scholarly journals Some features of pre-trip medical examination

2021 ◽  
Vol 2 (3) ◽  
pp. 66-70
Author(s):  
Ekaterina M. Gutor ◽  
Elena A. Zhidkova ◽  
Konstantin G. Gurevich
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Medical Management ◽  
Road Safety ◽  
Management System ◽  
Medical Examination

Pre-trip examinations of drivers are the basis of medical management system road safety. Pre-trip examinations should be optimized so as not to miss significant changes in the health status of workers and/or predict such changes. Authors propose to use a pulsogram to analyze parameters of heart rate variability during pre-trip examination of train crews.

scholarly journals Associations Between Heart Rate Variability Measured With a Wrist-Worn Sensor and Older Adults’ Physical Function: Observational Study

10.2196/13757 ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. e13757 ◽  
Author(s):  
Sarah Anne Graham ◽  
Dilip V Jeste ◽  
Ellen E Lee ◽  
Tsung-Chin Wu ◽  
Xin Tu ◽  
...  
Keyword(s):  
Older Adults ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Physical Health ◽  
Physical Function ◽  
Significant Proportion ◽  
Physical Health Status ◽  
Sf 36 ◽  
Composite Scores

Background Heart rate variability (HRV), or variation in beat-to-beat intervals of the heart, is a quantitative measure of autonomic regulation of the cardiovascular system. Low HRV derived from electrocardiogram (ECG) recordings is reported to be related to physical frailty in older adults. Recent advances in wearable technology offer opportunities to more easily integrate monitoring of HRV into regular clinical geriatric health assessments. However, signals obtained from ECG versus wearable photoplethysmography (PPG) devices are different, and a critical first step preceding their widespread use is to determine whether HRV metrics derived from PPG devices also relate to older adults’ physical function. Objective This study aimed to investigate associations between HRV measured with a wrist-worn PPG device, the Empatica E4 sensor, and validated clinical measures of both objective and self-reported physical function in a cohort of older adults living independently within a continuing care senior housing community. Our primary hypothesis was that lower HRV would be associated with lower physical function. In addition, we expected that HRV would explain a significant proportion of variance in measures of physical health status. Methods We evaluated 77 participants from an ongoing study of older adults aged between 65 and 95 years. The assessments encompassed a thorough examination of domains typically included in a geriatric health evaluation. We collected HRV data with the Empatica E4 device and examined bivariate correlations between HRV quantified with the triangular index (HRV TI) and 3 widely used and validated measures of physical functioning—the Short Physical Performance Battery (SPPB), Timed Up and Go (TUG), and Medical Outcomes Study Short Form 36 (SF-36) physical composite scores. We further investigated the additional predictive power of HRV TI on physical health status, as characterized by SF-36 physical composite scores and Cumulative Illness Rating Scale for Geriatrics (CIRS-G) scores, using generalized estimating equation regression analyses with backward elimination. Results We observed significant associations of HRV TI with SPPB (n=52; Spearman ρ=0.41; P=.003), TUG (n=51; ρ=−0.40; P=.004), SF-36 physical composite scores (n=49; ρ=0.37; P=.009), and CIRS-G scores (n=52, ρ=−0.43; P=.001). In addition, the HRV TI explained a significant proportion of variance in SF-36 physical composite scores (R2=0.28 vs 0.11 without HRV) and CIRS-G scores (R2=0.33 vs 0.17 without HRV). Conclusions The HRV TI measured with a relatively novel wrist-worn PPG device was related to both objective (SPPB and TUG) and self-reported (SF-36 physical composite) measures of physical function. In addition, the HRV TI explained additional variance in self-reported physical function and cumulative illness severity beyond traditionally measured aspects of physical health. Future steps include longitudinal tracking of changes in both HRV and physical function, which will add important insights regarding the predictive value of HRV as a biomarker of physical health in older adults.

FETAL HEART RATE VARIABILITY ANALYSIS FROM PHONOCARDIOGRAPHIC RECORDINGS

2011 ◽  
Vol 11 (05) ◽  
pp. 1315-1331 ◽  
Author(s):  
VIJAY S. CHOURASIA ◽  
ANIL KUMAR TIWARI
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Fetal Heart Rate ◽  
Heart Sound ◽  
Fetal Heart ◽  
Heart Rate Variability Analysis ◽  
Nonlinear Features ◽  
Fetal Heart Rate Variability ◽  
Fetal Wellbeing

