In this study,single-channel photoplethysmography(PPG)signals were used to estimate the heart rate(HR),diastolic blood pressure(DBP),and systolic blood pressure(SBP).A deep learning model was proposed using a long-ter...In this study,single-channel photoplethysmography(PPG)signals were used to estimate the heart rate(HR),diastolic blood pressure(DBP),and systolic blood pressure(SBP).A deep learning model was proposed using a long-term recurrent convolutional network(LRCN)modified from a deep learning algorithm,the convolutional neural network model of the modified inception deep learning module,and a long short-term memory network(LSTM)to improve the model’s accuracy of BP and HR measurements.The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository.How to design a filter of PPG signals and how to choose the loss functions for deep learning model were also discussed in the study.Finally,the stability of the proposed model was tested using a 10-fold cross-validation,with an MAE±SD of 2.942±5.076 mmHg for SBP,1.747±3.042 mmHg for DBP,and 1.137±2.463 bpm for the HR.Compared with its existing counterparts,the model entailed less computational load and was more accurate in estimating SBP,DBP,and HR.These results established the validity of the model.展开更多
This aim of the present study was to analyze the hemodynamic responses during resistance exercise performed at different intensities and with different recovery intervals. This study was conducted on twenty-four appar...This aim of the present study was to analyze the hemodynamic responses during resistance exercise performed at different intensities and with different recovery intervals. This study was conducted on twenty-four apparently healthy male individuals (25.50 ± 3.72 years and 76.50 ± 4.50 kg) experienced in strength training. The volunteers performed a 1RM test to determine the training load for the study. Blood pressure and Rate Pressure Product were measured before and at the end of the exercise training. The only significant difference observed was in SBP during strength training at 70% intensity (121.7 ± 8.68, p = 0.039), which was lower than SBP at the remaining intensities of 80% (126.3 ± 7.11) and 90% (127.1 ± 7.51). It was concluded that strength training performed at different intensities and recovery intervals did not significantly alter most variables, changing only the SBP due to the intensity employed.展开更多
Background Continuous blood pressure(BP)monitoring provides additional information about how changes in BP may correlate with daily activities and sleep patterns.Recommendations from the American Heart Association and...Background Continuous blood pressure(BP)monitoring provides additional information about how changes in BP may correlate with daily activities and sleep patterns.Recommendations from the American Heart Association and American College of Cardiology strongly suggest confirming a diagnosis of hypertension with continuous BP monitoring.Non-invasive and non-intrusive detection of haemodynamic parameters is emerging as a norm,based on self-monitoring wearable medical devices.Researchers have carried out several studies using non-invasive and continuous BP measurements as an alternative to conventional cuff-based measurements.In this work,we proposed a novel method for cuffless estimation of BP using impedance cardiography(ICG).Methods We conducted a single-centre,cross-sectional study of 104 subjects(of whom 30 were categorized as controls and the remaining 74 as the disease group)at the Medical College and Hospital,Kolkata.The disease group consisted of patients with confirmed coronary artery disease,while the individuals in the control group were deemed to be healthy.All subjects underwent electrocardiogram recording by on-duty doctors in order to determine their health status.A custom-made device based on the principle of impedance plethysmography was designed to record impedance changes due to subjects’peripheral blood flow.The device was used to record ICG signals.In this study,we developed a novel auto-adaptive algorithm based on ICG signals for non-invasive,cuffless,continuous monitoring of BP and heart rate.Separate mathematical models were developed for all the estimated parameters(BP and heart rate)for both the study groups(control and disease).The developed models were auto-adaptive and did not require subject-specific calibration.Performance indicators including,𝑟2,error percentage,standard deviation,and mean difference were used to quantify the performance of the models.Results The ICG signal recorded by the device was used to extract features and compute the augmentation index.The calculated augmentation index values showed strong correlations with systolic BP(𝑟=0.99,𝑃<0.05),diastolic BP(𝑟=0.95,𝑃<0.05),and heart rate(𝑟=0.78,𝑃<0.05).The models were also shown to have a high degree of accuracy for systolic and diastolic BP.Error margins were in the range±2.33 and±1.79 mmHg for systolic BP in disease