Zhang Fan, Chen Shixiong, Zhang Haoshi, Zhang Xiufeng, Li Guanglin
Institute of Biomedical and Health Engineering and the Key Lab of Human-Machine-Intelligence Synergic System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.
The National Research Center for Rehabilitation Technical Aids, Beijing, China.
Med Eng Phys. 2014 Aug;36(8):1007-13. doi: 10.1016/j.medengphy.2014.05.009. Epub 2014 Jun 2.
Bioelectric signals such as electromyogram (EMG) and electrocardiogram (ECG) are often affected by various low-frequency trending interferences. It is critical to remove these interferences from the recordings so that the critical features of the bioelectric signals could be clearly observed. In this study, an advanced method based on smoothness prior approach (SPA) was proposed to solve this problem. EMG and ECG signals from both the MIT-BIH database and the experiments were employed to evaluate the detrending performance of the proposed method. For comparison purposes, a conventional high-pass Butterworth filter was also used for the detrending of the EMG and ECG signals. Two numerical measures, the correlation coefficient (CC) and root mean square error (RMSE) between the clean data and the detrended data, were calculated to evaluate the detrending performance. The results showed that the proposed SPA method outperformed the high-pass filtering method in reducing various kinds of trending interferences and preserving the desired frequency contents of the EMG and ECG signals. The study suggested that the SPA method might be a promising approach in detrending bioelectric signals.
生物电信号,如肌电图(EMG)和心电图(ECG),常常受到各种低频趋势干扰的影响。从记录中去除这些干扰至关重要,以便能够清晰地观察到生物电信号的关键特征。在本研究中,提出了一种基于平滑先验方法(SPA)的先进方法来解决这个问题。使用来自麻省理工学院 - 贝斯以色列女执事医疗中心(MIT - BIH)数据库和实验的肌电图和心电图信号来评估所提出方法的去趋势性能。为了进行比较,还使用传统的高通巴特沃斯滤波器对肌电图和心电图信号进行去趋势处理。计算了两个数值指标,即干净数据与去趋势数据之间的相关系数(CC)和均方根误差(RMSE),以评估去趋势性能。结果表明,所提出的SPA方法在减少各种趋势干扰和保留肌电图和心电图信号的期望频率成分方面优于高通滤波方法。该研究表明,SPA方法可能是一种用于生物电信号去趋势处理的有前途的方法。