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1.
Nat Electron ; 7(2): 168-179, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-38433871

RESUMO

Approaches to quantify stress responses typically rely on subjective surveys and questionnaires. Wearable sensors can potentially be used to continuously monitor stress-relevant biomarkers. However, the biological stress response is spread across the nervous, endocrine, and immune systems, and the capabilities of current sensors are not sufficient for condition-specific stress response evaluation. Here we report an electronic skin for stress response assessment that non-invasively monitors three vital signs (pulse waveform, galvanic skin response and skin temperature) and six molecular biomarkers in human sweat (glucose, lactate, uric acid, sodium ions, potassium ions and ammonium). We develop a general approach to prepare electrochemical sensors that relies on analogous composite materials for stabilizing and conserving sensor interfaces. The resulting sensors offer long-term sweat biomarker analysis of over 100 hours with high stability. We show that the electronic skin can provide continuous multimodal physicochemical monitoring over a 24-hour period and during different daily activities. With the help of a machine learning pipeline, we also show that the platform can differentiate three stressors with an accuracy of 98.0%, and quantify psychological stress responses with a confidence level of 98.7%.

2.
Nano Lett ; 19(9): 6346-6351, 2019 09 11.
Artigo em Inglês | MEDLINE | ID: mdl-31381353

RESUMO

Levodopa is the standard medication clinically prescribed to patients afflicted with Parkinson's disease. In particular, the monitoring and optimization of levodopa dosage are critical to mitigate the onset of undesired fluctuations in the patients' physical and emotional conditions such as speech function, motor behavior, and mood stability. The traditional approach to optimize levodopa dosage involves evaluating the subjects' motor function, which has many shortcomings due to its subjective and limited quantifiable nature. Here, we present a wearable sweat band on a nanodendritic platform that quantitatively monitors levodopa dynamics in the body. Both stationary iontophoretic induction and physical exercise are utilized as our methods of sweat extraction. The sweat band measures real-time pharmacokinetic profiles of levodopa to track the dynamic response of the drug metabolism. We demonstrated the sweat band's functionalities on multiple subjects with implications toward the systematic administering of levodopa and routine management of Parkinson's disease.


Assuntos
Monitoramento de Medicamentos/instrumentação , Levodopa , Doença de Parkinson , Suor/metabolismo , Dispositivos Eletrônicos Vestíveis , Feminino , Humanos , Levodopa/administração & dosagem , Levodopa/farmacocinética , Doença de Parkinson/tratamento farmacológico , Doença de Parkinson/metabolismo
3.
Adv Mater ; 30(23): e1707442, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29663538

RESUMO

Drug monitoring plays crucial roles in doping control and precision medicine. It helps physicians tailor drug dosage for optimal benefits, track patients' compliance to prescriptions, and understand the complex pharmacokinetics of drugs. Conventional drug tests rely on invasive blood draws. While urine and sweat are attractive alternative biofluids, the state-of-the-art methods require separate sample collection and processing steps and fail to provide real-time information. Here, a wearable platform equipped with an electrochemical differential pulse voltammetry sensing module for drug monitoring is presented. A methylxanthine drug, caffeine, is selected to demonstrate the platform's functionalities. Sweat caffeine levels are monitored under various conditions, such as drug doses and measurement time after drug intake. Elevated sweat caffeine levels upon increasing dosage and confirmable caffeine physiological trends are observed. This work leverages a wearable sweat sensing platform toward noninvasive and continuous point-of-care drug monitoring and management.


Assuntos
Suor , Monitoramento de Medicamentos , Humanos , Monitorização Fisiológica , Dispositivos Eletrônicos Vestíveis , Xantinas
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