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

RSC Advances, Journal Year: 2025, Volume and Issue: 15(10), P. 7844 - 7854

Published: Jan. 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.

Language: Английский

---

Artificial Intelligence Assisted Nanogenerator Applications

Journal of Materials Chemistry A, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 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.

Language: Английский

---

Machine Learning Assisted-Intelligent Lactic Acid Monitoring in Sweat Supported by a Perspiration-Driven Self-Powered Sensor

Nano Letters, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 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%.

Language: Английский

---

Advances in smart textiles for personal thermal management

Med-X, Journal Year: 2025, Volume and Issue: 3(1)

Published: March 3, 2025

Language: Английский

---

Deep-Learning-Based Analysis of Electronic Skin Sensing Data

Sensors, Journal Year: 2025, Volume and Issue: 25(5), P. 1615 - 1615

Published: March 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.

Language: Английский

---

Flexible wearable electronics for enhanced human-computer interaction and virtual reality applications

Nano Energy, Journal Year: 2025, Volume and Issue: 138, P. 110821 - 110821

Published: March 5, 2025

Language: Английский

---

Advances in 2D materials for wearable biomonitoring

Materials Science and Engineering R Reports, Journal Year: 2025, Volume and Issue: 164, P. 100971 - 100971

Published: March 12, 2025

Language: Английский

---

Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 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.

Language: Английский

---

Intelligent sensing devices and systems for personalized mental health

Med-X, Journal Year: 2025, Volume and Issue: 3(1)

Published: April 2, 2025

Language: Английский

---

Navigating Sensor-Skin Coupling Challenges in Magnetic-Based Blood Pressure Monitoring: Innovations and Clinical Implications for Hypertension and Aortovascular Disease Management

Current Problems in Cardiology, Journal Year: 2024, Volume and Issue: unknown, P. 102964 - 102964

Published: Dec. 1, 2024

Language: Английский

---