This paper presents an algorithm for classification of fetal health status using fetal heart rate variability (fHRV) analysis through phonocardiography. First, the fetal heart sound signals are acquired from the maternal abdominal surface using a specially developed Bluetooth-based wireless data recording system. Then, fetal heart rate (FHR) traces are derived from these signals. Ten numbers of linear and nonlinear features are extracted from each FHR trace. Finally, the multilayer perceptron (MLP) neural network is used to classify the health status of the fetus. Results show very promising performance toward the prediction of fetal wellbeing on the set of collected fetal heart sound signals. Finally, this work is likely to lead to an automatic screening device with additional potential of predicting fetal wellbeing.

scholarly journals POTENTIALS OF SHORT RECORDING OF HEART RATE VARIABILITY IN DISPLAYING SYSTEMIC INFORMATIONAL ENERGY PROCESSES OF THE HUMAN BODY DURING CLINICAL EXAMINATION OF PATIENTS WITH NON-COMMUNICABLE DISEASES

2020 ◽  
Vol 20 (4) ◽  
pp. 78-82
Author(s):  
G.V. Nevoit
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Clinical Examination ◽  
Human Body ◽  
Communicable Diseases ◽  
Functional Health ◽  
Non Communicable Diseases ◽  
Group 2 ◽  
Energy Processes

The article highlights the issues on the improvement of diagnosis and treatment of non-communicable diseases by applying the approaches of systemic medicine and the latest technologies. The aim of the study is to assess the clinical and diagnostic capabilities of a short recording of heart rate variability in displaying systemic informational energy processes of the human body. There has been a necessity to increase the effectiveness of measures for the prevention and treatment of non-communicable diseases in Ukraine through the early diagnosis and the introduction of the latest science-based technologies into medical practice and the development of a scientific concept of magnetoelectrochemical metabolism. An open-label, non-randomized controlled trial was performed. The study of the wave characteristics of the heart rate in functionally healthy respondents of different levels of physical fitness was one of its components. Main group 1 (n=171) and control group 2 (patients with non-communicable diseases and concomitant diseases, n=76) were examined by the method of short recording of heart rate variability using spectral analysis of wave parameters of the heart rate and variation heart rate monitoring. Clinically significant objective signs of changes in the functional state of the patients in group 2 in comparison with the individuals having good functional health status were identified. The significant difference between the indicators of the functional state in the subgroups of the individuals with good functional health has proven the significant clinical sensitivity of the method and the potentials of its applying as an objective tool for structured clinical examination of the health status, as well as for assessment of the therapeutic efficacy in the dynamics of managing patients with non-communicable diseases and determining their prognosis. The method of short recording of heart rate variability can be included into the procedure of objective structured clinical examination of patients with non-communicable diseases.

scholarly journals Model Construction of Using Physiological Signals to Detect Mental Health Status

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaoqian Liu
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Sliding Window ◽  
Physiological Signals ◽  
Health State ◽  
Detection Model ◽  
Physiological Signal ◽  
State Detection

Background. Mental health is a direct indicator of human mental activity, and it also affects all aspects of the human body. It plays a very important role in monitoring human mental health. Objectives. To design a mental health state detection model based on physiological signals to detect human mental health. Methods. For the detection of mental health, the sliding window method is used to divide the physiological signal dataset and the corresponding time into several segments and then calculate the physiological signal data in the sliding window for each physiological signal to form a sequence of characteristic values; according to the heart rate variability of the physiological signal, the heart rate variability (HRV) is extracted from the interval spectrum waveform: through the discrete trend analysis in statistics, the change characteristics of the ECG signal are analyzed, and the sequence statistical indicators of the physiological signal are calculated. With the help of a support vector machine used for the significant accuracy with less computation power, the physiological signals of the mental state are classified, and the discriminant function of the mental health state signals is normalized. A mental health state detection model is constructed according to the index system, the optimal solution of the model is obtained through the optimization function, and the mental health state detection is completed. Result. The detection error of the proposed model is less which improves the detection accuracy and is less time consuming. Conclusion. The detection model using physiological signals is proposed to evaluate the mental health status. As compared to the other detection models, its detection time is short and method error is always less than 2% which shows its accuracy and effectiveness.

