1.Post-effect of acupuncture on brain functional connectivity
Bo LIU ; Xian LIU ; Yu LONG ; Jun CHEN ; Zhiguang CHEN ; Xiaojing SHANG ; Weizhao MO ; Xiaofan LI
Chinese Journal of Medical Imaging Technology 2009;25(12):2186-2189
Objective To explore post-effect of acupuncturing ST36 (Zusanli) on brain functional connectivity. Methods Twelve healthy volunteers participated in this experiment. The fMRI data taken before and 25 minutes after removed acupuncturing stimulation were analyzed, while posterior cingulated cortex were chosen as seed points. Results At 25 minutes after removed acupuncturing stimulation, new increased functional connectivity were found in the left paracentral lobule, right superior parietal lobule and right postcentral gyrus. After acupuncture, there was intensity functional connectivity greater than in primary brain regions. Conclusion Post-effect of acupuncture can increase functional connectivity in healthy volunteer's brain.
2.An endpoint-detection algorithm of surface electromyography insensitive to electrocardiogram interference.
Weizhao XU ; Hongqiang MO ; Lianfang TIAN ; Demiao OU
Journal of Biomedical Engineering 2018;35(6):953-958
Surface electromyography (sEMG) has been widely used in the study of clinical medicine, rehabilitation medicine, sports, etc., and its endpoints should be detected accurately before analyzing. However, endpoint detection is vulnerable to electrocardiogram (ECG) interference when the sEMG recorders are placed near the heart. In this paper, an endpoint-detection algorithm which is insensitive to ECG interference is proposed. In the algorithm, endpoints of sEMG are detected based on the short-time energy and short-time zero-crossing rates of sEMG. The thresholds of short-time energy and short-time zero-crossing rate are set according to the statistical difference of short-time zero-crossing rate between sEMG and ECG, and the statistical difference of short-time energy between sEMG and the background noise. Experiment results on the sEMG of rectus abdominis muscle demonstrate that the algorithm detects the endpoints of the sEMG with a high accuracy rate of 95.6%.