Results 191 to 200 of about 1,888,792 (317)

Hierarchical Multi‐Material Architectures With Gradient Design for Dynamic‐Range Flexible Tactile Sensing

Advanced Materials Technologies, EarlyView.
Hierarchical multi‐material TPMS lattices are engineered as flexible tactile sensors by combining soft and stiff elastomeric layers with a conformal conductive coating. The bilayer architecture delivers sensitivity at low pressures while maintaining a broad detectable range under large loads, enabling reliable pressure and vibration monitoring for ...
Reza Noroozi, Domenic Quiquero, Yan Yan Shery Huang, HaoTian Harvey Shi   +3 more
wiley   +1 more source

Feasibility of real-time compression frequency and compression depth assessment in CPR using a "machine-learning" artificial intelligence tool. [PDF]

Resusc Plus
Ecker H, Adams NB, Schmitz M, Wetsch WA.
europepmc   +1 more source

Low‐Temperature Processed Optoelectronic Synapses With Enhanced Responsivity for Edge‐Oriented In‐Sensor Reservoir Computing

Advanced Materials Technologies, EarlyView.
Image pixels are converted into optical pulse sequences to stimulate the optoelectronic synaptic device, generating dynamic responses that form high‐dimensional features. These features improve classification efficiency and demonstrate strong potential for neuromorphic edge computing systems.
Jo‐Lin Chen, Shi‐Qian Guo, Yu‐Chuan Chiu, Po‐Tsun Liu   +3 more
wiley   +1 more source

The principle of uncertainty in biology: Will machine learning/artificial intelligence lead to the end of mechanistic studies? [PDF]

PLoS Biol
de Lorenzo V.
europepmc   +1 more source

Soft Robotic Excretory Care Simulator for Nursing Education: Functional and Perceptual Biomimetics Approach

Advanced Robotics Research, EarlyView.
A soft robotic simulator is developed to replicate the digital removal of feces (DRF), a sensitive yet essential nursing procedure. Integrating soft actuators, sensors, and a realistic rectal model, the simulator balances functional fidelity with perceptual realism. Engineering evaluations and nurse feedback confirm its potential to enhance training in
Shoko Miyagawa, Sota Suzuki, Shizuka Watanabe, Zebing Mao, Young Ah Seong, Toshinori Fujie, Tatsuhiro Horii, Kenjiro Tadakuma, Koichi Suzumori, Hiroyuki Nabae, Shingo Maeda   +10 more
wiley   +1 more source

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance. [PDF]

Int J Cardiovasc Imaging
Oliveira C, Vilela M, Silva Marques J, Jorge C, Rodrigues T, Francisco AR, Oliveira RM, Silva B, Silva JL, Oliveira AL, Pinto FJ, Nobre Menezes M.   +11 more
europepmc   +1 more source

Deep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs. [PDF]

PLoS One, 2020
Zhu J, Shen B, Abbasi A, Hoshmand-Kochi M, Li H, Duong TQ.   +5 more
europepmc   +1 more source

Artificial intelligence. Machine learning

Vehicle and Electronics. Innovative Technologies, 2019
openaire   +2 more sources

Remote Control of Hand Actuators via Glove Sensors for Medical Care Applications

Advanced Robotics Research, EarlyView.
This study presents a novel textile‐based sensory glove–actuator system for remote medical care, explored through finite element simulations. By integrating capacitive sensors, pneumatic actuators, and machine learning, the system models real‐time hand movement control.
Bahman Taherkhani, Mahdi Bodaghi
wiley   +1 more source

Is Histopathology Deep Learning Artificial Intelligence the Future of Precision Oncology? [PDF]

J Clin Oncol
Wagner VM.
europepmc   +1 more source