Outcome

Intention

Falls are the leading cause of fatal and non-fatal injuries among elderly people. Adopting prevention techniques could reduce the frequency of falls, however,  it is important to address the aftermath of a fall to ensure appropriate response and care.

The fall detector will act as an emergency service in case the elderly person suffers a fall. It will send a notification to their loved ones enabling them to respond to the situation.

The fall detector will also have an added feature of health tracking and monitoring that will enable the loved ones or the doctors to keep a follow up. 

Bill of materials

1. Particle Photon x1

2. ADXL 355 Accelerometer x1

3. Buzzer x1

4. Button x1

5. Portable Battery x1

6. Jump Wires 

Process

The first version of the device detected the position of a person. We found that for most of the daily movement of a person, the upper body of a person maintains an upright posture. But in the case of a fall, a person will lie on the ground eventually. This result in the posture change of the upper body. Our first algorithm was based on it. 

The second version of the device deteced impact, in other words, a sudden increae of acceleration. This acceleration can be caused by fall as well as some daily movement. Hence, an algorithm to eliminate such noises are necessary. However, we found out that the movement of a human body was quite complex, and it was not just a matter of sensor sensitivity.

The third version of the device detected both impact and position change. We did many user tests to revise the code. These tests include walking, bending, going up/down stairs and so on.  The final version of the fall detector passed all these activities. However, there was still some noises which could not be ultimately eliminated. 

Function

The fall detector had to meet the following requirements:

1. Daily activities of old people should not trigger the detector. These activities including walking, going up /down stairs, turning around, sitting down and standing up. 

2. Falling down should trigger the detector. 

3. In the case of trigger, the device should send notification to someone's mobile phone.

4. In the case of trigger, the device should use some signals to let the user know a falling has been detected. 

5. In the case of false trigger, for example, a drop of the device, the user should be able to cancel the device before the notification is sent.

Reflections

During our research, we found that the industrial products of fall detector for old people use two kinds of sensors,  accelerometers and highly sensitive barometric sensors. Our testing of the accelerometer completely understood the two kinds of data input. Normal activities of a person can cause many disturbances which will also trigger the fall detector. But when we set the sensor to be less sensitive, the whole code was backfiring. After several rounds of iteration of the algorithm, we finally derived our product that could be potentially used by elderly to stop worrying about falling down. This provides a subtle as well as effective solution at the same time.