Movement-Type Classification Using Acceleration Sensor
Keywords:
Fast fourier transform, walking-pattern, running-pattern, motion profile.Abstract
The most common moving processes include walking, running, going up stairs, and going down stairs. People distinguish the first two types of movement based on their perception of speed. However, people’s values are different, making it difficult to distinguish walking from running objectively. On the other hand, speeds of walking are usually not far from speeds of going upstairs/downstairs. Thus, it is difficult to train a computer to objectively distinguish these four types of movement only based on “speed”. This study tried to find a way to quantify movements during the experiments. Also a sensor was used in the experiments to help obtain the data during the movements. The sensor could continuously record the detailed information of each movement using packets. The pattern of each movement was represented using the corresponding acceleration data along the three axes of this
study, the x axis (horizontally moving back and forth), the y axis
(vertically moving up and down), and the z axis (horizontally
moving in and out). Through the Fast Fourier Transform, the
differences among various types of movement were observed.
The extracted information was further used as the basis for
computers to distinguish the four types of movement, walking,
running, going upstairs, and going downstairs.
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