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12-lead surface ecg  (Nihon Kohden corporation)

 
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    Structured Review

    Nihon Kohden corporation 12-lead surface ecg
    An <t>ECG</t> example demonstrating the measurement of the frontal QRS-T angle. The QRS axis and T axis were calculated automatically (arrowheads). Then, the frontal QRSTa was calculated as the absolute value of the difference between the frontal plane QRS and T axes (frontal QRS-T angle=|QRS axis−T axis|). For the ECG of the patient demonstrating above, frontal QRS-T angle=|46° (QRS axis)−44° (T axis)|=2° ECG - <t>electrocardiography</t>
    12 Lead Surface Ecg, supplied by Nihon Kohden corporation, 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/lead+surface+ecg/12+lead+surface+ecg/pmc06955084-95-1-8
    Average 90 stars, based on 1 article reviews
    12-lead surface ecg - by Bioz Stars, 2026-10
    90/100 stars

    Images

    1) Product Images from "Frontal QRS-T angle is related with hemodynamic significance of coronary artery stenosis in patients with single vessel disease"

    Article Title: Frontal QRS-T angle is related with hemodynamic significance of coronary artery stenosis in patients with single vessel disease

    Journal: Anatolian Journal of Cardiology

    doi: 10.14744/AnatolJCardiol.2019.99692

    An ECG example demonstrating the measurement of the frontal QRS-T angle. The QRS axis and T axis were calculated automatically (arrowheads). Then, the frontal QRSTa was calculated as the absolute value of the difference between the frontal plane QRS and T axes (frontal QRS-T angle=|QRS axis−T axis|). For the ECG of the patient demonstrating above, frontal QRS-T angle=|46° (QRS axis)−44° (T axis)|=2° ECG - electrocardiography
    Figure Legend Snippet: An ECG example demonstrating the measurement of the frontal QRS-T angle. The QRS axis and T axis were calculated automatically (arrowheads). Then, the frontal QRSTa was calculated as the absolute value of the difference between the frontal plane QRS and T axes (frontal QRS-T angle=|QRS axis−T axis|). For the ECG of the patient demonstrating above, frontal QRS-T angle=|46° (QRS axis)−44° (T axis)|=2° ECG - electrocardiography

    Techniques Used:

    Electrocardiographic parameters of patients with normal and low FFR
    Figure Legend Snippet: Electrocardiographic parameters of patients with normal and low FFR

    Techniques Used:

    Related Articles

    Control:

    Article Title: Frontal QRS-T angle is related with hemodynamic significance of coronary artery stenosis in patients with single vessel disease
    Article Snippet: A 12-lead surface ECG (Cardiofax M Model ECG-1250; Nihon Kohden Corporation, Tokyo, Japan) that had been performed in the supine position, with a 25 mm/s paper speed and a voltage of 10 mm/s, before performing coronary angiography, was evaluated retrospectively.



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    Image Search Results


    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