Abstract Considering the properties of slow change and quasi-periodicity of magnetocardiography (MCG) signal, we use an integrated technique of adaptive and low-pass filtering in dealing with two-channel MCG data measured by high $T_{\rm c}$ SQUIDs. The adaptive filter in the time domain is based on a noise feedback normalized least-mean-square (NLMS) algorithm, and the low-pass filter with a cutoff at 100Hz in the frequency domain characterized by Gaussian functions is combined with a notch at the power line frequency. In this way, both relevant and irrelevant noises in original MCG data are largely eliminated. The method may also be useful for other slowly varying quasi-periodical signals.
Received: 26 May 2005
Revised: 01 September 2005
Accepted manuscript online:
Fund: Project supported by the Major Program for the Fundamental Research of Chinese Academy of Sciences, China (Grant No KJCX2-W4) and the National High Technology Research and Development Program of China (Grant No 2002AA306412).
Cite this article:
Zhu Xue-Min (朱学敏), Ren Yu-Feng (任育峰), Yu Hong-Wei (于洪伟), Zhao Shi-Ping (赵士平), Chen Geng-Hua (陈赓华), Zhang Li-Hua (张利华), Yang Qian-Sheng (杨乾声) A digital filtering scheme for SQUID based magnetocardiography 2006 Chinese Physics 15 100
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
