Continuous Tremor Monitoring in Parkinson's Disease: A Wristwatch-inspired Triboelectric Sensor Approach DOI Creative Commons

Sirinya Ukasi,

Satana Pongampai, Basanta K. Panigrahi

et al.

iScience, Journal Year: 2024, Volume and Issue: 27(12), P. 111480 - 111480

Published: Nov. 26, 2024

Language: Английский

A novel dual-mode paper fiber sensor based on laser-induced graphene and porous salt-ion for monitoring humidity and pressure of human DOI

Aoxun Liang,

Wenhao Dong, Xiaoyu Li

et al.

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: unknown, P. 158184 - 158184

Published: Nov. 1, 2024

Language: Английский

Citations

10
Self-powered and self-sensing triboelectric electromagnetic hybrid generator with dual motion amplification mechanism for application in floating slab track system DOI

Yuan Wang,

Jinyan Feng,

Jiaoyi Wu

et al.

Nano Energy, Journal Year: 2025, Volume and Issue: unknown, P. 110663 - 110663

Published: Jan. 1, 2025

Language: Английский

Citations

2
Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation DOI Creative Commons
Mirza Akhi Khatun, Sanober Farheen Memon, Ciarán Eising

et al.

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 145869 - 145896

Published: Jan. 1, 2023

The Healthcare Internet-of-Things (H-IoT), commonly known as Digital Healthcare, is a data-driven infrastructure that highly relies on smart sensing devices (i.e., blood pressure monitors, temperature sensors, etc.) for faster response time, treatments, and diagnosis. However, with the evolving cyber threat landscape, IoT have become more vulnerable to broader risk surface (e.g., risks associated generative AI, 5G-IoT, etc.), which, if exploited, may lead data breaches, unauthorized access, lack of command control potential harm. This paper reviews fundamentals healthcare IoT, its privacy, security challenges machine learning H-IoT devices. further emphasizes importance monitoring layers such perception, network, cloud, application. Detecting responding anomalies involves various cyber-attacks protocols Wi-Fi 6, Narrowband Internet Things (NB-IoT), Bluetooth, ZigBee, LoRa, 5G New Radio (5G NR). A robust authentication mechanism based deep techniques required protect mitigate from increasing cybersecurity vulnerabilities. Hence, in this review paper, privacy mitigation strategies building resilience are explored reported.

Language: Английский

Citations

23
Intelligent cardiovascular disease diagnosis system combined piezoelectric nanogenerator based on 2D Bi2O2Se with deep learning technique DOI

Yuanhu Sun,

Junqi Mao,

Liang Cao

et al.

Nano Energy, Journal Year: 2024, Volume and Issue: 128, P. 109878 - 109878

Published: June 13, 2024

Language: Английский

Citations

7
Artificial intelligence-assisted wearable electronics for human-machine interfaces DOI
Lingji Kong,

Juhuang Song,

Zheng Fang

et al.

Device, Journal Year: 2025, Volume and Issue: unknown, P. 100707 - 100707

Published: Feb. 1, 2025

Language: Английский

Citations

1
AI‐Enabled Adaptive Eutectogel Skin for Effective Motion Monitoring with Low Signal Artifacts DOI Open Access

Yexi Jin,

Ruolin Wang,

Dingkang Tang

et al.

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

Published: Feb. 16, 2025

Abstract Interfacial gel compliance is essential for the stable monitoring of physiological electrical signals. Current materials often fail to maintain operation at skin interface, which subject constant change, due an inadequate balance viscoelastic properties. In this study, a dynamic adaptive network involving metal coordination with hierarchical hydrogen bonding developed. The multilayered supramolecular structure has enabled polymer chains generate new physical entanglements upon dissociation. This cross‐linking allows eutectogel sustain viscosity and elasticity across broad frequency range (10 −7 –340 Hz). Furthermore, metal‐based exhibits enhanced stretchability (1800%), good conductivity (125 mS m −1 ), wide operating temperature (−70–100 °C), strong interfacial adhesion. offers superior stability in acquisition signals when compared standard commercial gels. Viable application resultant strain sensors demonstrated human–machine interaction (HMI) virtual reality (VR) haptic interaction. addition, convolutional neural (CNN) algorithm employed develop intelligent system evaluating motion states using surface electromyography (sEMG) signals, achieving accuracy 94.1%.

Language: Английский

Citations

1
Trends in Flexible Sensing Technology in Smart Wearable Mechanisms–Materials–Applications DOI Creative Commons
Sen Wang, Haorui Zhai, Qiang Zhang

et al.

Nanomaterials, Journal Year: 2025, Volume and Issue: 15(4), P. 298 - 298

Published: Feb. 15, 2025

Flexible sensors are revolutionizing our lives as a key component of intelligent wearables. Their pliability, stretchability, and diverse designs enable foldable portable devices while enhancing comfort convenience. Advances in materials science have provided numerous options for creating flexible sensors. The core their application areas like electronic skin, health medical monitoring, motion human-computer interaction is selecting that optimize sensor performance weight, elasticity, comfort, flexibility. This article focuses on sensors, analyzing "sensing mechanisms-materials-applications" framework. It explores development trajectory, material characteristics, contributions various domains such interaction. concludes by summarizing current research achievements discussing future challenges opportunities. expected to continue expanding into new fields, driving the evolution smart wearables contributing society.

Language: Английский

Citations

1
A Dual-Mode Transparent Flexible Pressure Sensor Array for Tactile Sensing Visualization DOI
Chenyu Fang, Leilei Zhao, Wanwan Su

et al.

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 161618 - 161618

Published: March 1, 2025

Language: Английский

Citations

1
AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices DOI Creative Commons

Aiswarya Baburaj,

Syamini Jayadevan,

Akshaya Kumar Aliyana

et al.

Advanced Science, Journal Year: 2025, Volume and Issue: 12(20)

Published: April 25, 2025

Triboelectric nanogenerators (TENGs) are emerging as transformative technologies for sustainable energy harvesting and precision sensing, offering eco-friendly power generation from mechanical motion. They harness while enabling self-sustaining sensing self-powered devices. However, challenges such material optimization, fabrication techniques, design strategies, output stability must be addressed to fully realize their practical potential. Artificial intelligence (AI), with its capabilities in advanced data analysis, pattern recognition, adaptive responses, is revolutionizing fields like healthcare, industrial automation, smart infrastructure. When integrated TENGs, AI can overcome current limitations by enhancing output, stability, adaptability. This review explores the synergistic potential of AI-driven TENG systems, optimizing materials embedding machine learning deep algorithms intelligent real-time sensing. These advancements enable improved harvesting, predictive maintenance, dynamic performance making TENGs more across industries. The also identifies key future research directions, including development low-power algorithms, materials, hybrid robust security protocols AI-enhanced solutions.

Language: Английский

Citations

1
Hybrid human energy harvesting method of MTEG-TENG based on a flexible shared substrate DOI
Changxin Liu,

Tong Shao,

Zhijie Hao

et al.

Materials Today Sustainability, Journal Year: 2024, Volume and Issue: 26, P. 100692 - 100692

Published: Feb. 13, 2024

Language: Английский

Citations

6