Human activities & posture recognition : innovative algorithm for highly accurate detection rate : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering in Electronics & Computer Systems Engineering at Massey University, Palmerston North, New Zealand
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Date
2013
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Massey University
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Abstract
The main purpose of thesis is to introduce new
innovative algorithm for “unintentional fall detection”
with 100% accuracy of detecting falls on hard surfaces
which can cause severe and sometimes fatal injuries.
Furthermore this thesis explains how to detect deliberate
human activities such as running, walking etc using the
same algorithm with near perfect accuracy. Subset of the
above mention algorithm is used for posture recognition
as well.
The above mentioned algorithm is converted into computer software
using java programming language for real time detection. A graphical
user interface is developed to display human posture and activity
information.
Most pre-existing algorithms need expensive and wide range of sensors to
achieve this level of accuracy. In this thesis it explains how to use just one
tri-axial accelerometer with wireless zigbee communication module and
achieve far better accuracy. Most of the other sensor types violate human
privacy therefore they are unethical to be used at residence of vulnerable
elderly or sick individual and majority of them are very expensive when
compared to a tri-axial accelerometer which costs just around NZ$5.
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Keywords
Human activity recognition, Mathematical models, Algorithm