A modified basic scale entropy computing method for one-dimensional signal complexity analysis in real time
Conference: BIBE 2019 - The Third International Conference on Biological Information and Biomedical Engineering
06/20/2019 - 06/22/2019 at Hangzhou, China
Proceedings: BIBE 2019
Pages: 6Language: englishTyp: PDF
Personal VDE Members are entitled to a 10% discount on this title
Authors:
Shao, Huijie; Gu, Ya; Liu, Jicheng (School of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, China)
Chou, Yongxin (School of Electrical and Automatic Engineering, Changshu Institute of Technology, Suzhou, China & The East China Science and Technology Research Institute of Changshu Co., Ltd, Suzhou, China)
Wang, Liguo (Department of Orthopaedics Gansu Provincial Hospital, Lanzhou, China)
Abstract:
Basic scale entropy (BSE) is one of the important indicators for evaluating the complexity of one-dimensional signal, while it is difficult to be employed to analyze the signal in microcontroller for its long time-consumption. In this study, a modified basic scale entropy (MBSE) computing method based on the theory of BSE and the process of data updating in buffer is proposed to reduce the computational complexity. The BSE and MBSE methods are engaged to compute the complexity of random noise, P-P intervals, and R-R intervals. The results indicate that the MBSE method saves more time and installed memory space than BSE method, especially in evaluating the long-term complexity of the signal (with longer sign vector and buffer space). Thus, the proposed can be used to compute the complexity of one-dimensional signal in real-time.