正常人短时心率变异性指标在长时序列中的分布特性及其年龄的影响
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摘要
无创的心率变异性(HRV)检测所反映的自主神经状态可受生理、病理和心理等因素影响。提出研究短时HRV分析指标在长时序列中的分布特性,并探讨在正常人中随年龄可能发生的变化。将THEW中Normal子数据库中年龄大于18岁的Holter数据(n=177)分为5个年龄组(18≤y≤25,n=35; 2555,n=23)。利用5 min的滑动窗口、2.5 min的步长,计算每个滑动窗的RR间期均值(MRRI)、LF/HF和短时分形尺度指数(α_1),然后基于长时序列,分别计算MRRI和LF/HF,以及MRRI和α_1这两种配对的Spearman相关系数,并在各组内统计相关性良好人数的百分占比。然后,以具有正常作息时间和数据长度为筛选标准,从177名正常人中筛选出93名250.05)),但在其他时段这些参数则可能存在显著差异。随着可穿戴技术的发展,长时心率序列(RR间期序列)的可获得性大幅度提高,该研究结果对于拓展长时序列的HRV分析方法可提供新的思路。
The autonomic nervous system state reflected by non-invasive heart rate variability(HRV) can be affected by physiological, pathological and psychological factors. In this paper, we proposed to study the distribution of short-term HRV indices in long-term series and explore the possible changes of autonomic nervous system with age in normal people. The data were provided by the database Normal in THEW(http://www.thew-project.org). The 24-hour Holter data of normal people(n=177) were divided into 5 age groups(18≤y≤25, n=35; 2555, n=23). Linear and non-linear measures of short-term HRV indices(LF/HF and α_1) were performed along the 24 h RR interval(RRI) series using a 5 min sliding window with 2.5 min overlap. Then, mean RRI(MRRI) in each sliding window were calculated. For each Holter record, Spearman correlation coefficients(Spearman CC) between MRRI and LF/HF, as well as that between MRRI and α_1 were calculated. And the percentage of people with good correlation in each age group was counted. Then, 93 subjects(25 55(78.26% for MRRI vs LF/HF, 65.22% for MRRI vs α_1). In the morning minimum EMRRI episodes, there were no significant differences in EM_MRRI, EM_LF/HF and EM_α_1 among the 4 groups, but there might be significant differences in other periods. With the development of wearable technology, the availability of long-term RRI series has been greatly improved. The results of this study provide a new idea for HRV analysis.
The autonomic nervous system state reflected by non-invasive heart rate variability(HRV) can be affected by physiological, pathological and psychological factors. In this paper, we proposed to study the distribution of short-term HRV indices in long-term series and explore the possible changes of autonomic nervous system with age in normal people. The data were provided by the database Normal in THEW(http://www.thew-project.org). The 24-hour Holter data of normal people(n=177) were divided into 5 age groups(18≤y≤25, n=35; 25
引文
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[27] Mahdiani S,Jeyhani V,Peltokangas M,et al.Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis?[C]// The 37th Annual International Conference of the IEEE Engineering and Medicine and Biology Society.Milan:IEEE,2015:5948-5951.
[2] Xhyheri B,Manfrini O,Mazzolini M,et al.Heart rate variability today [J].Progress in Cardiovascular Diseases,2012,55:321-331.
[3] Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.Heart rate variability:standards of measurement,physiological interpretation and clinical use [J].Circulation,1996,93:1043-1065.
[4] Kleiger RE,Stein PK,Bigger JT.Heart rate variability:Measurement and clinical utility [J].Annals of Noninvasive Electrocardiology,2005,10(1):88-101.
[5] Fei L,Copie X,Malik M,et al.Short- and long-term assessment of heart rate variability for risk stratification after acute myocardial infarction[J].The American Journal of Cardiology,1996,77(9):681-684.
[6] Voss A,Schroeder R,Vallverdú M,et al.Short-term vs long-term heart rate variability in ischemic cardiomyopathy risk stratification [J].Frontiers in Physiology,2013,4:1-15.
[7] Dantas EM,Kemp AH,Andreao RV,et al.Reference values for short-term resting-state heart rate variability in healthy adults:Results from the Brazilian Longitudinal Study of Adult Health—ELSA-Brasil study [J].Psychophysiology,2018,55:e13052.
