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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 × 10−3m, 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.
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A Computationally Assisted Approach for Designing Wearable Biosensors toward Non‐Invasive Personalized Molecular Analysis
Abstract Wearable sweat sensors have the potential to revolutionize precision medicine as they can non‐invasively collect molecular information closely associated with an individual's health status. However, the majority of clinically relevant biomarkers cannot be continuously detected in situ using existing wearable approaches. Molecularly imprinted polymers (MIPs) are a promising candidate to address this challenge but haven't yet gained widespread use due to their complex design and optimization process yielding variable selectivity. Here, QuantumDock is introduced, an automated computational framework for universal MIP development toward wearable applications. QuantumDock utilizes density functional theory to probe molecular interactions between monomers and the target/interferent molecules to optimize selectivity, a fundamentally limiting factor for MIP development toward wearable sensing. A molecular docking approach is employed to explore a wide range of known and unknown monomers, and to identify the optimal monomer/cross‐linker choice for subsequent MIP fabrication. Using an essential amino acid phenylalanine as the exemplar, experimental validation of QuantumDock is performed successfully using solution‐synthesized MIP nanoparticles coupled with ultraviolet–visible spectroscopy. Moreover, a QuantumDock‐optimized graphene‐based wearable device is designed that can perform autonomous sweat induction, sampling, and sensing. For the first time, wearable non‐invasive phenylalanine monitoring is demonstrated in human subjects toward personalized healthcare applications.
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- Award ID(s):
- 2145802
- PAR ID:
- 10442048
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Materials
- Volume:
- 35
- Issue:
- 35
- ISSN:
- 0935-9648
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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