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Human fall detection app implemented for WatchOS (2110327 Algorithm Project)

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Fally

Fally is an app designed for detecting human falls especially for elder people.

When fall detected and you don’t press an “Tap here if you're ok” button within the specific time, Fally will automatically notify your family for help.

Make Fally be a part of your daily life to protect yourself and your loved one.

Screenshot

Fally screenshot

Getting Started

Prerequisites

This project requires the Xcode 8 and WatchOS 3.1
👉 See this link for further details about Xcode

Build and Run

Using Apple Watch's Simulator, Xcode built-in, to simulate this application

How to run in Simulator

Input file

Since Xcode simulator doesn't provide the feature which allows us to simulate CMDeviceMotion data directly, we'll use an input file to feed Fally mock up acceleration data; in x, y and z axises instead.
An input file fed to Fally must be conformed to the following pattern:

input_file_name.txt

,,acceleration_x_axis,acceleration_y_axis,acceleration_z_axis
,,acceleration_x_axis,acceleration_y_axis,acceleration_z_axis
,,acceleration_x_axis,acceleration_y_axis,acceleration_z_axis
...

Note that ,, in front of each line cannot be omitted and all acceleration_?_axis is in G unit.
👉 See example of input file [here](Fally WatchKit Extension/fall25.txt).

Then, add all input files under Fally Watchkit Extension/SimulatedInputFile group in Xcode.

Input file location

Include your Input File in Simulator Scheme

Select Edit Scheme... from build panel as seen in an image below.

Edit scheme

Then, select Arguments and under Environment Variablesedit input value to match your input file name without file extension.

Input value

Run in Simulator

Eventually, your app is ready to run. Make sure that Fally WatchKit App Scheme is selected before clicking Build and then run the current scheme.

Select scheme

Build and then run

Authors

Citation

  • Bogdan Kwolek, Michal Kepski, Human fall detection on embedded platform using depth maps and wireless accelerometer, Computer Methods and Programs in Biomedicine, Volume 117, Issue 3, December 2014, Pages 489-501, ISSN 0169-2607. [Link]

Warning

Since main purpose of this application is to demonstrate human fall detection algorithm, most part of this application are partially implemented.

And we also know that we should promote such this important section to the top of this README.md 😀

License

This project is licensed under the MIT License - see the LICENSE file for details

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Human fall detection app implemented for WatchOS (2110327 Algorithm Project)

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