scholarly journals Wristbands in Home-Based Rehabilitation—Validation of Heart Rate Measurement

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 60
Author(s):  
Magdalena Jachymek ◽  
Michał T. Jachymek ◽  
Radosław M. Kiedrowicz ◽  
Jarosław Kaźmierczak ◽  
Edyta Płońska-Gościniak ◽  
...  
Keyword(s):  
Heart Rate ◽  
Stress Test ◽  
Absolute Error ◽  
Concordance Correlation ◽  
Heart Rates ◽  
Home Based ◽  
Accuracy And Precision ◽  
Validation Criteria ◽  
Precision And Accuracy ◽  
Electrocardiogram Ecg

The possibility of using a smartwatch as a rehabilitation tool to monitor patients’ heart rates during exercise has gained the attention of many researchers. This study aimed to evaluate the accuracy and precision of the HR measurement performed by two wrist monitors: the Fitbit Charge 4 and the Xiaomi Mi Band 5. Thirty-one healthy volunteers were asked to perform a stress test on a treadmill. Their heart rates were recorded simultaneously by the wristbands and an electrocardiogram (ECG) at 1 min intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC), and Bland–Altman analysis were calculated to compare the precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < 0.8. The overall MAPE and LCCC of the Fitbit were 10.19% (±11.79%) and 0.753 (95% CI: 0.717–0.785), respectively. The MAPE and LCCC of the Xiaomi were 6.89% (±9.75) and 0.903 (0.886–0.917), respectively. The precision and accuracy of both devices decreased with the increased exercise intensity. The accuracy of wearable wrist-worn heart rate monitors varies and depends on the intensity of training. Therefore, the decision to use such a device as a heart rate monitor during in-home rehabilitation should be made with caution.

Validation of heart rate measurement of Fitbit Charge 4 and Xiaomi Mi Band 5 (Preprint)

2021 ◽  
Author(s):  
Magdalena Jachymek ◽  
Michał Tomasz Jachymek ◽  
Radosław Marek Kiedrowicz ◽  
Jarosław Kaźmierczak ◽  
Małgorzata Peregud-Pogorzelska
Keyword(s):  
Heart Rate ◽  
Stress Test ◽  
Absolute Error ◽  
Sensor Technology ◽  
Concordance Correlation ◽  
Accuracy And Precision ◽  
Validation Criteria ◽  
Precision And Accuracy ◽  
Fitness Trackers ◽  
Error Percentage

BACKGROUND Recent advances in mobile sensor technology have led to increased popularity of wrist-worn fitness trackers. The possibility to use a smartwatch as a rehabilitation tool to monitor patients’ heart rate during exercise has won the attention of many researchers. OBJECTIVE The aim of the study was to evaluate the accuracy and precision of HR measurement performed by two wrist monitors: Fitbit Charge 4 (Fitbit) and Xiaomi Mi Band 5 (Xiaomi). METHODS 31 healthy volunteers were asked to perform a stress test on a treadmill. During the test their heart rate was recorded simultaneously by both wristbands and ECG at 1minute intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC) and Bland-Altman were calculated to compare precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < .8 RESULTS The overall MAPE of the Fitbit device was 10.19% (±11.79%) and the MAPE of Xiaomi was (6.89 % ± 9.75). LCCC of Fitbit HR measurements was .753 (95% CI:0.717-0.785) and of Xiaomi – .903 (0.886-0.917). In both devices the precision and accuracy were decreasing with the increasing exercise intensity. Age, sex, height, weight, BMI did not influence the accuracy of both devices. CONCLUSIONS The accuracy of a wearable wrist-worn heart rate monitor varies and depends on the intensity of training. The decision concerning the application of such a device as a monitor during in-home rehabilitation should be taken with caution, as it may prove not reliable enough.

scholarly journals How well are heart rates measured by pulse oximeters and electronic sphygmomanometers? Practice-based evidence from an observational study of acutely ill medical patients during hospital admission

2019 ◽  
Vol 18 (3) ◽  
pp. 144-147
Author(s):  
Mary Rimbi ◽  
◽  
Immaculate Nakitende ◽  
Teopista Namujwiga ◽  
John Kellett ◽  
...  
Keyword(s):  
Heart Rate ◽  
Observational Study ◽  
Hospital Admission ◽  
Pulse Oximeter ◽  
Medical Patients ◽  
Limits Of Agreement ◽  
Heart Rates ◽  
Electrocardiogram Ecg ◽  
Pulse Oximeters

