Fall Detection with YOLOv7 Pose Estimation Demo

Not everyone has an Apple Watch⌚️ for , but we can use a camera with some AI. Whether you’d want a camera watching📷 you 24/7 is a topic for another day however this technology is essential for frail care.
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If you would like to code apps like this for health care applications⛑, I can show you, from scratch, step-by-step using YOLOv7.
👾Click this link to learn – https://lnkd.in/dgsmAvXE
🏂Or get started with YOLOv7 for Free https://lnkd.in/did9A-mE

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You may have an elderly👴🏼🧓🏼 or frail loved one👨🏻‍🦽 who does not own a smartwatch and even if they do, they don’t want to wear (or maybe forget to wear) the device.

This is where we can apply Estimation for , which can inform you or a health care provider🧑🏻‍⚕️ that a person has fallen. This is so that they may attend to the patient as soon as possible🩺.

When it comes to health🏥, every second counts⏱, and the sooner you are notified of the person falling, the sooner they can be cared for or treated⚕️.

I have put together a compilation of people falling, or rather intentionally falling in a martial arts setting. I will post another video demo, to relate more to actual falling events soon.

☕️ Show your appreciation for this tutorial – Please Buy me a Coffee/Chai so I can create more free tutorials for you 😊 – https://augmentedstartups.info/BuyMeCoffee

✅YOLOv7 surpasses all known object detectors (speed & accuracy)
✅56 FPS V100, 55.9% AP
✅120% faster than
✅State-of-the-Art

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