Results 141 to 150 of about 65,577 (259)

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Body position classification using wearable sensors in infants with cerebral palsy. [PDF]

Infant Behav Dev
Kretch KS, Enriques FA, Franchak JM, Abney DH, Bell CA, Jerry CM, Lindig K, Steffen G.   +7 more
europepmc   +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair, Hrisheekesh Thachoth Chandran, Karl Leo, Hans Kleemann   +3 more
wiley   +1 more source

Real-world gait study of Parkinson's disease using wearable sensors: a systematic review. [PDF]

J Neuroeng Rehabil
Michaud M, de l'Escalopier N, Voisard C, Oudre L, Ricard D.   +4 more
europepmc   +1 more source

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Wearable sensors for monitoring drug pharmacokinetics in patients with Parkinson's disease. [PDF]

Sci Rep
Guo YJ, Li CC, Huang JA, Singh K, Mellini H, Lin YH, Yu CC, Fang TC, Pi CC, Chen PC, Li CY, Fan SY, Huang WC, Tsai TH, Liao YT, Tai LC.   +15 more
europepmc   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Wearable Sensors in Gait Assessment for Parkinson Disease and Stroke in Real-World Environments: Systematic Review and Meta-Analysis. [PDF]

J Med Internet Res
Neumann S, Albites-Sanabria J, Naef AC, Luft AR, Chiari L, Easthope Awai C.   +5 more
europepmc   +1 more source

Rational Tuning of Hygroscopic Oscillation of Stacked Nanoflake Assemblies for Continuous Ambient Energy Harvesting

Advanced Materials, EarlyView.
Stacked nanoflake assembly (SNA) membranes can oscillate autonomously, offering opportunities for soft actuation and energy harvesting. This work uncovers the physical mechanism behind the sustained oscillation of SNA membranes in gradient humidity and identifies three governing dimensionless parameters, enabling rational design for optimizing SNA ...
Zijing Zhang, Jimin Fu, Gesa Zhang, Zhihua Liang, Boxun Zhang, Haimin Yao   +5 more
wiley   +1 more source

Adaptive Convolutional Neural Network-Enhanced Scale-Fusion Network for Human Activity Recognition Using Wearable Sensors. [PDF]

Sensors (Basel)
Xie D, Yan P, Li Y, Wang Q, Liu J.
europepmc   +1 more source