Fall detection app developed using SwiftUI

• swiftui-charts

  1 660 10.0 Swift

  :rocket: SwiftUI Charts with custom styles

  

SwiftUI was used to ensure a dynamic and reactive interface for such a data-heavy application. I used https://github.com/spacenation/swiftui-charts for plotting the data, the Polar iOS SDK (https://github.com/polarofficial/polar-ble-sdk) for interfacing with the chest strap, and TensorflowLite for running the ML model.

• polar-ble-sdk

  19 438 7.4 HTML

  Repository includes SDK and code examples. More info https://polar.com/en/developers

  

SwiftUI was used to ensure a dynamic and reactive interface for such a data-heavy application. I used https://github.com/spacenation/swiftui-charts for plotting the data, the Polar iOS SDK (https://github.com/polarofficial/polar-ble-sdk) for interfacing with the chest strap, and TensorflowLite for running the ML model.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• Fall-Detection-App

  1 9 3.7 Swift

  Commercial iOS fall detection app. Connects to a Polar H10 device for triaxial acceleromter and ECG signals. These signals are passed to a trained ResNet152 model using Tensorflow background processes for live inference.

If you're interested you can find the code here: https://github.com/hwixley/Fall-Detection-App

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