<![CDATA[Every persons have their own unique way of walking which is called gait. Gait can be used to identify a person. Gyroscope is a sensor used to detect vibration and measure acceleration based on direction or orientation. This paper presents an individual recognition based on gait using gyroscope sensor embedded in smartphone. The gait data is processed and analyzed by implementing Linear Predictive Coding (LPC) and k-Nearest Neighbour (k-NN). LPC is used to extract features from gait data. It produces feature vector based on combination of p-previous signal and takes only important value of the feature data. Then, k-NN is used for classification, using some calculation methods such as Euclidean, Cityblock, Cosine, and Correlation distance. The gait signals contain x,y,z axis and the signal magnitude. In this paper x,y,z axis and the signal magnitude are also combined to improve the accuracy. The highest accuracy of 99.58% is achieved using signal combination x-y-z-m. Overall, this person detection system produces accuracy between 50% to 99.58%.]]>
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