We developed a smart-phone based system to measure the activities of autonomic nervous system during everyday life. Using commonly marketed smart phones, by touching your fingertips on the phone’s camera over a short...We developed a smart-phone based system to measure the activities of autonomic nervous system during everyday life. Using commonly marketed smart phones, by touching your fingertips on the phone’s camera over a short time of about 30 seconds, it will detect changes in the brightness of the blood flow and in turn analyze your heart rate variability. By using this system, about 100,000 cases were measured and from this large amount of data regarding heart rate variability, we evaluated the autonomic nervous function in their daily life. As a result, for the correlation between autonomic nervous system and age, we found that as the increase of age, the total power becomes decreased and the sympathetic nervous system tends to increase between thirties and fifties. For the correlation between autonomic nervous system and BMI (Body Mass Index), it is found that in general, the higher the BMI, the lower the total power and the stronger the sympathetic nervous system. In other words, people who are fat are lower about the total power and stronger about the sympathetic nervous system. In addition, for the correlation between autonomic nervous system and one day life, it is found that total power and sympathetic function tend to increase, while as evening approaches, sympathetic function tends to become suppressed.展开更多
Background: The optimal breathing pattern (BP) to effectively regulate autonomic nervous activity is yet to be determined. Objective: We aimed to clarify the effects of four BPs (BP-1, BP-2, BP-3, and BP-4) on autonom...Background: The optimal breathing pattern (BP) to effectively regulate autonomic nervous activity is yet to be determined. Objective: We aimed to clarify the effects of four BPs (BP-1, BP-2, BP-3, and BP-4) on autonomic nervous activity and mood changes. Methods: Eleven healthy adult female volunteers performed each BP in a sitting position for 5 min in a resting state. The time required for one breathing for BP-1 (30 breaths/min), BP-2 (20 breaths/min), BP-3 (15 breaths/min), and BP-4 (10 breaths/min) were 2 s, 3 s, 4 s, and 6 s, respectively. The inspiratory/expiratory time of one breathing was 1 s/1 s, 1 s/2 s, 2 s/2 s, and 2 s/4 s. The high-frequency component (HF) and low-frequency component (LF)/HF ratio during and before (control) performing a BP were calculated from heart rate variability data recorded using the wearable biometric information tracer M-BIT. Three mood changes, which are, “pleasure—unpleasure”, “relaxation—tension”, and “sleepiness—arousal”, in the subjects were assessed using the visual analog scale (VAS) before and after performing a BP. Results: Slower breathing induced an increase in HF power and a reduction in LF/HF ratio, indicating increased parasympathetic activity and decreased sympathetic dominance. Furthermore, VAS revealed that slower breathing increased the tendency to feel “pleasure”, “relaxation”, and “sleepiness”. Conclusion: Our results suggest that slower breathing predominates parasympathetic activity in the autonomic nervous system, resulting in a relaxing effect. This result may help lay the foundation for deriving breathing methods that efficiently regulate an individual’s autonomic activity.展开更多
Atrial fibrillation(AF)is the most common supraventricular arrhythmia in clinical practice,and many patients exhibit silent AF.Variables based on Electrocardiogram(ECG)have shown promise in assessing AF risk in the pr...Atrial fibrillation(AF)is the most common supraventricular arrhythmia in clinical practice,and many patients exhibit silent AF.Variables based on Electrocardiogram(ECG)have shown promise in assessing AF risk in the previous study.This study protocol proposes a systematic approach,named RAF-ECP,to evaluate the role of ECG phenotypes in assessing the risk of AF.The protocol aims to standardize the definition and calculation of ECG phenotypes,ensuring consistency and compa-rability across different research studies and healthcare settings.Data will be collected from multiple clinical laboratories,with an anticipated sample size of 10,000 cases(lead I and II,10 s)evenly distributed between subjects with and without AF events in one-year time frame.By analyzing ECG data and baseline information,statistical tests and machine learning classifiers will be employed to identify significant risk factors and develop a comprehensive risk assessment model for AF.The anticipated outcomes include hazard ratio values,confidence intervals,p values,as well as accuracy,sensitivity,and specificity measures.The study also discusses the clinical relevance and potential benefits of standardizing ECG phenotypes,emphasizing the need for collaboration between multiple centers to obtain diverse and representative datasets.The proposed RAF-ECP study protocol offers a novel and significant approach to understanding the impact of ECG phenotypes on AF risk assessment.Its integration of statistical analysis and machine learning techniques has the potential to advance AF research and contribute to the development of improved risk prediction models and clinical decision support tools.展开更多
文摘We developed a smart-phone based system to measure the activities of autonomic nervous system during everyday life. Using commonly marketed smart phones, by touching your fingertips on the phone’s camera over a short time of about 30 seconds, it will detect changes in the brightness of the blood flow and in turn analyze your heart rate variability. By using this system, about 100,000 cases were measured and from this large amount of data regarding heart rate variability, we evaluated the autonomic nervous function in their daily life. As a result, for the correlation between autonomic nervous system and age, we found that as the increase of age, the total power becomes decreased and the sympathetic nervous system tends to increase between thirties and fifties. For the correlation between autonomic nervous system and BMI (Body Mass Index), it is found that in general, the higher the BMI, the lower the total power and the stronger the sympathetic nervous system. In other words, people who are fat are lower about the total power and stronger about the sympathetic nervous system. In addition, for the correlation between autonomic nervous system and one day life, it is found that total power and sympathetic function tend to increase, while as evening approaches, sympathetic function tends to become suppressed.
