Since falls are a major public health problem among older people, the number of systems aimed at detecting them has increased dramatically over recent years. It aims to serve as a reference for both clinicians and biomedical engineers planning or conducting field investigations. Challenges, issues and trends in fall detection have been identified after the reviewing work. The number of studies using context-aware techniques is still increasing but there is a new trend towards the integration of fall detection into smart phones as well as the use of machine learning methods in the detection algorithm. We must also look into many different aspects like real-life conditions, usability, and user acceptance as well as issues related to power consumption, real-time operations, sensing limitations, privacy and record of real-life falls.

Components required:

Intel Edison

Grove base shield v2

Grove 3 axis digital accelerometer

Grove Buzzer

Grove Cables

9v Battery

9v Battery clip

Micro USB Cables

Software used:

Arduino 1.5.3-Intel 1.0.4 for windows

PuTTY

Step 1: Setup the Edison

Assemble the Edison with the Grove board. Place the buzzer on D4 and the accelerometer on I2C.

Step 2: Code

Copy the FallDetector.ino on to Edison and compile it. Now if there is a fall, the buzzer will go off.

FallDetector.ino
Download

Step 3: Optional: Connecting It to Cloud

Now using PuTTY connect your Edison to the intel cloud analytic.

Instructions can be found on https://www.instructables.com/id/Connecting-Intel-E...

Here your sensors are the accelerometer values and a flag variable, trigger which indicates fall.

Step 4: Future Scope

In future we can even add a health monitoring system enabling us to determine future falls.

Also in addition to this we can even add an mobile application showing the details about fall and an option for 3 pre-entered text messages and a call to be sent in case of a fall being detected.