Giter Club home page Giter Club logo

fally's Introduction

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

fally's People

Contributors

pqrsooo avatar yongfrank avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.