The Results of the Analysis of Gait According to Mobile Phone Accelerometer Data for an Intelligent System of Authentication of Users-Reference-Cited by-同舟云学术

The Results of the Analysis of Gait According to Mobile Phone Accelerometer Data for an Intelligent System of Authentication of Users

Published:2021 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31th International Conference on Computer Graphics and Vision. Volume 1
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Author:

Grecheneva Anastasia Vladimirovna¹^ORCID,Dorofeev Nikolay Viktorovich¹^ORCID,Goryachev Maxim Sergeevich¹^ORCID

Affiliation:

1. Vladimir State University

Abstract

In this paper, we researched parameters of a person's gait according to the accelerometer of a mobile phone for the further development of the technology of intelligent gait analysis in biometric authentication systems. The paper considers the features of registering human movements based on various methods, describes the problems in assessing gait parameters based on accelerometric data of a mobile phone. The study involved 32 people aged 15 to 67 years, male and female, with different physiological characteristics (height, weight, posture). Also, two twins with the same physiological parameters and a person who underwent surgery on the knee joint were involved in the experimental group. The form of clothing was different-from tight-fitting trousers to loose trousers, and sneakers, shoes and shoes (for women) with low heels were used as shoes. The research methodology included the main types of movements that are performed in a person's daily life when walking. During the research, informative parameters were analyzed: the average value, the mean square deviation, the signal forms (the value of the correlation coefficient). In the course of the research, it was found that the use of a single accelerometric sensor of a mobile phone allows you to distinguish between the movements of a person when moving in different conditions (form of clothing, type of road, etc.), as well as to distinguish people by the features of movements.

Publisher

Keldysh Institute of Applied Mathematics

Reference23 articles.

1. C. Lei, Y. Chuang, Privacy protection for telecare medicine information systems with multiple servers using a biometric-based authenticated key agreement scheme, IEEE Access 7 (2019) 186480-186490. doi:10.1109/ACCESS.2019.2958830.

2. Z. Mehmood, A. Ghani, G. Chen, A. S. Alghamdi, Authentication and secure key management in E-health services: a robust and efficient protocol using biometrics, IEEE Access 7 (2019) 113385-113397. doi:10.1109/ACCESS.2019.2935313.

3. N. V. Dorofeev, A. V. Grecheneva, V. S. Buzhinsky, Assessment of human gait parameters base on accelerometer data, Biomedical Engineering 55 (2021) 92-96. doi:10.1007/s.10527-021-10078-y.

4. G. L. Marcialis, P. Mastinu, F. Roli, Serial fusion of multi-modal biometric systems, IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications, 2010, pp. 1-7. doi:10.1109/BIOMS.2010.5610438.

5. A. E. Sulavko, D. A. Volkov, S. S. Zhumazhanova, R. V. Borisov, Subjects Authentication Based on Secret Biometric Patterns Using Wavelet Analysis and Flexible Neural Networks, XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE), IEEE, Novosibirsk Russia, 2018, pp. 218-227. doi:10.1109/APEIE.2018.8545676.