Results 201 to 210 of about 86,623 (303)

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

Methodological refinement in bibliometric mapping of wearable sensors for stroke rehabilitation. [PDF]

Digit Health
Tahir HN, Antar AS, Yousaf M, Javed S, Rizvi SB.   +4 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

Wearable Sensors and Artificial Intelligence for Ecological Knee Osteoarthritis Assessment: Development and Feasibility of a Hybrid Digital Phenotyping Framework. [PDF]

Sensors (Basel)
Mapinduzi J, Daniels K, Kossi O, Verbrugghe J, Bonnechère B.   +4 more
europepmc   +1 more source

Programmable 3D Photovoltaics via Mechanically Origami‐Coded Interlocked 3D Kirigami and Nano‐Root Anchored AgNWs–In–Ga Multiphasic Alloy Conductor

Advanced Materials, EarlyView.
Mechanically origami‐coded 3D kirigami photovoltaics convert a single extension–release cycle into deterministic self‐folding, reconfiguring planar solar cells into programmable 3D modules. Distinct coding strategies enable either ultrahigh stretchability (500% system strain) or ultrahigh initial effective areal coverage (225%).
Seok Joon Hwang, Jiwon Ryu, Byungsoo Kang, Injong Oh, Dae‐Hee Cho, YoungHoi Cho, Seung S. Lee, Dong Hoe Kim, Deokjae Choi, Gee Yeong Kim, Heesuk Jung, Taehee Kim, Hyeonggeun Yu, Seungjun Chung, Byoung Koun Min, Phillip Lee   +15 more
wiley   +1 more source

A Novel Workflow to Estimate Limb Orientation from Wearable Sensors to Monitor Infant Motor Development. [PDF]

Sensors (Basel)
Song D, Kaiser WJ, Vangala S, Wilson RB.
europepmc   +1 more source

High‐Performance Transparent, Deformable, and Recoverable Biomimetic Stevia–PVA Hydrogel Triboelectric Nanogenerator with Machine Learning‐Assisted Motion Recognition

Advanced Materials, EarlyView.
A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu, Bui Minh Quang, Toan Minh Pham, Jinsoo Kim, Kyungwho Choi, Dukhyun Choi   +5 more
wiley   +1 more source

Triboelectric Wearable Sensors for Human-Centric Smart Electronics: From Self-Powered Sensing to Artificial Intelligence-Assisted Human-Machine Interface Systems. [PDF]

Nanomicro Lett
Ra Y, Cho S, Guo X, Choi D, Lee C.
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

Global trends in wearable sensors for stroke motor rehabilitation: A bibliometric analysis. [PDF]

Digit Health
Li X, Wang J, Luan X, Yang H, Liu R.
europepmc   +1 more source