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 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 similar to 37.87% of others. Therefore, the proposed algorithm can efficiently denoise TMS signals and has advantages in fast processing of multi-channel signals.