and control subjects,respectively,and±3.60 and±1.82 mmHg for diastolic BP.However,the accuracy was lower in the prediction of heart rate in disease subjects,with a reported𝑟2 value of 0.72 and an error margin of±2.88 beats per min;for healthy subjects,the results were marginally better,with an error margin of±1.82 beats per min.All statistical analyses were performed using MATLAB(R2017a,MathWorks R○,USA).Conclusion In this study,we developed a non-invasive cuffless approach for estimation of systemic peripheral BP and heart rate using ICG.The proposed methodology eliminated any discomfort to patients caused by inflation of the cuff(in the case of cuff-based BP monitoring)or the need to constantly wear a fingertip photoplethysmography device(in the case of cuffless BP monitoring).The results obtained appeared promising and increased the potential scope of ICG for monitoring other haemodynamic parameters related to heart function.展开更多
The aim of this work was to study little active and sedentary women through physical assessments using anthropometric measurements and exercise testing using the Naughton and Bruce protocols. Approximately 53 women we...The aim of this work was to study little active and sedentary women through physical assessments using anthropometric measurements and exercise testing using the Naughton and Bruce protocols. Approximately 53 women were evaluated: Group 1—comprised of 17 completely sedentary women, aged 25-58 years, mean age 44.4 years, and Group 2—comprised of 36 women who answered doing physical activities once or twice a week (low active), aged 28-54 years, mean age 39.5 years. The results Group 1— high weight, body mass index showing overweight, heart rate above the target areas of your training, i.e., above 85% effort. Systolic blood pressure reached a high level in the seventh stage with 21 minutes of effort (177.3) and diastolic (92.7). Group 2—normal weight, body mass index recorded is considered thin, heart rate heart zones above the target of your training, i.e., above 85% effort also. Systolic blood pressure reached the highest level in phase 1 recovery (156.75). Diastolic blood pressure recorded pressure levels considered normal for the type of work done by the group. The values reported for the double product are considered normal for the type of effort made by both groups. Conclusion: The participants from group 1 are able to join physical activity programs from the results presented, specifically due to weight, BMI, heart rate and blood pressure. The participants from group 2 require more days of practice of physical activities and longer hours to improve the levels of heart rate and blood pressure.展开更多
基金This study was supported in part by the Ministry of Science and Technology MOST108-2221-E-150-022-MY3 and Taiwan Ocean University.
文摘In this study,single-channel photoplethysmography(PPG)signals were used to estimate the heart rate(HR),diastolic blood pressure(DBP),and systolic blood pressure(SBP).A deep learning model was proposed using a long-term recurrent convolutional network(LRCN)modified from a deep learning algorithm,the convolutional neural network model of the modified inception deep learning module,and a long short-term memory network(LSTM)to improve the model’s accuracy of BP and HR measurements.The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository.How to design a filter of PPG signals and how to choose the loss functions for deep learning model were also discussed in the study.Finally,the stability of the proposed model was tested using a 10-fold cross-validation,with an MAE±SD of 2.942±5.076 mmHg for SBP,1.747±3.042 mmHg for DBP,and 1.137±2.463 bpm for the HR.Compared with its existing counterparts,the model entailed less computational load and was more accurate in estimating SBP,DBP,and HR.These results established the validity of the model.
文摘This aim of the present study was to analyze the hemodynamic responses during resistance exercise performed at different intensities and with different recovery intervals. This study was conducted on twenty-four apparently healthy male individuals (25.50 ± 3.72 years and 76.50 ± 4.50 kg) experienced in strength training. The volunteers performed a 1RM test to determine the training load for the study. Blood pressure and Rate Pressure Product were measured before and at the end of the exercise training. The only significant difference observed was in SBP during strength training at 70% intensity (121.7 ± 8.68, p = 0.039), which was lower than SBP at the remaining intensities of 80% (126.3 ± 7.11) and 90% (127.1 ± 7.51). It was concluded that strength training performed at different intensities and recovery intervals did not significantly alter most variables, changing only the SBP due to the intensity employed.
基金This work was supported by the Ministry of Human Resource Devel-opment(MHRD),Department of Higher Education,New Delhi,India,F.NO.4-23/2014-TS.I,Dt.14-02-2014(Project code:LYA).
