Abstract
Falling is one of the most common accidents with potentially irreversible
consequences, especially considering special groups, such as the
elderly or disabled. One approach to solve this issue would be an
early detection of the falling event. Towards reaching the goal of
early fall detection, we have worked on distinguishing and monitoring
some basic human activities such as walking and running. Since we
plan to implement the system mostly for seniors and the disabled,
simplicity of the usage becomes very important.
We have successfully implemented an algorithm that would not require
the acceleration sensor to be fixed in a specific position (the smart
phone itself in our application), whereas most of the previous research
dictates the sensor to be fixed in a certain direction. This algorithm
reviews data from the accelerometer to determine if a user has taken
a step or not and keeps track of the total amount of steps. After
testing, the algorithm was more accurate than a commercial pedometer
in terms of comparing outputs to the actual number of steps taken
by the user.
Original language | English |
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Title of host publication | Proc. of the 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS) |
State | Published - Aug 2012 |