Nanomaterial Innovations and Machine Learning in Gas Sensing Technologies for Real-Time Health Diagnostics DOI

Md. Harun-Or-Rashid,

Sahar Mirzaei, Noushin Nasiri

et al.

ACS Sensors, Journal Year: 2025, Volume and Issue: unknown

Published: March 10, 2025

Breath sensors represent a frontier in noninvasive diagnostics, leveraging the detection of volatile organic compounds (VOCs) exhaled breath for real-time health monitoring. This review highlights recent advancements breath-sensing technologies, with focus on innovative materials driving their enhanced sensitivity and selectivity. Polymers, carbon-based like graphene carbon nanotubes, metal oxides such as ZnO SnO2 have demonstrated significant potential detecting biomarkers related to diseases including diabetes, liver/kidney dysfunction, asthma, gut health. The structural operational principles these are examined, revealing how unique properties contribute key respiratory gases acetone, ammonia (NH3), hydrogen sulfide, nitric oxide. complexity samples is addressed through integration machine learning (ML) algorithms, convolutional neural networks (CNNs) support vector machines (SVMs), which optimize data interpretation diagnostic accuracy. In addition sensing VOCs, devices capable monitoring parameters airflow, temperature, humidity, essential comprehensive analysis. also explores expanding role artificial intelligence (AI) transforming wearable into sophisticated tools personalized enabling disease Together, advances sensor ML-based analytics present promising platform future individualized, healthcare.

Language: Английский

Nanomaterial Innovations and Machine Learning in Gas Sensing Technologies for Real-Time Health Diagnostics DOI

Md. Harun-Or-Rashid,

Sahar Mirzaei, Noushin Nasiri

et al.

ACS Sensors, Journal Year: 2025, Volume and Issue: unknown

Published: March 10, 2025

Breath sensors represent a frontier in noninvasive diagnostics, leveraging the detection of volatile organic compounds (VOCs) exhaled breath for real-time health monitoring. This review highlights recent advancements breath-sensing technologies, with focus on innovative materials driving their enhanced sensitivity and selectivity. Polymers, carbon-based like graphene carbon nanotubes, metal oxides such as ZnO SnO2 have demonstrated significant potential detecting biomarkers related to diseases including diabetes, liver/kidney dysfunction, asthma, gut health. The structural operational principles these are examined, revealing how unique properties contribute key respiratory gases acetone, ammonia (NH3), hydrogen sulfide, nitric oxide. complexity samples is addressed through integration machine learning (ML) algorithms, convolutional neural networks (CNNs) support vector machines (SVMs), which optimize data interpretation diagnostic accuracy. In addition sensing VOCs, devices capable monitoring parameters airflow, temperature, humidity, essential comprehensive analysis. also explores expanding role artificial intelligence (AI) transforming wearable into sophisticated tools personalized enabling disease Together, advances sensor ML-based analytics present promising platform future individualized, healthcare.

Language: Английский

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