文摘Background Continuous blood pressure(BP)monitoring provides additional information about how changes in BP may correlate with daily activities and sleep patterns.Recommendations from the American Heart Association and American College of Cardiology strongly suggest confirming a diagnosis of hypertension with continuous BP monitoring.Non-invasive and non-intrusive detection of haemodynamic parameters is emerging as a norm,based on self-monitoring wearable medical devices.Researchers have carried out several studies using non-invasive and continuous BP measurements as an alternative to conventional cuff-based measurements.In this work,we proposed a novel method for cuffless estimation of BP using impedance cardiography(ICG).Methods We conducted a single-centre,cross-sectional study of 104 subjects(of whom 30 were categorized as controls and the remaining 74 as the disease group)at the Medical College and Hospital,Kolkata.The disease group consisted of patients with confirmed coronary artery disease,while the individuals in the control group were deemed to be healthy.All subjects underwent electrocardiogram recording by on-duty doctors in order to determine their health status.A custom-made device based on the principle of impedance plethysmography was designed to record impedance changes due to subjects’peripheral blood flow.The device was used to record ICG signals.In this study,we developed a novel auto-adaptive algorithm based on ICG signals for non-invasive,cuffless,continuous monitoring of BP and heart rate.Separate mathematical models were developed for all the estimated parameters(BP and heart rate)for both the study groups(control and disease).The developed models were auto-adaptive and did not require subject-specific calibration.Performance indicators including,𝑟2,error percentage,standard deviation,and mean difference were used to quantify the performance of the models.Results The ICG signal recorded by the device was used to extract features and compute the augmentation index.The calculated augmentation index values showed strong correlations with systolic BP(𝑟=0.99,𝑃<0.05),diastolic BP(𝑟=0.95,𝑃<0.05),and heart rate(𝑟=0.78,𝑃<0.05).The models were also shown to have a high degree of accuracy for systolic and diastolic BP.Error margins were in the range±2.33 and±1.79 mmHg for systolic BP in disease and control subjects,respectively,and±3.60 and±1.82 mmHg for diastolic BP.However,the accuracy was lower in the prediction of heart rate in disease subjects,with a reported𝑟2 value of 0.72 and an error margin of±2.88 beats per min;for healthy subjects,the results were marginally better,with an error margin of±1.82 beats per min.All statistical analyses were performed using MATLAB(R2017a,MathWorks R○,USA).Conclusion In this study,we developed a non-invasive cuffless approach for estimation of systemic peripheral BP and heart rate using ICG.The proposed methodology eliminated any discomfort to patients caused by inflation of the cuff(in the case of cuff-based BP monitoring)or the need to constantly wear a fingertip photoplethysmography device(in the case of cuffless BP monitoring).The results obtained appeared promising and increased the potential scope of ICG for monitoring other haemodynamic parameters related to heart function.
文摘The aim of this work was to study little active and sedentary women through physical assessments using anthropometric measurements and exercise testing using the Naughton and Bruce protocols. Approximately 53 women were evaluated: Group 1—comprised of 17 completely sedentary women, aged 25-58 years, mean age 44.4 years, and Group 2—comprised of 36 women who answered doing physical activities once or twice a week (low active), aged 28-54 years, mean age 39.5 years. The results Group 1— high weight, body mass index showing overweight, heart rate above the target areas of your training, i.e., above 85% effort. Systolic blood pressure reached a high level in the seventh stage with 21 minutes of effort (177.3) and diastolic (92.7). Group 2—normal weight, body mass index recorded is considered thin, heart rate heart zones above the target of your training, i.e., above 85% effort also. Systolic blood pressure reached the highest level in phase 1 recovery (156.75). Diastolic blood pressure recorded pressure levels considered normal for the type of work done by the group. The values reported for the double product are considered normal for the type of effort made by both groups. Conclusion: The participants from group 1 are able to join physical activity programs from the results presented, specifically due to weight, BMI, heart rate and blood pressure. The participants from group 2 require more days of practice of physical activities and longer hours to improve the levels of heart rate and blood pressure.
文摘目的 探讨自主呼吸训练影响稳定型冠心病心率变异性和心率-压力乘积的护理康复效果。方法 选取120例稳定型冠心病患者平均分为观察组和对照组2组,每组60例。对照组患者给予常规健康宣教,观察组患者则在常规健康宣教的基础上给予自主呼吸训练。分析2组患者康复训练前后心率变异性[1 d正常RR标准差异(SDNN)、1 d内5 min时段RR间期均值标准差(SDANN)、连续RR间期差值均方根(RMSSD)和相邻正常RR间期差值>50 ms百分比(PNN50)]和心率-压力乘积的差异,同时记录康复训练后患者的动态血压参数[24 h平均收缩压(24 h SBP)、24 h平均舒张压(24 h DBP)、白昼平均收缩压(dSBP)、白昼平均舒张压(dDBP)、夜间平均收缩压(nSBP)、夜间平均舒张压(n DBP)]和血脂指标[总胆固醇(TC)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)],并统计患者不良反应发生率。结果 康复训练后,与对照组患者相比,观察组患者的24 h SBP、24 h DBP、dSBP、dDBP、nSBP、nDBP、TC、TG和LDL-C均减小,HDL-C则较大,差异均有统计学意义(P<0.05)。康复训练前2组患者的心率变异性和心率-压力乘积差异无统计学意义(P>0.05),在康复训练后观察组患者的SDNN、SDANN、RMSSD和PNN50显著高于对照组,平均心率、平均血压和平均心率血压乘积则显著低于对照组(P<0.05)。观察组患者不良反应发生率低于对照组(P<0.05)。结论 自主呼吸训练对稳定型冠心病患者的心率变异性和心率-压力乘积的护理康复效果显著,具有良好的有效性及安全性,值得临床推广。
