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Self-Powered Wearable Biosensors

Authors: Yu Song; Daniel Mukasa; Haixia Zhang; Wei Gao;

Self-Powered Wearable Biosensors

Abstract

Wearable biosensors hold the potential of revolutionizing personalized healthcare and telemedicine. Advances in chemical sensing, flexible materials, and scalable manufacturing techniques now allow wearables to detect key physiological indicators such as temperature, vital signs, body motion, and molecular biomarkers. With these systems operating on the skin, they enable continuous and noninvasive disease diagnosis and health monitoring. Such complex devices, however, require suitable power sources in order to realize their full capacity. Emerging wearable energy harvesters are attractive for addressing the challenges of a wearable power supply. These harvesters convert various types of ambient energy sources (e.g., biomechanical energy, biochemical energy, and solar energy) into electricity. In some circumstances, the harvested electrical signals can directly be used for active sensing of physiological parameters. On the other hand, single or hybrid wearable energy harvesters, when integrated with power management circuits and energy storage devices, could power additional biosensors as well as signal processing and data transmission electronics. Self-powered sensor systems operate continuously and sustainably without an external power supply are promising candidates in the next generation of wearable electronics and the Internet of Things. This Account highlights recent progress in self-powered wearable sensors toward personalized healthcare, covering biosensors, energy harvesters, energy storage, and power supply strategies. The Account begins with an introduction of our wearable biosensors toward an epidermal detection of physiological information. Advances in structural and material innovations enable wearable systems to measure both biophysical and biochemical indicators conformably, accurately, and continuously. We then discuss emerging technologies in wearable energy harvesting, classified according to their capability to scavenge energy from various sources. These include examples of using energy ...

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Keywords

screening and diagnosis, Sensors, Data Management and Data Science, 610, Wearable electronics, Bioengineering, Materials Engineering, 4.1 Discovery and preclinical testing of markers and technologies, Self-powered dynamic systems, Detection, Engineering, Good Health and Well Being, Solar energy, Networking and Information Technology R&D (NITRD), Affordable and Clean Energy, Power, Information and Computing Sciences, Generic health relevance, Electronics, Sensors and Digital Hardware

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    185
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
185
Top 1%
Top 10%
Top 0.1%
Green
hybrid