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single-lead electrocardiography  (ADInstruments)


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    ADInstruments single-lead electrocardiography
    Single Lead Electrocardiography, supplied by ADInstruments, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/single+lead+electrocardiography/single+lead+electrocardiography/pm40490291-72-10-12
    Average 90 stars, based on 1 article reviews
    single-lead electrocardiography - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    other:

    Article Title: Blood pressure oscillations impact signal-averaged sympathetic transduction of blood pressure: implications for the association with resting sympathetic outflow.
    Article Snippet: Signal-averaged sympathetic transduction of blood pressure (BP) is inversely related to resting muscle sympathetic nerve activity (MSNA) burst frequency in healthy cohorts.. Whether this represents a physiological compensatory adaptation or a methodological limitation, remains unclear.. The current analysis aimed to determine the contribution of methodological limitations by evaluating the dependency of MSNA transduction at different levels of absolute BP.

    Article Title: Water drinking enhances the gain of arterial baroreflex control of muscle sympathetic nerve activity in healthy young humans
    Article Snippet: Arterial blood pressure and heart rate were measured on a continuous beat-to-beat basis using finger photoplethysmography (Finometer Pro; Finapres Medical Systems, Arnhem, The Netherlands) and a single lead electrocardiography (PowerLab 4/25T and Laboratory Chart Pro 7 software, AD Instruments, Castle Hill, NSW, Australia), respectively.

    Article Title: Potentiation of GABAergic synaptic transmission by diazepam acutely increases resting beat-to-beat blood pressure variability in young adults.
    Article Snippet: Heart rate was measured with a single lead electrocardiography (CardioMatic, MSC-6111, New York or PowerLab 4/25 T and Lab Chart pro 7 software; AD Instruments, Australia).

    Article Title: Three Weeks of Overload Training Increases Resting Muscle Sympathetic Activity
    Article Snippet: COATES, A. M., A. V. INCOGNITO, J. D. SEED, C. J. DOHERTY, P. J. MILLAR, and J. F. BURR.. Three Weeks of Overload Training Increases Resting Muscle Sympathetic Activity.Med.. Sci.



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    Image Search Results


    A Representation depicting the overall agreement between rPPG and ECG, where the difference of between rPPG and ECG is plotted on the y-axis, and the mean heart rate is plotted on the x-axis. Each data point represents a 60-s interval. Bias is indicated by the black lines and limits of agreement are indicated by the dotted lines. B A scatterplot illustrating the relationship between heart rates measured by ECG (x-axis) and rPPG (y-axis). Each data point represents a 60-s interval. Points closely aligned with the diagonal line indicate strong agreement between the two measurement methods, while deviations from this line reflect discrepancies between rPPG and ECG readings

    Journal: Journal of Clinical Monitoring and Computing

    Article Title: Accuracy of remote, video-based supraventricular tachycardia detection in patients undergoing elective electrical cardioversion: a prospective cohort

    doi: 10.1007/s10877-025-01263-5

    Figure Lengend Snippet: A Representation depicting the overall agreement between rPPG and ECG, where the difference of between rPPG and ECG is plotted on the y-axis, and the mean heart rate is plotted on the x-axis. Each data point represents a 60-s interval. Bias is indicated by the black lines and limits of agreement are indicated by the dotted lines. B A scatterplot illustrating the relationship between heart rates measured by ECG (x-axis) and rPPG (y-axis). Each data point represents a 60-s interval. Points closely aligned with the diagonal line indicate strong agreement between the two measurement methods, while deviations from this line reflect discrepancies between rPPG and ECG readings

    Article Snippet: Heart rate was derived from single-lead ECG (IntelliVue MP70 patient monitor (Philips, Eindhoven, the Netherlands), 500 Hz) with Intellivue Datalogger software.

    Techniques:

    A , C Representation depicting the agreement between rPPG and ECG, where the difference of between rPPG and ECG is plotted on the y-axis, and the mean heart rate is plotted on the x-axis. Each data point represents a 60-s interval. Bias is indicated by the black lines and limits of agreement are indicated by the dotted lines. In figure C , the mean and limits of agreement are provided as a reference, but it should be noted that these values may not be entirely reliable due to the presence of heteroscedasticity. B , D Scatterplots illustrating the relationship between heart rates measured by ECG (x-axis) and rPPG (y-axis). Each data point represents a 60-s interval. Points closely aligned with the diagonal line indicate strong agreement between the two measurement methods, while deviations from this line reflect discrepancies between rPPG and ECG readings

    Journal: Journal of Clinical Monitoring and Computing

    Article Title: Accuracy of remote, video-based supraventricular tachycardia detection in patients undergoing elective electrical cardioversion: a prospective cohort

    doi: 10.1007/s10877-025-01263-5

    Figure Lengend Snippet: A , C Representation depicting the agreement between rPPG and ECG, where the difference of between rPPG and ECG is plotted on the y-axis, and the mean heart rate is plotted on the x-axis. Each data point represents a 60-s interval. Bias is indicated by the black lines and limits of agreement are indicated by the dotted lines. In figure C , the mean and limits of agreement are provided as a reference, but it should be noted that these values may not be entirely reliable due to the presence of heteroscedasticity. B , D Scatterplots illustrating the relationship between heart rates measured by ECG (x-axis) and rPPG (y-axis). Each data point represents a 60-s interval. Points closely aligned with the diagonal line indicate strong agreement between the two measurement methods, while deviations from this line reflect discrepancies between rPPG and ECG readings

    Article Snippet: Heart rate was derived from single-lead ECG (IntelliVue MP70 patient monitor (Philips, Eindhoven, the Netherlands), 500 Hz) with Intellivue Datalogger software.