Role of genetic and environmental influences on heart rate variability in middle-aged men

2007 ◽  
Vol 293 (2) ◽  
pp. H1013-H1022 ◽  
Author(s):  
A. L. T. Uusitalo ◽  
E. Vanninen ◽  
E. Levälahti ◽  
M. C. Battié ◽  
T. Videman ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Chronic Diseases ◽  
Leisure Time ◽  
Genetic Factors ◽  
Coffee Consumption ◽  
Genetic Effects ◽  
Healthy Male ◽  
Sport Activities

Our aim was to estimate causal relationships of genetic factors and different specific environmental factors in determination of the level of cardiac autonomic modulation, i.e., heart rate variability (HRV), in healthy male twins and male twins with chronic diseases. The subjects were 208 monozygotic (MZ, 104 healthy) and 296 dizygotic (DZ, 173 healthy) male twins. A structured interview was used to obtain data on lifetime exposures of occupational loading, regularly performed leisure-time sport activities, coffee consumption, smoking history, and chronic diseases from 12 yr of age through the present. A 5-min ECG at supine rest was recorded for the HRV analyses. In univariate statistical analyses based on genetic models with additive genetic, dominance genetic, and unique environmental effects, genetic effects accounted for 31–57% of HRV variance. In multivariate statistical analysis, body mass index, percent body fat, coffee consumption, smoking, medication, and chronic diseases were associated with different HRV variables, accounting for 1–11% of their variance. Occupational physical loading and leisure-time sport activities did not account for variation in any HRV variable. However, in the subgroup analysis of healthy and diseased twins, occupational loading explained 4% of the variability in heart periods. Otherwise, the interaction between health status and genetic effects was significant for only two HRV variables. In conclusion, genetic factors accounted for a major portion of the interindividual differences in HRV, with no remarkable effect of health status. No single behavioral determinant appeared to have a major influence on HRV. The effects of medication and diseases may mask the minimal effect of occupational loading on HRV.

scholarly journals Associations Between Heart Rate Variability Measured With a Wrist-Worn Sensor and Older Adults’ Physical Function: Observational Study (Preprint)

2019 ◽  
Author(s):  
Sarah Anne Graham ◽  
Dilip V Jeste ◽  
Ellen E Lee ◽  
Tsung-Chin Wu ◽  
Xin Tu ◽  
...  
Keyword(s):  
Older Adults ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Status ◽  
Physical Health ◽  
Physical Function ◽  
Significant Proportion ◽  
Physical Health Status ◽  
Sf 36 ◽  
Composite Scores

BACKGROUND Heart rate variability (HRV), or variation in beat-to-beat intervals of the heart, is a quantitative measure of autonomic regulation of the cardiovascular system. Low HRV derived from electrocardiogram (ECG) recordings is reported to be related to physical frailty in older adults. Recent advances in wearable technology offer opportunities to more easily integrate monitoring of HRV into regular clinical geriatric health assessments. However, signals obtained from ECG versus wearable photoplethysmography (PPG) devices are different, and a critical first step preceding their widespread use is to determine whether HRV metrics derived from PPG devices also relate to older adults’ physical function. OBJECTIVE This study aimed to investigate associations between HRV measured with a wrist-worn PPG device, the Empatica E4 sensor, and validated clinical measures of both objective and self-reported physical function in a cohort of older adults living independently within a continuing care senior housing community. Our primary hypothesis was that lower HRV would be associated with lower physical function. In addition, we expected that HRV would explain a significant proportion of variance in measures of physical health status. METHODS We evaluated 77 participants from an ongoing study of older adults aged between 65 and 95 years. The assessments encompassed a thorough examination of domains typically included in a geriatric health evaluation. We collected HRV data with the Empatica E4 device and examined bivariate correlations between HRV quantified with the triangular index (HRV TI) and 3 widely used and validated measures of physical functioning—the Short Physical Performance Battery (SPPB), Timed Up and Go (TUG), and Medical Outcomes Study Short Form 36 (SF-36) physical composite scores. We further investigated the additional predictive power of HRV TI on physical health status, as characterized by SF-36 physical composite scores and Cumulative Illness Rating Scale for Geriatrics (CIRS-G) scores, using generalized estimating equation regression analyses with backward elimination. RESULTS We observed significant associations of HRV TI with SPPB (n=52; Spearman ρ=0.41; <italic>P</italic>=.003), TUG (n=51; ρ=−0.40; <italic>P</italic>=.004), SF-36 physical composite scores (n=49; ρ=0.37; <italic>P</italic>=.009), and CIRS-G scores (n=52, ρ=−0.43; <italic>P</italic>=.001). In addition, the HRV TI explained a significant proportion of variance in SF-36 physical composite scores (R<sup>2</sup>=0.28 vs 0.11 without HRV) and CIRS-G scores (R<sup>2</sup>=0.33 vs 0.17 without HRV). CONCLUSIONS The HRV TI measured with a relatively novel wrist-worn PPG device was related to both objective (SPPB and TUG) and self-reported (SF-36 physical composite) measures of physical function. In addition, the HRV TI explained additional variance in self-reported physical function and cumulative illness severity beyond traditionally measured aspects of physical health. Future steps include longitudinal tracking of changes in both HRV and physical function, which will add important insights regarding the predictive value of HRV as a biomarker of physical health in older adults.

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