Godwin Ryan C, Flood William C, Hudson Jeremy P, Benayoun Marc D, Zapadka Michael E, Melvin Ryan L, Whitlow Christopher T
Department of Anesthesiology and Perioperative Medicine, Heersink School of Medicine, University of Alabama, Birmingham, Birmingham, AL, USA.
Department of Radiology, Heersink School of Medicine, University of Alabama, Birmingham, Birmingham, AL, USA.
Heliyon. 2024 Feb 23;10(5):e26664. doi: 10.1016/j.heliyon.2024.e26664. eCollection 2024 Mar 15.
Magnetoencephalography (MEG) measures magnetic fluctuations in the brain generated by neural processes, some of which, such as cardiac signals, are generally removed as artifacts and discarded. However, heart rate variability (HRV) has long been regarded as a biomarker related to autonomic function, suggesting the cardiac signal in MEG contains valuable information that can provide supplemental health information about a patient. To enable access to these ancillary HRV data, we created an automated extraction tool capable of capturing HRV directly from raw MEG data with artificial intelligence. Five scans were conducted with simultaneous MEG and electrocardiogram (ECG) acquisition, which provides a ground truth metric for assessing our algorithms and data processing pipeline. In addition to directly comparing R-peaks between the MEG and ECG signals, this work explores the variation of the corresponding HRV output in time, frequency, and non-linear domains. After removing outlier intervals and aligning the ECG and derived cardiac MEG signals, the RMSE between the RR-intervals of each was = 2 ms, = 2 ms, = 8 ms, = 4 ms, = 13 ms. The findings indicate that cardiac artifacts from MEG data carry sufficient signal to approximate an individual's HRV metrics.
脑磁图（MEG）测量由神经活动产生的大脑中的磁波动，其中一些波动，如心脏信号，通常作为伪迹被去除并丢弃。然而，心率变异性（HRV）长期以来一直被视为与自主神经功能相关的生物标志物，这表明MEG中的心脏信号包含有价值的信息，能够提供关于患者的补充健康信息。为了获取这些辅助的HRV数据，我们创建了一种自动化提取工具，该工具能够利用人工智能直接从原始MEG数据中捕获HRV。我们进行了五次扫描，同时采集MEG和心电图（ECG）数据，这为评估我们的算法和数据处理流程提供了一个基本事实指标。除了直接比较MEG和ECG信号之间的R波峰外，这项工作还探索了相应HRV输出在时间、频率和非线性域中的变化。在去除异常区间并对齐ECG和导出的心脏MEG信号后，两者RR间期之间的均方根误差分别为 = 2毫秒， = 2毫秒， = 8毫秒， = 4毫秒， = 13毫秒。研究结果表明，MEG数据中的心脏伪迹携带了足够的信号来近似个体的HRV指标。
