Signal (Stream) synchronization with White noise sources, in biomedical applications. (April 2015)

• Record Type: Journal Article
• Authors: Vaz, P.; Almeida, V.; Ferreira, L.R.; Correia, C.; Cardoso, J.
• Is Part Of: Biomedical signal processing and control. Volume 18(2015)
• Page Start: 394
• Page End: 400
• Publication Date: 2015-04
• Subjects: Correlation -- Instrument optimization -- Synchronization -- White noise -- Biomedical signals; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2015.02.015
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract : Graphical abstract: Abstract : Highlights: Motivation : Synchronize biomedical signals from several acquisition systems is a difficult task. Methodology : Use of white noise and correlation methods to synchronize biomedical signals. Results : Synchronization with an error of 0.2 ms in an experimental case. Conclusions : This is a reliable and flexible method for several biomedical acquisition systems. Abstract: When multiple acquisition systems are used to simultaneously acquire signals, synchronization issues may arise potentially causing errors in the determination of acquisition starting points and continuous clock offsets and shifts on each device. This paper introduces a processing method to efficiently synchronize these signals in the presence of white noise sources without the requirement of clock sharing or any other digital line exchange. The use of a signal source, such as white noise with a very wide frequency band, is of great interest for synchronization purposes, due to its aperiodic nature. This high bandwidth signal is simultaneously acquired by all the acquisition channels, on distinct systems, and, synchronized afterwards using cross-correlation methods. Two different correlation methods were tested; a global method, used when clock system frequencies are exactly known, and a local method, used when independent clocks evidence shifts over time that cumulatively account for long term acquisition errors in the synchronization process. In a computational simulation with known clock frequencies the results show a synchronization error of ≈1/10 of the time resolution, for both methods. For unknown clock frequencies, the global method achieved an error of 24/10 the time resolution, indicating a much poorer performance. In the experimental set-up, only the local method was tested. The best result shows a synchronization error of 4/10 of the time resolution. All the signal conditioning and acquisition parameters were chosen taking into account potential biomedical applications.