single-lead electrocardiography  (ADInstruments)

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:

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:

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

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