文摘Background: The optimal breathing pattern (BP) to effectively regulate autonomic nervous activity is yet to be determined. Objective: We aimed to clarify the effects of four BPs (BP-1, BP-2, BP-3, and BP-4) on autonomic nervous activity and mood changes. Methods: Eleven healthy adult female volunteers performed each BP in a sitting position for 5 min in a resting state. The time required for one breathing for BP-1 (30 breaths/min), BP-2 (20 breaths/min), BP-3 (15 breaths/min), and BP-4 (10 breaths/min) were 2 s, 3 s, 4 s, and 6 s, respectively. The inspiratory/expiratory time of one breathing was 1 s/1 s, 1 s/2 s, 2 s/2 s, and 2 s/4 s. The high-frequency component (HF) and low-frequency component (LF)/HF ratio during and before (control) performing a BP were calculated from heart rate variability data recorded using the wearable biometric information tracer M-BIT. Three mood changes, which are, “pleasure—unpleasure”, “relaxation—tension”, and “sleepiness—arousal”, in the subjects were assessed using the visual analog scale (VAS) before and after performing a BP. Results: Slower breathing induced an increase in HF power and a reduction in LF/HF ratio, indicating increased parasympathetic activity and decreased sympathetic dominance. Furthermore, VAS revealed that slower breathing increased the tendency to feel “pleasure”, “relaxation”, and “sleepiness”. Conclusion: Our results suggest that slower breathing predominates parasympathetic activity in the autonomic nervous system, resulting in a relaxing effect. This result may help lay the foundation for deriving breathing methods that efficiently regulate an individual’s autonomic activity.
基金funded by Shanghai Municipal Science and Technology Major Project,under Grant No.2017SHZDZX01Medical Scientific Research Key Project of Jiangsu Commission of Health,under Grant No.ZDB2020025.
文摘Atrial fibrillation(AF)is the most common supraventricular arrhythmia in clinical practice,and many patients exhibit silent AF.Variables based on Electrocardiogram(ECG)have shown promise in assessing AF risk in the previous study.This study protocol proposes a systematic approach,named RAF-ECP,to evaluate the role of ECG phenotypes in assessing the risk of AF.The protocol aims to standardize the definition and calculation of ECG phenotypes,ensuring consistency and compa-rability across different research studies and healthcare settings.Data will be collected from multiple clinical laboratories,with an anticipated sample size of 10,000 cases(lead I and II,10 s)evenly distributed between subjects with and without AF events in one-year time frame.By analyzing ECG data and baseline information,statistical tests and machine learning classifiers will be employed to identify significant risk factors and develop a comprehensive risk assessment model for AF.The anticipated outcomes include hazard ratio values,confidence intervals,p values,as well as accuracy,sensitivity,and specificity measures.The study also discusses the clinical relevance and potential benefits of standardizing ECG phenotypes,emphasizing the need for collaboration between multiple centers to obtain diverse and representative datasets.The proposed RAF-ECP study protocol offers a novel and significant approach to understanding the impact of ECG phenotypes on AF risk assessment.Its integration of statistical analysis and machine learning techniques has the potential to advance AF research and contribute to the development of improved risk prediction models and clinical decision support tools.