Background: heart rates generated by pulse oximeters and electronic sphygmomanometers in acutely ill patients may not be the same as those recorded by ECG Methods: heart rates recorded by an oximeter and an electronic sphygmomanometer were compared with electrocardiogram (ECG) heart rates measured on acutely ill medical patients. Results: 1010 ECGs were performed on 217 patients while they were in the hospital. The bias between the oximeter and the ECG measured heart rate was -1.37 beats per minute (limits of agreement -22.6 to 19.9 beats per minute), and the bias between the sphygmomanometer and the ECG measured heart rate was -0.14 beats per minute (limits of agreement -22.2 to 21.9 beats per minute). Both devices failed to identify more than half the ECG recordings that awarded 3 NEWS points for heart rate. Conclusion: Heart rates of acutely ill patients are not reliably measured by pulse oximeter or electronic sphygmomanometers.

scholarly journals Camera-based heart rate estimation for hospitalized newborns in the presence of motion artifacts

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Qiong Chen ◽  
Yalin Wang ◽  
Xiangyu Liu ◽  
Xi Long ◽  
Bin Yin ◽  
...  
Keyword(s):  
Heart Rate ◽  
Body Movement ◽  
Region Of Interest ◽  
Ground Truth ◽  
Absolute Error ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Majority Voting ◽  
Thermal Cameras ◽  
Electrocardiogram Ecg

Abstract Background Heart rate (HR) is an important vital sign for evaluating the physiological condition of a newborn infant. Recently, for measuring HR, novel RGB camera-based non-contact techniques have demonstrated their specific superiority compared with other techniques, such as dopplers and thermal cameras. However, they still suffered poor robustness in infants’ HR measurements due to frequent body movement. Methods This paper introduces a framework to improve the robustness of infants’ HR measurements by solving motion artifact problems. Our solution is based on the following steps: morphology-based filtering, region-of-interest (ROI) dividing, Eulerian video magnification and majority voting. In particular, ROI dividing improves ROI information utilization. The majority voting scheme improves the statistical robustness by choosing the HR with the highest probability. Additionally, we determined the dividing parameter that leads to the most accurate HR measurements. In order to examine the performance of the proposed method, we collected 4 hours of videos and recorded the corresponding electrocardiogram (ECG) of 9 hospitalized neonates under two different conditions—rest still and visible movements. Results Experimental results indicate a promising performance: the mean absolute error during rest still and visible movements are 3.39 beats per minute (BPM) and 4.34 BPM, respectively, which improves at least 2.00 and 1.88 BPM compared with previous works. The Bland-Altman plots also show the remarkable consistency of our results and the HR derived from the ground-truth ECG. Conclusions To the best of our knowledge, this is the first study aimed at improving the robustness of neonatal HR measurement under motion artifacts using an RGB camera. The preliminary results have shown the promising prospects of the proposed method, which hopefully reduce neonatal mortality in hospitals.

Method for measurement of heart rate in awake, noninstrumented small mammals

1984 ◽  
Vol 247 (6) ◽  
pp. H1010-H1012
Author(s):  
F. Vetterlein ◽  
J. Sammler ◽  
H. dal Ri ◽  
G. Schmidt
Keyword(s):  
Heart Rate ◽  
Small Mammals ◽  
Small Animals ◽  
Heart Rates ◽  
Metal Plates ◽  
Electrocardiogram Ecg

A method is described that enables the researcher to determine the heart rate in awake, noninstrumented small animals by recording the electrocardiogram (ECG) via the paws. Single animals are placed in a cage that has metal plates built into its floor. Through switches any two plates can be connected with an ECG recorder whenever contact with at least one front and one hind paw is made. The heart rate is then determined by measuring the number of R waves per unit of time. In rats of 140 and 300 g body wt mean resting heart rates of 384 +/- 10 and 320 +/- 4 beats/min, respectively, have been measured with this method.

scholarly journals TRIMETAZIDINE MR EFFECTS ON THE PARAMETERS OF 24-HOUR ELECTROCARDIOGRAM MONITORING AND HEART RATE VARIABILITY

