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PreFalls 2.2

7.4 MB / 0+ Downloads / Rating 5.0 - 1 reviews


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PreFalls, developed and published by WMT-UTCC, has released its latest version, 2.2, on 2017-07-06. This app falls under the Health & Fitness category on the Google Play Store and has achieved over 10 installs. It currently holds an overall rating of 5.0, based on 1 reviews.

PreFalls APK available on this page is compatible with all Android devices that meet the required specifications (Android 4.3+). It can also be installed on PC and Mac using an Android emulator such as Bluestacks, LDPlayer, and others.

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App Screenshot

App Screenshot

App Details

Package name: com.ben.prefalls

Updated: 8 years ago

Developer Name: WMT-UTCC

Category: Health & Fitness

New features: Show more

App Permissions: Show more

Installation Instructions

This article outlines two straightforward methods for installing PreFalls on PC Windows and Mac.

Using BlueStacks

  1. Download the APK/XAPK file from this page.
  2. Install BlueStacks by visiting http://bluestacks.com.
  3. Open the APK/XAPK file by double-clicking it. This action will launch BlueStacks and begin the application's installation. If the APK file does not automatically open with BlueStacks, right-click on it and select 'Open with...', then navigate to BlueStacks. Alternatively, you can drag-and-drop the APK file onto the BlueStacks home screen.
  4. Wait a few seconds for the installation to complete. Once done, the installed app will appear on the BlueStacks home screen. Click its icon to start using the application.

Using LDPlayer

  1. Download and install LDPlayer from https://www.ldplayer.net.
  2. Drag the APK/XAPK file directly into LDPlayer.

If you have any questions, please don't hesitate to contact us.

Previous Versions

PreFalls 2.2
2017-07-06 / 7.4 MB / Android 4.3+

About this app

The main objective of this project is to develop an innovative software
system that can dynamically perform spatial-temporal gait analysis and
physical activity classification in order to assess the mobility and falls of
elderly people remotely in real-time. The system is designed to be utilized
as a tool that can precisely identify changes in gait parameters (e.g. stride
length) and recognize types of physical activities of the elderly based on the patterns of acceleration data. In our system, a mobile phone equipped with
motion sensors (an accelerometer and a gyroscope) has to be worn on the
waist of elderly people when they perform physical activities. It then
continuously submits sensor measurements (e.g. acceleration force angular
velocity and calculated stride length) to our remote monitoring system. The
system then processes the sensor measurements dynamically as they
arrive, performs gait analysis and activity classification with low latency,
and finally graphically displays certain gait parameters and types of
mobility-related activities of the elderly in real-time to support medical
staffs in diagnosing diseases and planning the treatment. In the case of fall
risk is identified or a fall event is detected, an instant notification will be
sent to caregivers who provide care and support for the elderly via a
dedicated mobile application. Furthermore, in case that immobility is
detected (elderly people sit or lie in bed for long periods of time), the
system will notify caregivers immediately as well.

New features

Fix bug

App Permissions

Allows an app to access approximate location.
Allows an app to access precise location.
Allows applications to open network sockets.
Allows access to the vibrator.
Allows an application to receive the ACTION_BOOT_COMPLETED that is broadcast after the system finishes booting.
Allows applications to access information about networks.
Allows using PowerManager WakeLocks to keep processor from sleeping or screen from dimming.