1.Application of heart rate mathematical analysis for body functional state evaluation
Journal of Practical Medicine 2002;435(11):44-48
Statistical analysis of 100 successive RR interval time in ECG, mean heart rate was carried out in 3 groups. The 1st group consisted of 23 healthy men, aged 19.3. The 2nd group consisted of 8 men, aged 21,6 and suffered from inconciousness during working time. The 3rd group consisted of 6 men, aged 19.2 with bad occupational adaptation. Results: heart rate index of 2nd and 3rd groups at rest clearly represented functional strain in comparison with that of 1st group were decreased, mean HR and SI were increased. After 30 and 60 minutes of stricly standing, all index of 3 groups were significantly greater than that at rest, but the index variation of the 1st group were higher than in 2nd and 3rd groups.
Analysis
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Heart Rate
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physiology
2.Comparison of heart rate variability measurements between ballistocardiogram and electrocardiography.
Kun WANG ; Tiangang ZHU ; Xianwen ZHANG ; Chao YU ; Xinrong CAO ; Jintian TANG ; Zheng WAN
Chinese Journal of Cardiology 2015;43(5):448-451
OBJECTIVETo compare the heart rate variability (HRV) measurements between ballistocardiogram (BCG) and electrocardiography (ECG).
METHODSThe signals of BCG and ECG of 21 patients were collected synchronously. JJ intervals of BCG and RR intervals of ECG were used to calculate the cardiac periods. The parameters of HRV analysis were calculated in time domain analysis, frequency domain analysis and nonlinear analysis. The results derived from BCG and ECG were compared.
RESULTSThe parameters of HRV analysis calculated from BCG and ECG had high similarity. The correlation coefficients of SDNN, TP, LF, HF and SD2 between the BCG and ECG methods were high (r = 1). The correlation coefficients of rMSSD and SD2 were 0.99 and of PNN50 and LF/HF were 0.98 between the two methods. HRV analysis results derived from the two methods were similar (P > 0.05).
CONCLUSIONHRV could also be measured reliably by calculating the JJ interval from BCG.
Ballistocardiography ; Electrocardiography ; Heart ; physiology ; Heart Rate ; Humans
3.Interactive guided breathing technology.
Zheng-Bo ZHANG ; Wei-Dong WANG ; Kai-Yuan LI ; Bu-Qing WANG ; Qing ANG
Chinese Journal of Medical Instrumentation 2008;32(2):86-119
OBJECTScientific guided breathing technology is to be studied based on the cardiopulmonary interaction.
METHODSHeart rate variability was used as the target function to study the smoothly respiratory relaxation procedure in order to acquire the common pattern of regular and slow breathing.
RESULTSMusic based on the acquired common pattern was created and a musical pattern temporally-related to the breathing movement monitored by a sensor could be chosen to guide the breathing interactively.
Breathing Exercises ; Heart Rate ; physiology ; Humans ; Respiration
4.Heart rate measurement algorithm based on artificial intelligence.
Chinese Journal of Medical Instrumentation 2010;34(1):1-3
Based on the heart rate measurement method using time-lapse image of human cheek, this paper proposes a novel measurement algorithm based on Artificial Intelligence. The algorithm combining with fuzzy logic theory acquires the heart beat point by using the defined fuzzy membership function of each sampled point. As a result, it calculates the heart rate by counting the heart beat points in a certain time period. Experiment shows said algorithm satisfies in operability, accuracy and robustness, which leads to constant practical value.
Algorithms
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Artificial Intelligence
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Heart Rate
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physiology
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Humans
5.The role of vagal innervation in the variability of heart beat.
Shu-Yun HE ; San-Jue HU ; Xian-Hui WANG ; Sheng HAN
Acta Physiologica Sinica 2002;54(2):129-132
To determine the role of vagi in heart rate variability, conscious rabbits were employed and electrocardiogram was recorded under conditions of bilateral vagi intact, unilateral vagotomy, and bilateral vagotomy. The variability of RR intervals (RRI) was analyzed using power spectrum and approximate entropy (ApEn). The results showed that the values of high frequency power (HF) component, low frequency power (LF) component and ApEn in animals with bilateral vagi intact were the highest, but the LF/HF ratio was the lowest; unilateral vagotomy decreased ApEn, right vagotomy increased LF/HF ratio but left vagotomy did not; the LF/HF ratio increased while ApEn decreased significantly in animals with bilateral vagotomy. It is suggested that the variability of RRI is mainly regulated by the vagi and the role of right vagi is more important than that of the left. When measuring heart rate variability, the results obtained with conventional method are consistent with those with nonlinear method.
Animals
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Entropy
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Heart Rate
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physiology
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Male
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Rabbits
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Vagus Nerve
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physiology
7.A noninvasive method for measuring electrocardiogram from chick embryos and researching changes of their heart rate during the late period of development.
Jian-Song DING ; Jihua NIE ; Su-Ping ZHANG
Chinese Journal of Applied Physiology 2009;25(1):48-106
Animals
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Chick Embryo
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physiology
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Electrocardiography
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methods
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Heart
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embryology
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physiology
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Heart Rate
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physiology
9.Investigating the fractal characteristic of heart rate variability during anesthesia.
Xiaofang LIU ; Wenlong XU ; Wu CHEN ; Zhiqian YE
Journal of Biomedical Engineering 2006;23(3):492-495
By use of fractal analysis indexes-correlation dimension, fractal dimension and scaling exponent, the heart rate variability signals obtained from 38 subjects' ECG during anesthesia are analyzed. The results show that there is an obvious change of fractal characteristic of heart rate variability during anesthesia. The correlation dimension (P < 0.000001) during anesthesia is evidently less than that during consciousness, while the short-range scaling exponent a (P < 0.0001) during consciousness is evidently less than that during anesthesia. These illustrate that the difference in fractal characteristic between anesthesia and well-balanced state can be detected by the fractal analysis of heart rate variability. In the end, the paper poses that the analysis of heart rate variability is fit for monitoring the depth of anesthesia by detrended fluctuation analysis.
Anesthesia
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Electrocardiography
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Heart Rate
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physiology
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Humans
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Monitoring, Physiologic
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methods