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Computer software could detect falls or physical distress in elderly at night

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The Kepler Night Nurse Edge Box sends alerts to carers if any unusual activity is detected

New software has been developed which could prevent elderly people from falling out of bed.

The computer vision technology means care staff can get to patients quicker and eliminate false alarms.

Up until now care home staff have relied on sensor systems such a bed mats, motion sensors and devices like necklaces and bracelets for residents through the night.

Kepler Vision has launched the Kepler Night Nurse Edge Box which uses deep learning and computer vision to monitor patients.

Care staff get a text alert sent from the Edge Box which analyses the live feeds when patients need help. The Edge computer capability means the feed doesn’t have to be monitored in the cloud which removes concerns about privacy.

The software can detect if someone is having difficulty standing up or taking a long time in the toilet.

It can automatically add behavioural observations to a patient’s medical file.

Dr. Harro Stokman, of Kepler Vision Technologies, said: “This new product combines the proven effectiveness of our Night Nurse solution with reduced set up cost and complexity and removes the need for a constant high speed internet connection processing many feeds at once.

“Given the current state of the care home industry, we are proud to be offering something that reduces the strain on staff by allowing them to more effectively administer care, without sacrificing the privacy of patients.”

Kepler Night Nurse can analyse fisheye lensed video feeds without “straightening” the images. Running the video processing locally on the Edge Box instead of running it in the cloud eliminates the need to compress video streams. This allows for more close-up inspection of what is going on in the video, increasing the accuracy of the computer vision software.

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