2013 ◽  
Vol 12 (5) ◽  
pp. 68-74
Author(s):  
M. V. Novikova ◽  
M. G. Glezer
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Stress Test ◽  
Ecg Monitoring ◽  
Randomised Study ◽  
St Segment ◽  
Number Of Patients ◽  
Stable Coronary Heart Disease ◽  
Electrocardiogram Monitoring ◽  
Electrocardiogram Ecg

Aim. To assess the effects of the four-month trimetazidine MR therapy on the parameters of 24-hour electrocardiogram (ECG) monitoring and heart rate variability (HRV) in patients with stable coronary heart disease (CHD).Material and methods. This prospective, non-randomised study, with the inclusion of 66 consecutive patients who had stable CHD and stable stress test results, investigated the effects of trimetazidine MR therapy on the parameters of 24-hour ECG monitoring and HRV.Results. Trimetazidine MR did not markedly affect the 24-hour, daytime, or nighttime levels of heart rate. Trimetazidine MR therapy was not associated with any substantial changes in frequency and time-domain HRV parameters or in the incidence of cardiac arrhythmias. However, there was a significant reduction in the number of patients with ST segment depression (from 66,7% to 43,8%; p<0,001) and in the duration of ischemic episodes (from 10 (6,2;21) minutes to 7,42 (5;12,3) minutes (p=0,025)).Conclusion. Adding trimetazidine MR to the treatment of patients with stable CHD provides an additional beneficial antiischemic effect.

A PHONOCARDIOGRAM-BASED NOISE-ROBUST REAL-TIME HEART RATE MONITORING ALGORITHM FOR OUTPATIENTS DURING NORMAL ACTIVITIES

2018 ◽  
Vol 18 (05) ◽  
pp. 1850044 ◽  
Author(s):  
KYOUNG WON NAM ◽  
JI MIN AHN ◽  
YOUNG JUN HWANG ◽  
GYE ROK JEON ◽  
DONG PYO JANG ◽  
...  
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Absolute Error ◽  
Electronic Stethoscope ◽  
Ecg Signals ◽  
Error Formula ◽  
Noise Robust ◽  
Electrocardiogram Ecg ◽  
Pcg Signals ◽  
Monitoring Algorithm

For outpatients who need continuous monitoring of heart rate (HR) variation, it is important that HR can be monitored during normal activities such as speaking and walking. In this study, a noise-robust real-time HR monitoring algorithm based on phonocardiogram (PCG) signals is proposed. PCG signals were recorded using an electronic stethoscope; electrocardiogram (ECG) signals were recorded simultaneously with HR references. The proposed algorithm consisted of pre-processing, peak/nonpeak classification, voice noise processing, walking noise processing, and HR calculation. The performance of the algorithm was evaluated using PCG/ECG signals from 11 healthy participants. For comparison, the absolute errors between manually extracted ECG-based HR values and automatically calculated PCG-based HR values were calculated for the proposed algorithm and the comparison algorithm in two different test protocols. Experimental results showed that the average absolute errors of the proposed algorithm were 72.03%, 22.92%, and 36.39% of the values of the comparison algorithm for resting-state, speaking-state, and walking-state data, respectively, in protocol-1. In protocol-2, the average absolute error was 36.99% of that of the comparison algorithm. A total of 1102 cases in protocol-1 and 783 in protocol-2 had an absolute error [Formula: see text] beats per minute (BPM) using the comparison algorithm and an absolute error [Formula: see text] BPM using the proposed algorithm. On the basis of these results, we anticipate that the proposed algorithm can potentially improve the performance of continuous real-time HR monitoring during activities of normal life, thereby improving the safety of outpatients with cardiovascular diseases.

scholarly journals Standard Area Diagram Set for Scab Evaluation in Fruits of sour Passion Fruit

2019 ◽  
Vol 11 (14) ◽  
pp. 298 ◽  
Author(s):  
Anne Pinheiro Costa ◽  
José Ricardo Peixoto ◽  
Luiz Eduardo Bassay Blum ◽  
Márcio de Carvalho Pires
Keyword(s):  
Absolute Error ◽  
Passion Fruit ◽  
Coefficient Of Determination ◽  
Concordance Correlation Coefficient ◽  
Simple Linear Regression ◽  
Concordance Correlation ◽  
Passiflora Edulis ◽  
Accuracy And Precision ◽  
Variation Range ◽  
Sour Passion Fruit

