A fast and efficient algorithm for multi-channel transcranial magnetic stimulation (TMS) signal denoising

• Published in: Medical & biological engineering & computing Vol. 60; no. 9; pp. 2479 - 2492
• Main Authors: Liu, Jinzhen, Tian, Kaiwen, Xiong, Hui, Zheng, Yu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2022; Springer Nature B.V
• Subjects: Adaptive algorithms; Algorithms; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Computer Applications; Filtration; Flow charts; Human Physiology; Imaging; Information processing; Magnetic fields; Morphology; Noise reduction; Radiology; Review Article; Segments; Signal processing; Transcranial magnetic stimulation; TMS signal; Adaptive framing; Signal denoising; Mathematical morphology
• ISSN: 0140-0118; 1741-0444; 1741-0444
• DOI: 10.1007/s11517-022-02616-x

TMS signal denoising is crucial for 264-channel TMS high-performance magnetic field detection system application, which can be considered as a problem of obtaining an optimal solution to the desired clean signal. In order to efficiently suppress the noise, an improved generalized morphological filtering (IGMF) algorithm based on adaptive framing is proposed. Firstly, the framing points are calculated by the adaptive framing algorithm, and multiple signal segments are obtained by the framing points. Then, the IGMF algorithm is used to filter the signal segments. Finally, the filtered signal segments are merged into TMS signals. The performance of our algorithm is evaluated using the SNR, RMSE, and MAE. Experiments show that the results of the proposed algorithm on three evaluation indicators are superior to others. And the running time of the algorithm is only 2.88 ~ 37.87% of others. Therefore, the proposed algorithm can efficiently denoise TMS signals and has advantages in fast processing of multi-channel signals. Graphical abstract The improved generalized morphological filtering(IGMF) algorithm based on adaptive framing algorithm is used to process 264-channel signals, which achieves signal denoising through a series of operations. The flowchart and result of this algorithm are shown in Fig.  1 .