Note: There might be no orientation change in a fall but this algorithm requires the involvement of orientation change.Loona has a behavior and personality just like an adorable pet:Įvery time she wakes up from her sleep mode, Loona curiously roams around the house if she encounters any obstacles, she will approach and observe them closely. There is a loop, meaning that if a condition is false at any stage, the process goes back to start and re-executes. After that, we check to see if orientation remains the same for some time. If all of these are detected as true conditions, then we need to check whether there is a change in orientation within 500ms and usually, it's true if the above conditions are true. Then we need to check that it breaks the high threshold in some milliseconds - let's say 500ms. The lower threshold is the minimum threshold in the range decided by us and the value gradually increases up to the high threshold. The above equation is of the magnitude of acceleration and the three values ax, ay, and az are the acceleration of X-, Y-, and Z-axis respectively as per data collected.Īfter calculating the acceleration magnitude, we need to know if its value breaks the lower threshold. First of all, we need to decide on an algorithm. We will also try to send the SOS message via a Wi-Fi module. The circuit we discuss in this tutorial is built around an Arduino UNO and an MPU6050 accelerometer and gyroscope breakout module. But we also need to decide a threshold so that the system can differentiate between a fall and normal activity. A gyroscope is used to determine an orientation and an accelerometer provides the information about the angular parameter as three-axis data. So, an algorithm must detect a fall in these situations when there is a rapid change of position in a very short amount of time.Ĭommonly, fall detection systems use a gyroscope and an accelerometer. In most fall situations, the body leans to the side and touches the ground with high acceleration. There are several kinds of fall detection methods and the algorithm each uses is what makes them unique and accurate.

Fall detection can also be done by a surveillance camera, also known as a computer-vision-based fall detection system. Nowadays, fall detectors are commonly included in smartwatches, wearable fitness trackers, and other types of wearables. Making a system to alert when a fall occurs is helpful, as it provides peace of mind to both the wearer and their loved ones. Falls for the elderly can be especially serious, as they can lead to serious health issues. Fall detection is a major challenge in the public healthcare domain.

Diy human gyroscope