Алгоритм выбора небольшого числа МЭГ сенсоров:
a smaller number of sensors which are systematically chosen can outperform the entire sensor array when considering noisy measurements. We propose a greedy selection algorithm based upon the QR decomposition that is computationally efficient to implement for MEG. We demonstrate the performance of the sensor selection algorithm for the tasks of signal reconstruction and localization. The performance is dependent upon source localization, with shallow sources easily identified and reconstructed, and deep sources more difficult to locate.
Yeo WJ, Taulu S, Kutz JN. Effcient magnetometer sensor array selection for signal reconstruction and brain source localization. arXiv preprint arXiv:2205.10925. 2022 May 22. https://doi.org/10.48550/arXiv.2205.10925
a smaller number of sensors which are systematically chosen can outperform the entire sensor array when considering noisy measurements. We propose a greedy selection algorithm based upon the QR decomposition that is computationally efficient to implement for MEG. We demonstrate the performance of the sensor selection algorithm for the tasks of signal reconstruction and localization. The performance is dependent upon source localization, with shallow sources easily identified and reconstructed, and deep sources more difficult to locate.
Yeo WJ, Taulu S, Kutz JN. Effcient magnetometer sensor array selection for signal reconstruction and brain source localization. arXiv preprint arXiv:2205.10925. 2022 May 22. https://doi.org/10.48550/arXiv.2205.10925