Abstract
With the continuous development of science and technology, especially the development of medical technology, electronic information technology, biotechnology and related materials technology, and the social reality that people’s demand for centralized and managed medical services in traditional medical institutions has gradually changed to the demand for new medical services of individualized treatment, disease prevention, and health management, wireless body area network has emerged as the times require, and it provides more perfect supervision and management for people’s health. Although the amount of human perception data is large, its value density is very low. Human perception data is very vulnerable to the influence of perception devices, external environment and human psychology and physiology, which results in large fluctuation of perception data and cannot fully reflect the real state of human health. Therefore, data cleaning for biological information in the body area network is particularly important. For the X Y Z triaxial displacement data of biological activity location, a statistical mathematical model represented by a box diagram is proposed to clean the data. The final results show that the scheme improves the accuracy of data in the experiment of motion detection.
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Acknowledgment
We gratefully acknowledge anonymous reviewers who read drafts and made many helpful suggestions. This work is supported by Guangxi Vocational Education Teaching Reform Research Project (GXGZJG2018A040), Fundamental Research Funds for the Central Universities of China (328201911), Higher Education Department of the Ministry of Education Industry-university Cooperative Education Project and Education and Teaching Reform Project of Beijing Electronic and Technology Institute.
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Guo, J., Zong, Y., Chen, F., Guo, C., Xie, D. (2020). Data Cleaning Algorithm Based on Body Area Network. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Lecture Notes in Computer Science(), vol 12239. Springer, Cham. https://doi.org/10.1007/978-3-030-57884-8_51
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DOI: https://doi.org/10.1007/978-3-030-57884-8_51
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