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AI system can track human movements from behind walls

Press Trust of India  |  Boston 

scientists have developed an (AI) vision system that can sense people's postures and movements from the other side of a solid wall.

The "RF-Pose" uses AI to teach to sense people's postures and movement, even from the other side of a wall.

The researchers used a to analyse radio signals that bounce off people's bodies, and can then create a dynamic stick figure that walks, stops, sits and moves its limbs as the person performs those actions.

The team said that the system could be used to monitor like and (MS), providing a better understanding of progression and allowing doctors to adjust medications accordingly.

It could also help elderly people live more independently, while providing the added security of monitoring for falls, and changes in activity patterns.

The team is currently working with doctors to explore multiple applications in

"We've seen that monitoring patients' walking speed and ability to do basic activities on their own gives providers a window into their lives that they didn't have before, which could be meaningful for a whole range of diseases," said from Massachusetts Institute of (MIT) in the US.

"A key advantage of our approach is that patients do not have to wear sensors or remember to charge their devices," said Katabi.

Besides health-care, the team said that RF-Pose could also be used for new classes of video games where players move around the house, or even in to help locate survivors.

Researchers gathered thousands of images of people doing activities like walking, talking, sitting, opening doors and waiting for elevators.

They then used these images from the camera to extract the stick figures, which they showed to the along with the corresponding radio signal.

This combination of examples enabled the system to learn the association between the radio signal and the stick figures of the people in the scene.

Post-training, RF-Pose was able to estimate a person's posture and movements without cameras, using only the that bounce off people's bodies.

Besides sensing movement, researchers showed that they could use to accurately identify somebody 83 per cent of the time out of a line-up of 100 individuals.

This ability could be particularly useful for the application of search-and-rescue operations, when it may be helpful to know the identity of specific people.

The model outputs a 2D stick figure, but the team is also working to create 3D representations that would be able to reflect even smaller micromovements.

(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)

First Published: Tue, June 12 2018. 13:35 IST
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