Creating a Fall Detection Model Using Unsupervised Learning

Author(s): Petros Demetrakopoulos

Originally published on Towards AI.

Source: Image by Harlie Raethel on Unsplash

In our rapidly aging society, the risk of falling has become a growing concern. For elderly individuals, a fall can have grave consequences, ranging from painful fractures to hospitalization and, tragically, even death. Moreover, for those who live alone, there’s often no one around to call for help in the event of a fall. In such challenging circumstances, a wearable fall detector emerges as a practical and potentially lifesaving solution.

What’s remarkable is that many smartphones are already equipped with an array of sensors designed to measure motion. These sensors include accelerometers, gyroscopes, and gravity… Read the full blog for free on Medium.

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Published via Towards AI