Scab (Cladosporium spp.) significantly comprises the commercial acceptance of sour passion fruit (Passiflora edulis) because of the deformed and atrophied fruit appearance resulting from the development of the lesions. Therefore, the objective of this study was to elaborate and validate a standard area diagram set (SADs) for the severity evaluation of scab in fruits of sour passion fruit. The SADs comprised eight severity levels (0.6; 1; 2; 4; 8; 16; 37; and 46%) and was validated by 20 raters (G1 and G3, inexperienced; G2 and G4, experienced). Initially, all raters performed a non-aided SADs evaluation of the scab severity. Afterward, G1 and G2 completed the second evaluation without the proposed SADs, whereas G3 and G4 performed a SADs-aided assessment of the disease severity. The accuracy and precision of the evaluations were determined by simple linear regression and by the Lin&rsquo;s concordance correlation coefficient. Constant and systematic errors decreased with the use of the SADs, demonstrating an approximation between the estimated and the actual values. Precision increased with an increase in the coefficient of determination. Also, the absolute error reduced by 66% (G3) and 47% (G4). Therefore, 94.4% (G3) and 98.8% (G4) of the estimates had up to &plusmn;10% of errors, which corresponds to a 20.4% (G3) and 5.6% (G4) increment in the estimates with errors within this variation range. As a result, accuracy and precision were higher in the SADs-aided groups. Inexperienced raters were the most benefited by the use of the SADs. The accuracy and precision of the non-aided groups had a slight or no increase when compared with the SADs-aided groups.

scholarly journals Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elisa Mejía-Mejía ◽  
James M. May ◽  
Mohamed Elgendi ◽  
Panayiotis A. Kyriacou
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Pulse Transit Time ◽  
Pulse Rate Variability ◽  
Physiological Factors ◽  
Ecg Signals ◽  
Non Invasive ◽  
Electrocardiogram Ecg

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

scholarly journals A Review of Deep Learning-Based Contactless Heart Rate Measurement Methods

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3719
Author(s):  
Aoxin Ni ◽  
Arian Azarang ◽  
Nasser Kehtarnavaz
Keyword(s):  
Heart Rate ◽  
Deep Learning ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Video Camera ◽  
Measurement Methods ◽  
Rate Measurement ◽  
Learning Methods ◽  
The Public ◽  
Heart Rate Measurement

The interest in contactless or remote heart rate measurement has been steadily growing in healthcare and sports applications. Contactless methods involve the utilization of a video camera and image processing algorithms. Recently, deep learning methods have been used to improve the performance of conventional contactless methods for heart rate measurement. After providing a review of the related literature, a comparison of the deep learning methods whose codes are publicly available is conducted in this paper. The public domain UBFC dataset is used to compare the performance of these deep learning methods for heart rate measurement. The results obtained show that the deep learning method PhysNet generates the best heart rate measurement outcome among these methods, with a mean absolute error value of 2.57 beats per minute and a mean square error value of 7.56 beats per minute.

A new modification of the homotopy perturbation method

2021 ◽  
pp. 095745652199987
Author(s):  
Magaji Yunbunga Adamu ◽  
Peter Ogenyi
Keyword(s):  
Comparative Analysis ◽  
Error Analysis ◽  
Perturbation Method ◽  
Homotopy Perturbation Method ◽  
Nonlinear Oscillators ◽  
Absolute Error ◽  
New Method ◽  
Optimal Analysis ◽  
Homotopy Perturbation ◽  
Accuracy And Precision

This study proposes a new modification of the homotopy perturbation method. A new parameter alpha is introduced into the homotopy equation in order to improve the results and accuracy. An optimal analysis identifies the parameter alpha, aimed at improving the solutions. A comparative analysis of the proposed method reveals that the new method presents results with higher degree of accuracy and precision than the classic homotopy perturbation method. Absolute error analysis shows the convenience of the proposed method, providing much smaller errors. Two examples are presented: Duffing and Van der pol’s nonlinear oscillators to demonstrate the efficiency, accuracy, and applicability of the new method.

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