Heart rate variability (HRV) analysis technology based on an autoregressive (AR) model is widely used in the assessment of autonomic nervous system function. The order of AR models has important influence on the accuracy of HRV analysis. This article presents a method to determine the optimum order of AR models. After acquiring the ECG signal of 46 healthy adults in their natural breathing state and extracting the beat-to-beat intervals (RRI) in the ECG, we used two criteria, i.e. final prediction error (FPE ) criterion to estimate the optimum model order for AR models, and prediction error whiteness test to decide the reliability of the model. We compared the frequency domain parameters including total power, power in high frequency (HF), power in low frequency (LF), LF power in normalized units and ratio of LF/HF of our HRV analysis to the results of Kubios-HRV. The results showed that the correlation coefficients of the five parameters between our methods and Kubios-HRV were greater than 0.95, and the Bland-Altman plot of the parameters was in the consistent band. The results indicate that the optimization algorithm of HRV analysis based on AR models proposed in this paper can obtain accurate results, and the results of this algorithm has good coherence with those of the Kubios-HRV software in HRV analysis.
Objective
To observe the characteristics of changes of 24hour ambulatory blood pressure and heart rate of 50 patients with anterior ischemic optic neuropathy (AION).
Methods
Fifty patients with AION and the persons without in the control group, which had the same number, gender and age as the patients with AION, underwent 24-hour ambulatory blood pressure and heart rate measurement.
Results
Both groups had no difference in mean blood pressure and heart rate during the daytime (t=1.25,0.93; P＞0.05), higher than those in the nighttime (t=3.63,3.16; P＜0.05). Mean blood pressure and heart rate of AION group at night were lower than those of the control group (t=3.82,1.77; P＜0.01,0.05), especially diastolic pressure of AION group was lower than that of the control group from 2 am to 7 am (P＜0.01), as well as the heart rate from 2 am to 5 am (P＜0.05 or P＜0.01). The curves of blood pressure of AION group showed more gradual and fluctuant rising, while those of the control group showed sharper and less fluctuant rising.
Conclusion
According to the curves of blood pressure rising, the patients with AION may have some defects in auto-regulatory mechanism of blood pressure. The low spots of blood pressure and heart rate in early morning, which might be a critical point leading to AION.
(Chin J Ocul Fundus Dis, 2002, 18: 259-261)
Objective To systematically review the effect of percutaneous acupoint electrical stimulation (TEAS) on heart rate variability (HRV). Methods The PubMed, Embase, Ovid MEDLINE, Cochrane Library, CNKI, WanFang Data, VIP, and CBM databases were electronically searched to collect randomized controlled trials (RCTs) on the effects of percutaneous acupoint electrical stimulation on heart rate variability from inception to February 28, 2023. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Meta-analysis was then performed using RevMan 5.4 software. Results A total of 14 RCTs involving 719 patients were included. The results of meta-analysis showed that SDNN (MD=12.95, 95%CI 9.18 to 16.72, P<0.01), RMSSD (MD=1.81, 95%CI 0.10 to 3.53, P=0.04), pNN50 (MD=1.75, 95%CI 1.02 to 2.48, P<0.01), HF (SMD=0.27, 95%CI 0.01 to 0.52, P=0.04), LF/HF (MD=?0.07, 95%CI ?0.12 to ?0.03, P<0.01), ln-LF (MD=0.63, 95%CI 0.25 to 1.01, P<0.01), ln-HF (MD=1.05, 95%CI 0.60 to 1.49, P<0.01), mean RR (MD=?11.86, 95%CI ?21.77 to ?1.96, P=0.02), and HR (SMD=?0.43, 95%CI ?0.66 to ?0.20, P<0.01) all showed improvement compared with the control group. However, there were no significant differences between the two groups in LF (SMD=0.15, 95%CI ?0.10 to 0.40, P=0.23), LF norm (SMD=0.24, 95%CI ?0.10 to 0.58, P=0.16) or HF norm (SMD=0.25, 95%CI ?0.47 to 0.97, P=0.5). TEAS on PC6: SDNN, pNN50, HF, LF/HF, LF norm, HF norm, ln-LF, ln-HF, and HR all showed improvement compared with the control group. However, there were no significant differences between the two groups in RMSSD, LF, or RR interval. Conclusion This study supports the improvement of heart rate variability by transcutaneous acupoint electrical stimulation and PC6 acupoint selection. Due to the limited quantity and quality of the included studies, more high-quality studies are needed to verify the above conclusion.
