A fast and efficient algorithm for multi-channel transcranial magnetic stimulation (TMS) signal denoising.
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 filte...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 60; no. 9; pp. 2479 - 2493 |
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| Autores principales: | , , , |
| Formato: | review Journal Article |
| Publicado: |
Springer Nature
Sep2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=158447326&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158447326 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2022 vid: 60 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 158447326 158158532 158447326 NLM35876998 158447326 10.1007/s11517-022-02616-x NLM35876998 158447326 ppf: 2479 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A fast and efficient algorithm for multi-channel transcranial magnetic stimulation (TMS) signal denoising. aug: au: Liu, Jinzhen Tian, Kaiwen Xiong, Hui Zheng, Yu affil: The School of Control Science and Engineering, Tiangong University, 300387, Tianjin, People's Republic of China sug: subj: Transcranial Magnetic Stimulation Algorithms Sensitivity and Specificity Clinical Assessment Tools ab: 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. 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. pubtype: Academic Journal doctype: review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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