目的 探讨肌电生物反馈对正常人脑血流动力学的影响及其变化规律。方法 总数30人的健康正常受试者纳入研究,按照表格法随机分为生物反馈实验组和对照组。其中生物反馈组20人,对照组10人。该试验采用肌电生物反馈作为反馈方法,记录两组试验前后双侧大脑前动脉、大脑中动脉和大脑后动脉的平均血流速度和脉动指数。每次生物反馈试验后间隔3天,作为一个生物反馈阶段,总共进行7个阶段。结果 生物反馈组大脑中动脉的平均血流速度在试验前、后高于对照组(P<0.05),而其脉动指数则低于对照组(P<0.05)。生物反馈组在试验前、后大脑中动脉的平均血流速度随着生物反馈次数的增加而增快(P<0.05),而脉动指数则随之而降低(P<0.05)。结论 肌电生物反馈能够增加正常人大脑中动脉的平均血流速度和降低其脉动指数,且随着生物反馈次数的增加而呈现累积效应。

Objective To discuss the effect of electromyographic biofeedback on cerebral hemodynamics in health people. Methods A total of 30 healthy volunteers were enrolled in this study, and randomly divided into biofeedback group (n=20) and control group (n=10). The biofeedback group had been done with electromyographic biofeedback for seven times with 3 days intervals after each test. The data including the mean velocity (Vm) and pulse index (PI) of anterior cerebral artery, middle cerebral artery (MCA) and posterior cerebral artery were collected bilaterally before and after the test using transcranial Doppler in the two groups. Results The values of Vm (P<0.05) were higher and PI (P<0.05) were lower in biofeedback group than those in control group before and after the test. The values of Vm (P<0.05) increased and PI (P<0.05) decreased gradually in biofeedback group from 1st to 7th tests. Conclusion The electromyographic biofeedback can induce to the increasing of velocity of cerebral blood flow and decreasing of PI in MCA, and the additive effect was observed during the 7 tests in biofeedback group.

目的 目前对于生物反馈发挥治疗作用的机理还未完全研究清楚,该实验借助近似熵(ApEn)这一新型的非线性研究方法,研究在生物反馈过程中心电的变化,从而希望发现生物反馈对心脏功能的潜在影响。方法 总数30人的健康正常受试者纳入研究,其中20人为生物反馈实验组,10人为正常对照组。该实验采用肌电生物反馈作为反馈方法,同时记录心电的变化。实验所得数据采用非线性动力学参数—近似熵(ApEn)进行研究。结果 实验组的平均心率在最后两个生物反馈阶段高于对照组。随着实验进展,实验组的心率标准差逐渐缩小,而心率和心电ApEn明显增高。结论 该实验发现生物反馈能够影响心电生理系统,使得心脏系统变得更加健康,展现出更强的抗应激能力,从而揭示了生物反馈潜在的治疗机理。

Objective The mechanism about biofeedback is not complete clear. Our aim was to study changes of cardiac function (electrophysiology) during biofeedback with the help of approximate entropy (ApEn), and a potential new mechanism about neurofeedback may be detected. Methods A total of 30 healthy volunteers participated in this study which consisted of the neurofeedback group(n=20) and the control group (n=10). We applied electromyogram neurofeedback as the feedback method, and simultaneously recorded electroencephalogram(EEG) and electrocardiogram(ECG). We applied the nonlinear analysis ApEn assess obtained data. Results In the biofeedback group the average of heart rate was higher than that of control group in the last two sessions. As the biofeedback experiment sessions were progressed, the standard deviation of heart rate gradually reduced and the ApEn of ECG increased with statistic significance in the biofeedback group. Conclusion We found that biofeedback can influence cardiac electrophysiological system and make cardiac systems progress healthily and achieve greater ability of anti-stress.