【摘要】 目的 探討急性腦梗死對心臟自主神經活性的影響。 方法 Wistar大鼠32只隨機分為正常組、假手術組和腦梗死組，腦梗死組用線栓法行右側大腦中動脈阻塞。腦梗死組和假手術組于術前及術后24 h作心率變異性（HRV）檢測，同時檢測正常組HRV，將3組的HRV指標進行比較。實驗終點取各組心肌組織檢測兒茶酚胺和神經肽Y（NPY），進行組間比較。 結果 術后24 h腦梗死組和正常組、假手術組相比，竇性心搏間期標準差、均方根，總功率譜、高頻功率譜（HF）、低頻功率譜（LF）降低，差異有統計學意義。3組比較LF/HF和分數維無明顯差異。腦梗死組心肌組織去甲腎上腺素（NA）和NPY高于正常組和假手術組。 結論 腦梗死引起心臟自主神經總活性降低、自主神經功能受損，自主神經末梢去甲腎上腺素和NPY的異常分泌可能是重要的原因。【Abstract】 Objective To investigate the effect of acute cerebral infarction on cardiac autonomic nervous activity. Methods A total of 32 Wistar rats were divided into normal group, sham operation group and infarction group by random. Experimental cerebral infarction in Wistar rats was induced by intraluminal occlusion of middle cerebral artery. About 24 hours after the occlusion or 24 hours after sham operation, the heart rate variability (HRV) sequences were measured, and the HRV values in the three groups were compared. The levels of catecholamine and neuropeptide (NPY) in myocardium were measured. Results At the 24th hour after the occlusion, the standard deviation and root mean square standard deviation of R-R interval, the total power, high frequency (HF) and low frequency (LF) in infarction group were lower than those in normal and sham operation group. LF/HF and fractal dimension did not differ much among the three groups. The levels of noradrenaline and NPY in myocardium in infarction group were higher than those in the other groups. Conclusion It is suggested that acute cerebral infarction may cause the decrease of autonomic nervous activity and damage of the autonomic nervous function; the abnormal secretion of noradrenalin in autonomic nerve ending and NPY may be the important reasons.
Lorenz plot (LP) method which gives a global view of long-time electrocardiogram signals, is an efficient simple visualization tool to analyze cardiac arrhythmias, and the morphologies and positions of the extracted attractors may reveal the underlying mechanisms of the onset and termination of arrhythmias. But automatic diagnosis is still impossible because it is lack of the method of extracting attractors by now. We presented here a methodology of attractor extraction and recognition based upon homogeneously statistical properties of the location parameters of scatter points in three dimensional LP (3DLP), which was constructed by three successive RR intervals as X, Y and Z axis in Cartesian coordinate system. Validation experiments were tested in a group of RR-interval time series and tags data with frequent unifocal premature complexes exported from a 24-hour Holter system. The results showed that this method had excellent effective not only on extraction of attractors, but also on automatic recognition of attractors by the location parameters such as the azimuth of the points peak frequency (APF) of eccentric attractors once stereographic projection of 3DLP along the space diagonal. Besides, APF was still a powerful index of differential diagnosis of atrial and ventricular extrasystole. Additional experiments proved that this method was also available on several other arrhythmias. Moreover, there were extremely relevant relationships between 3DLP and two dimensional LPs which indicate any conventional achievement of LPs could be implanted into 3DLP. It would have a broad application prospect to integrate this method into conventional long-time electrocardiogram monitoring and analysis system.
The present paper is to analyze the trend of sinus heart rate RR interphase sequence after a single ventricular premature beat and to compare it with the two parameters, turbulence onset (TO) and turbulence slope (TS). Based on the acquisition of sinus rhythm concussion sample, we in this paper use a piecewise linearization method to extract its linear characteristics, following which we describe shock form with natural language through cloud model. In the process of acquisition, we use the exponential smoothing method to forecast the position where QRS wave may appear to assist QRS wave detection, and use template to judge whether current cardiac is sinus rhythm. And we choose some signals from MIT-BIH Arrhythmia Database to detect whether the algorithm is effective in Matlab. The results show that our method can correctly detect the changing trend of sinus heart rate. The proposed method can achieve real-time detection of sinus rhythm shocks, which is simple and easily implemented, so that it is effective as a supplementary method.