[8] Kuusela T.Methodological aspects of heart rate variability analysis [M]// Heart Rate Variability (HRV) Signal Analysis [M].New York:CRC Press,2012:9-42.
[9] 颜延,邹浩,周林,等.可穿戴技术的发展 [J].中国生物医学工程学报,2015,34:644-653.
[10] Park S,Heo SW,Lee W.Self-powered ultra-flexible electronics via nanograting-patterned organic photovoltaics [J].Nature,2018,561:516-521.
[11] Almeida-Santos MA,Barreto-Filho JA,Oliveira JLM,et al.Age,heart rate variability and patterns of autonomic regulation of the heart [J].Archives of Gerontology and Geriatrics,2016,63:1-8.
[12] Zulfifiqar U,Jurivich DA,Gao Eeihua,et al.Relation of high heart rate variability to healthy longevity[J].Am J Cardiol 2010,105:1181-1185.
[13] Peng CK,Havlin S,Stanley HE,et al.Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series [J].Chaos,1995,5(1):82-87.
[14] Boardman A,Schlindwein FS,Rocha AP,et al.A study on the optimum order of autoregressive models for heart rate variability [J].Physiol Meas,2002,23:325-336.
[15] Bonnemeier H,Richardt G,Potratz J,et al.Circadian profile of cardiac autonomic nervous modulation in healthy subjects:Differing effects of aging and gender on heart rate variability [J].Journal of Cardiovascular Electrophysiology,2003,14(8):791-799.
[16] Junior EC,Oliveira FM.Attenuation of vagal modulation with aging-Univariate and bivariate analysis of HRV [C]// The 39th Annual International Conference of the IEEE Engineering and Medicine and Biology Society (EMBC).Jeju Island:IEEE,2017:3178-3181.
[17] Antelmi I,de Paula RS,Shinzato AR,et al.Influence of age,gender,body mass index,and functional capacity on heart rate variability in a cohort of subjects without heart disease [J].The American Journal of Cardiology,2004,93:381-385.
[18] Lipsitz LA,Mietus J,Moody GB,et al.Spectral characteristics of heart rate variability before and during postural tilt:Relations to aging and risk of syncope [J].Circulation,1990,81:1803-1810.
[19] Umetani K,Singer DH,MCcraty R,et al.Twenty-four hour time domain heart rate variability and heart rate:Relations to age and gender over nine decades [J].J Am Coll Cardiol,1998,31:593-601.
[20] Kim HS,Yoon KH,Cho JH.Diurnal heart rate variability fluctuations in normal volunteers [J].J Diabetes Science and Technology,2014,8(2):431-433.
[21] Armstrong RG,Kenny GP,Green G,et al.Diurnal variation in heart rate variability before and after maximal exercise testing [J].Chronobiology International,2011,28:344-351.
[22] Guo Yifang,Stein PK,Cbina S,et al.Circadian rhythm in the cardiovascular system - Chronocardiology [J].Am Heart J,2003,145:779-786.
[23] Liu Hongduoer,Zhan Ping,Wang Zhigang,et al.Assessment of autonomic nerve activity by circadian rhythm at different stages after acute myocardial infarction based on Holter data [J].Computing in Cardiology,2015,42:613-616.
[24] 李晨曦,潘越,王志刚,等.以线性参数模型和信息分解方法评价QT变异性对心率变异性的响应[J].中国生物医学工程学报,2018,37(3):305-312.
[25] Kario K,Pickering TG,Umeda Y,et al.Morning surge in blood pressure as a predictor of silent and clinical cerebrovascular disease in elderly hypertensives:A prospective study [J].Circulation,2003,107:1401-1406.
[26] Ellis RJ,Zhu B,Koenig J,et al.A careful look at ECG sampling frequency and R-peak interpolation on short-term measures of heart rate variability.Physiological Measurement,2015,36:1827-1852.
[27] Mahdiani S,Jeyhani V,Peltokangas M,et al.Is 50 Hz high enough ECG sampling frequency for accurate HRV analysis?[C]// The 37th Annual International Conference of the IEEE Engineering and Medicine and Biology Society.Milan:IEEE,2015:5948-5951.