A research team has successfully overcome the limitations of soft strain sensors by integrating computer vision technology into optical sensors. The team developed a sensor technology known as computer vision-based optical strain (CVOS). Unlike conventional sensors reliant on electrical signals, CVOS sensors employ computer vision and optical sensors to analyze microscale optical patterns, extracting data regarding changes. This approach inherently enhances durability by eliminating elements that compromise sensor functionalities and streamlining fabrication processes, thereby facilitating sensor commercialization.

In contrast to conventional sensors that solely detect biaxial strain, CVOS sensors exhibit the exceptional ability to detect three-axial rotational movements through real-time multiaxial strain mapping. In essence, these sensors enable the precise recognition of intricate and various bodily motions through a single sensor. The research team substantiated this claim through experiments applying CVOS sensors to assistive devices in rehabilitative treatments.

Through integration of an AI-based response correction algorithm that corrects diverse error factors arising during signal detection, the experiment results showed a high level of confidence. Even after undergoing more than 10,000 iterations, these sensors consistently maintained their exceptional performance. (Image credit: POSTECH)

For more information, visit here  .

Topics:
Artificial intelligence (AI) Collaboration and partnering Fabrication Imaging Imaging and visualization Manufacturing processes Medical Optical Components Optics People and personalities Research and development Sensors Sensors and actuators

More From SAE Media Group

    Magazine cover
    Medical Design Briefs Magazine

    This article first appeared in the October, 2023 issue of Medical Design Briefs Magazine (Vol. 13 No. 10).

    Read more articles from this issue here.

    Read more articles from the archives here.