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Letter

Exploration and Research of Human Identification Scheme Based on Inertial Data

Department of Precision Instrument, Engineering Research Center for Navigation Technology, Tsinghua University, Beijing 100084, China
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Author to whom correspondence should be addressed.
Sensors 2020, 20(12), 3444; https://doi.org/10.3390/s20123444
Received: 20 May 2020 / Revised: 14 June 2020 / Accepted: 17 June 2020 / Published: 18 June 2020
(This article belongs to the Section Wearables)
The identification work based on inertial data is not limited by space, and has high flexibility and concealment. Previous research has shown that inertial data contains information related to behavior categories. This article discusses whether inertial data contains information related to human identity. The classification experiment, based on the neural network feature fitting function, achieves 98.17% accuracy on the test set, confirming that the inertial data can be used for human identification. The accuracy of the classification method without feature extraction on the test set is only 63.84%, which further indicates the need for extracting features related to human identity from the changes in inertial data. In addition, the research on classification accuracy based on statistical features discusses the effect of different feature extraction functions on the results. The article also discusses the dimensionality reduction processing and visualization results of the collected data and the extracted features, which helps to intuitively assess the existence of features and the quality of different feature extraction effects. View Full-Text
Keywords: human identification; inertial data; classification experiments; feature visualization human identification; inertial data; classification experiments; feature visualization
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MDPI and ACS Style

Gao, Z.; Sun, J.; Yang, H.; Tan, J.; Zhou, B.; Wei, Q.; Zhang, R. Exploration and Research of Human Identification Scheme Based on Inertial Data. Sensors 2020, 20, 3444. https://doi.org/10.3390/s20123444

AMA Style

Gao Z, Sun J, Yang H, Tan J, Zhou B, Wei Q, Zhang R. Exploration and Research of Human Identification Scheme Based on Inertial Data. Sensors. 2020; 20(12):3444. https://doi.org/10.3390/s20123444

Chicago/Turabian Style

Gao, Zhenyi, Jiayang Sun, Haotian Yang, Jiarui Tan, Bin Zhou, Qi Wei, and Rong Zhang. 2020. "Exploration and Research of Human Identification Scheme Based on Inertial Data" Sensors 20, no. 12: 3444. https://doi.org/10.3390/s20123444

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