To track dynamically varying and physiologically relevant biomarker profiles in sweat, autonomous wearable platforms are required to periodically sample and analyze sweat with minimal or no user intervention. Previously reported sweat sensors are functionally limited to capturing biomarker information at one time-point/period, thereby necessitating repeated user intervention to increase the temporal granularity of biomarker data. Accordingly, we present a compact multi-compartment wearable system, where each compartment can be activated to autonomously induce/modulate sweat secretion ( via iontophoretic actuation) and analyze sweat at set time points. This system was developed following a hybrid-flex design and a vertical integration scheme—integrating the required functional modules: miniaturized iontophoresis interfaces, adhesive thin film microfluidic-sensing module, and control/readout electronics. The system was deployed in a human subject study to track the diurnal variation of sweat glucose levels in relation to the daily food intake. The demonstrated autonomous operation for diurnal sweat biomarker data acquisition illustrates the system's suitability for large-scale and longitudinal personal health monitoring applications.
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Wearable aptamer-field-effect transistor sensing system for noninvasive cortisol monitoring
Wearable technologies for personalized monitoring require sensors that track biomarkers often present at low levels. Cortisol—a key stress biomarker—is present in sweat at low nanomolar concentrations. Previous wearable sensing systems are limited to analytes in the micromolar-millimolar ranges. To overcome this and other limitations, we developed a flexible field-effect transistor (FET) biosensor array that exploits a previously unreported cortisol aptamer coupled to nanometer-thin-film In 2 O 3 FETs. Cortisol levels were determined via molecular recognition by aptamers where binding was transduced to electrical signals on FETs. The physiological relevance of cortisol as a stress biomarker was demonstrated by tracking salivary cortisol levels in participants in a Trier Social Stress Test and establishing correlations between cortisol in diurnal saliva and sweat samples. These correlations motivated the development and on-body validation of an aptamer-FET array–based smartwatch equipped with a custom, multichannel, self-referencing, and autonomous source measurement unit enabling seamless, real-time cortisol sweat sensing.
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- Award ID(s):
- 1847729
- NSF-PAR ID:
- 10336140
- Date Published:
- Journal Name:
- Science Advances
- Volume:
- 8
- Issue:
- 1
- ISSN:
- 2375-2548
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Wearable health monitoring has garnered considerable interest from the healthcare industry as an evolutionary alternative to standard practices with the ability to provide rapid, off‐site diagnosis and patient‐monitoring. In particular, sweat‐based wearable biosensors offer a noninvasive route to continuously monitor a variety of biomarkers for a range of physiological conditions. Both the accessibility and wealth of information of sweat make it an ideal target for noninvasive devices that can aid in early diagnosis of disease or to monitor athletic performance. Here, the integration of ammonium (NH4+) and calcium (Ca2+) ion‐selective membranes with a poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate)‐based (PEDOT:PSS) organic electrochemical transistor (OECT) for multiplexed sensing of NH4+and Ca2+in sweat with high sensitivity and selectivity is reported for the first time. The presented wearable sweat sensor is designed by combining a flexible and stretchable styrene‐ethylene‐butene‐styrene substrate with a laser‐patterned microcapillary channel array for direct sweat acquisition and delivery to the ion‐selective OECT. The resulting dermal sensor exhibits a wide working range between 0.01 × 10−3and 100 × 10−3
m , well within the physiological levels of NH4+and Ca2+in sweat. The integrated devices are successfully implemented with both ex situ measurements and on human subjects with real‐time analysis using a wearable sensor assembly.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1126/sciadv.abk0967