    Techniques:

    Respiratory rate (RR) estimation in spontaneously breathing humans. ( A ) RR estimates, in breaths per minute (bpm), during 3 levels of exercise in one subject. Algorithm-estimated RRs (estimated, blue) are compared with RR measured from the subject using the respiratory inductive plethysmography based Hexoskin monitor (expected, red) while performing three consecutive tasks: (1) resting, standing upright on a treadmill (Int 1); (2) walking on the treadmill at a moderate speed (1.2 m/s) (int 2); and (3) walking on the treadmill with 15% track inclination at the moderate speed (Int 3). ( B ) Summary results of algorithm-estimated and reference RRs (blue and red, respectively) during each subject-task interval. The data are from seven subjects, each performing either or all the three levels of exercise described above (subject-tasks), and presented in order of increasing average expected RR values. ( C ) The absolute errors (black) and relative errors (gray) of the algorithmic RR estimations across the subject-task intervals described above. Equivalence testing revealed that the expected and estimated RRs were the same ( p < 0.0001) for all subject-task intervals. ( D ) A comparison of the ECG cycle-to-cycle estimated and expected RR for all subjects and tasks with the indicated R 2 value (0.9092) and low root mean square error (RMSE, 2.2bpm) support a close linear relationship between the values. ( E ) Absolute error (bpm) and ( F ) relative error (%) distributions across all subjects.

    Journal: Scientific Reports

    Article Title: Open-source software for respiratory rate estimation using single-lead electrocardiograms

    doi: 10.1038/s41598-023-50470-0

    Figure Lengend Snippet: Respiratory rate (RR) estimation in spontaneously breathing humans. ( A ) RR estimates, in breaths per minute (bpm), during 3 levels of exercise in one subject. Algorithm-estimated RRs (estimated, blue) are compared with RR measured from the subject using the respiratory inductive plethysmography based Hexoskin monitor (expected, red) while performing three consecutive tasks: (1) resting, standing upright on a treadmill (Int 1); (2) walking on the treadmill at a moderate speed (1.2 m/s) (int 2); and (3) walking on the treadmill with 15% track inclination at the moderate speed (Int 3). ( B ) Summary results of algorithm-estimated and reference RRs (blue and red, respectively) during each subject-task interval. The data are from seven subjects, each performing either or all the three levels of exercise described above (subject-tasks), and presented in order of increasing average expected RR values. ( C ) The absolute errors (black) and relative errors (gray) of the algorithmic RR estimations across the subject-task intervals described above. Equivalence testing revealed that the expected and estimated RRs were the same ( p < 0.0001) for all subject-task intervals. ( D ) A comparison of the ECG cycle-to-cycle estimated and expected RR for all subjects and tasks with the indicated R 2 value (0.9092) and low root mean square error (RMSE, 2.2bpm) support a close linear relationship between the values. ( E ) Absolute error (bpm) and ( F ) relative error (%) distributions across all subjects.

    Article Snippet: Single-lead body surface ECG signals were obtained during the procedure and 90 min after coil placement using the AD Instruments PowerLab 4/35 system with Labchart 8 software.

    Techniques: Comparison

    Block diagram of respiration rate estimation algorithm. Raw single-lead ECG data are filtered (panels a and b ), R-peaks are detected (red symbols, panel c ), R-peak intervals are determined, QRS complexes are extracted (panel d ) and their root mean square amplitude (RMS) values are calculated (panel e ), a power spectrum is generated for a moving window of 16 QRS RMS values incremented one value at a time (panel f ), and its peak frequency and the R-peak interval data within the window are used to calculate the respiratory rate (RR) using the equation shown.

    Journal: Scientific Reports

    Article Title: Open-source software for respiratory rate estimation using single-lead electrocardiograms

    doi: 10.1038/s41598-023-50470-0

    Figure Lengend Snippet: Block diagram of respiration rate estimation algorithm. Raw single-lead ECG data are filtered (panels a and b ), R-peaks are detected (red symbols, panel c ), R-peak intervals are determined, QRS complexes are extracted (panel d ) and their root mean square amplitude (RMS) values are calculated (panel e ), a power spectrum is generated for a moving window of 16 QRS RMS values incremented one value at a time (panel f ), and its peak frequency and the R-peak interval data within the window are used to calculate the respiratory rate (RR) using the equation shown.

    Article Snippet: Single-lead body surface ECG signals were obtained during the procedure and 90 min after coil placement using the AD Instruments PowerLab 4/35 system with Labchart 8 software.

    Techniques: Blocking Assay, Generated