Adaptive temperature compensation for MoS2 humidity sensor in complex environments using ISSA-BP neural network DOI
Dapeng Li,

Hechu Zhang,

Aobei Chen

и другие.

Sensors and Actuators A Physical, Год журнала: 2024, Номер 379, С. 115982 - 115982

Опубликована: Окт. 22, 2024

Язык: Английский

Recent advancements in wearable sensors: integration with machine learning for human–machine interaction DOI Creative Commons

Guangrui Mu,

Jianyi Yang, Zhonghong Yan

и другие.

RSC Advances, Год журнала: 2025, Номер 15(10), С. 7844 - 7854

Опубликована: Янв. 1, 2025

Wearable sensors have emerged as a transformative technology, enabling real-time monitoring and advanced functionality in various fields, including healthcare, human–machine interaction, environmental sensing.

Язык: Английский

Процитировано

1

Artificial Intelligence Assisted Nanogenerator Applications DOI
Shumao Xu,

Farid Manshaii,

Xiao Xiao

и другие.

Journal of Materials Chemistry A, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

This review examines the integration of artificial intelligence with nanogenerators to develop self-powered, adaptive systems for applications in robotics, wearables, and environmental monitoring.

Язык: Английский

Процитировано

8

Machine Learning Assisted-Intelligent Lactic Acid Monitoring in Sweat Supported by a Perspiration-Driven Self-Powered Sensor DOI
Jing Xu, Yujin Li, Futing Wang

и другие.

Nano Letters, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

Lactic acid has aroused increasing attention due to its close association with serious diseases. A real-time, dynamic, and intelligent detection method is vital for sensitive of lactic acid. Here, a machine learning (ML)-assisted perspiration-driven self-powered sensor (PDS sensor) fabricated using Ni-ZIF-8@lactate oxidase pyruvate (Ni-ZIF-8@LOx&POx)/laser-induced graphene (LIG), bilirubin (BOD)/LIG, microchannel highly real-time monitoring in sweat. Driven by the oxidation reaction acid, PDS sensors exhibit excellent sensitivity, wide range, good reproducibility, selectivity When subjects different body mass index (BMI) undergo aerobic or anaerobic exercise maintain sedentary state, can monitor sweat wirelessly real-time. Moreover, ML algorithm was employed assist detect subjects' high prediction accuracy 96.0%.

Язык: Английский

Процитировано

0

Advances in smart textiles for personal thermal management DOI Creative Commons
Weibin Zhu, Lung Chow,

D. Ye

и другие.

Med-X, Год журнала: 2025, Номер 3(1)

Опубликована: Март 3, 2025

Язык: Английский

Процитировано

0

Flexible wearable electronics for enhanced human-computer interaction and virtual reality applications DOI
Jian Li, Yuliang Zhao, Yibo Fan

и другие.

Nano Energy, Год журнала: 2025, Номер 138, С. 110821 - 110821

Опубликована: Март 5, 2025

Язык: Английский

Процитировано

0

Advances in 2D materials for wearable biomonitoring DOI
Songyue Chen, Shumao Xu, Xiujun Fan

и другие.

Materials Science and Engineering R Reports, Год журнала: 2025, Номер 164, С. 100971 - 100971

Опубликована: Март 12, 2025

Язык: Английский

Процитировано

0

Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence DOI Creative Commons
Shuwen Chen, Shicheng Fan, Zheng Qiao

и другие.

Advanced Materials, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Intelligent wearable sensors, empowered by machine learning and innovative smart materials, enable rapid, accurate disease diagnosis, personalized therapy, continuous health monitoring without disrupting daily life. This integration facilitates a shift from traditional, hospital-centered healthcare to more decentralized, patient-centric model, where sensors can collect real-time physiological data, provide deep analysis of these data streams, generate actionable insights for point-of-care precise diagnostics therapy. Despite rapid advancements in learning, sensing technologies, there is lack comprehensive reviews that systematically examine the intersection fields. review addresses this gap, providing critical technologies advanced materials artificial Intelligence. The state-of-the-art materials-including self-healing, metamaterials, responsive materials-that enhance sensor functionality are first examined. Advanced methodologies integrated into devices discussed, their role biomedical applications highlighted. combined impact intelligent therapeutics also Finally, existing challenges, including technical compliance issues, information security concerns, regulatory considerations addressed, future directions advancing proposed.

Язык: Английский

Процитировано

0

Intelligent sensing devices and systems for personalized mental health DOI Creative Commons
Yantao Xing, Yang Yang, Kaiyuan Yang

и другие.

Med-X, Год журнала: 2025, Номер 3(1)

Опубликована: Апрель 2, 2025

Язык: Английский

Процитировано

0

Navigating Sensor-Skin Coupling Challenges in Magnetic-Based Blood Pressure Monitoring: Innovations and Clinical Implications for Hypertension and Aortovascular Disease Management DOI
Wasim Ullah Khan, Mohammed Alissa,

Ahmed Abouzied

и другие.

Current Problems in Cardiology, Год журнала: 2024, Номер unknown, С. 102964 - 102964

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

3

Deep-Learning-Based Analysis of Electronic Skin Sensing Data DOI Creative Commons

Yu-Chen Guo,

Xidi Sun,

Lulu Li

и другие.

Sensors, Год журнала: 2025, Номер 25(5), С. 1615 - 1615

Опубликована: Март 6, 2025

E-skin is an integrated electronic system that can mimic the perceptual ability of human skin. Traditional analysis methods struggle to handle complex e-skin data, which include time series and multiple patterns, especially when dealing with intricate signals real-time responses. Recently, deep learning techniques, such as convolutional neural network, recurrent transformer methods, provide effective solutions automatically extract data features recognize significantly improving data. Deep not only capable handling multimodal but also response personalized predictions in dynamic environments. Nevertheless, problems insufficient annotation high demand for computational resources still limit application e-skin. Optimizing algorithms, efficiency, exploring hardware-algorithm co-designing will be key future development. This review aims present techniques applied inspiration subsequent researchers. We first summarize sources characteristics models applicable their applications analysis. Additionally, we discuss use e-skin, particularly health monitoring human-machine interactions, explore current challenges development directions.

Язык: Английский

Процитировано

0