Results 151 to 160 of about 2,380,796 (287)
This review presents recent progress in vision‐augmented wearable interfaces that combine artificial vision, soft wearable sensors, and exoskeletal robots. Inspired by biological visual systems, these technologies enable multimodal perception and intelligent human–machine interaction.
Jihun Lee +4 more
wiley +1 more source
Mapping the Outcomes of Low-Vision Rehabilitation: A Scoping Review of Interventions, Challenges, and Research Gaps. [PDF]
Ekemiri K +8 more
europepmc +1 more source
An automation interface for environmental scanning electron microscopy (ESEM) enables simultaneous, interlaced data sets via frame‐by‐frame parameter changes. Demonstrated on oscillatory hydrogen oxidation over cobalt (Co) foil, dual‐magnification imaging bridges mesoscopic to microscopic length scales, capturing alternating views of surface dynamics ...
Maurits Vuijk +7 more
wiley +1 more source
Standard List for Low Vision Services
WHO/ IAPB Low Vision Working Group
doaj
Low Vision Rehabilitation in a Family Affected by Peters' Anomaly Syndrome. [PDF]
Beshtawi IM.
europepmc +1 more source
Flexible piezopolymer ultrasound transducers are engineered by tailoring the electrode–piezopolymer interface using metallic, flake‐based, and porous graphene electrodes. Laser‐induced graphene's porous structure enables polymer infiltration, strengthening interfacial coupling and enhancing piezoelectric response and acoustic output.
Spencer Hagen +3 more
wiley +1 more source
From abandonment to adoption: advancing assistive technologies for blindness and low vision in the AI era. [PDF]
Barak Ventura R +2 more
europepmc +1 more source
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov +3 more
wiley +1 more source
Development of a machine learning model to predict low vision aid fitting for visually impaired patients. [PDF]
Dai B +11 more
europepmc +1 more source

