drivers of innovation in modern wearable sensors. More recently, the considerable reductions in cost have enabled the penetration of modern wearable sensors into many segments of the (consumer) population and geographical regions of the world, unlocking continuous monitoring at a scale never seen before. In addition, advances in fabrication methods have enabled greater sophistication at increasingly smaller dimensions, enabling sensor platforms to reach scales amenable to integration into personal technologies. b | Building blocks of wearable devices, including the substrate and electrode materials and the components of the sensing, decision-making and power units. ISF, interstitial fluid. Panel b (on-tooth sensor) adapted from ref., Springer Nature Limited.
Fig. 2
Fig. 2. The decision-making unit and its working principles.
a | Conceptualization of the data pipeline. The combination and processing of multiple wearables with multiple sensing strategies provides access to physiologically relevant parameters and biomarkers to better explain the non-linearity in human physiology. The black and red lines indicate the data processing and model training pathways, respectively. b | Overview of data-driven methods. Post-processing of big data to explore the complex links between the measured signals and physiological status of individuals is possible with machine learning algorithms. ANN, artificial neural network; DT, decision tree; GDBSCAN, generalized density-based spatial clustering of applications with noise; GM, Gaussian means; HC, hierarchical clustering; kNN, k-nearest neighbours; RF, random forest; SVM, support-vector machines. Panel a (top part) adapted from ref., Springer Nature Limited.
Fig. 3
Fig. 3. Energy harvesting methods.
a | Piezoelectricity is generated by mechanical motion, which activates a piezoelectric material. b | Triboelectricity is produced by motion that results in the physical contact and separation of two materials with different electronegativities. c | Thermoelectricity is generated when the surface of conductor A is heated and this energy is then transferred to conductor B, which triggers the motion of charge carriers (such as electrons and holes) and generates a voltage. d | Photovoltaic energy is generated when a photovoltaic material is irradiated with light. e | Electromagnetic radiation is managed by antennas that transform electromagnetic waves into a voltage or current. f | Wearable biofuel cells create energy from a catalytic reaction, which occurs between the fuel provided by a biofluid (such as sweat) and an enzyme; the reaction is generally enhanced by a mediator that boosts the electron transfer process between the enzymes and the electrodes.

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References

    1. Iqbal SMA, Mahgoub I, Du E, Leavitt MA, Asghar W. Advances in healthcare wearable devices. npj Flex. Electron. 2021;5:9. doi: 10.1038/s41528-021-00107-x. - DOI
    1. Brophy K, et al. The future of wearable technologies. Brief. Pap. 2021;8:1–20.
    1. Ates HC, et al. Integrated devices for non-invasive diagnostics. Adv. Funct. Mater. 2021;31:2010388. doi: 10.1002/adfm.202010388. - DOI
    1. Heikenfeld J, et al. Wearable sensors: modalities, challenges, and prospects. Lab Chip. 2018;18:217–248. doi: 10.1039/C7LC00914C. - DOI - PMC - PubMed
    1. Gambhir SS, Ge TJ, Vermesh O, Spitler R, Gold GE. Continuous health monitoring: an opportunity for precision health. Sci. Transl. Med. 2021;13:eabe5383. doi: 10.1126/scitranslmed.abe5383. - DOI - PubMed