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Boston Scientific Corporation surface 12 lead ecg p waves
Surface 12 Lead Ecg P Waves, supplied by Boston Scientific Corporation, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/lead+surface+ecg/clinical+devices+ecg+grade+lead+single/pm39880539-50-0-23
Average 86 stars, based on 1 article reviews
surface 12 lead ecg p waves - by Bioz Stars, 2026-09
86/100 stars

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Article Title: Percutaneous left atrial appendage closure with concomitant dual-device implantation: a single-center observational study
Article Snippet: In the single-device group, two types of LAAC devices were used: single-closure system devices (Watchman or Watchman FLX, Boston Scientific, MA, USA) and pacifier-principle plug-and-disc devices [Amplatzer Cardiac Plug (ACP) or Amulet, St. Jude Medical/Abbott, IL, USA].

Article Title: Delta (Δ) 12-lead electrocardiography and vectorcardiography to identify the origin of focally induced atrial and ventricular premature depolarizations in horses.
Article Snippet: A 12-lead ECG (Labsystem Pro v2.6, Boston Scientific, Diegem, Belgium) was continuously recorded throughout the procedure.

Article Title: Left Bundle Branch Area Pacing with a Defibrillator Lead in a Patient with Recurrent Ventricular Tachycardia and Severe Nonischemic Cardiomyopathy: A Case Report
Article Snippet: We report, to the best of our knowledge, the first documented case of successful LBBAP using a single-coil defibrillator lead (Reliance 4-Front; Boston Scientific, Marlborough, MA, USA) positioned with a manually shaped stylet.

Article Title: Revision of an Eight-lead Boston Scientific® Spinal Cord Stimulator With Epidural Migration: A Case Report
Article Snippet: The patient underwent an uneventful placement of a left-sided single 16-point lead (Boston Scientific Corporation, Marlborough, Massachusetts, United States) covering the T10-T12 vertebral bodies (Figure ).

Article Title: Delta (Δ) 12-lead electrocardiography and vectorcardiography to identify the origin of focally induced atrial and ventricular premature depolarizations in horses
Article Snippet: A Δ 12-lead ECG (Labsystem Pro v2.6, Boston Scientific, Diegem, Belgium) was continuously recorded throughout the procedure.

Magnetic Resonance Imaging:

Article Title: Presumed convulsive syncopes during ventricular arrest due to pacemaker malfunction in a dog.
Article Snippet: Syncope and epileptic seizure (ES) account for the most common causes of transient loss of consciousness (TLOC), among other differentials like narcolepsy, anaemia, acid–base and electrolyte derangements, or intoxications (Blanc, 2015; Martin, 2024; Rodrigues et al., 2010).. The most common presentation of syncope is a short episode of unconsciousness and flaccid loss of postural tone without convulsion, pale mucous membranes and complete, rapid recovery (Blanc, 2015; Martin, 2024; Rodrigues et al., 2010).. Most generalised ES present with TLOC, autonomic signs (e.g. hypersalivation, defaecation and urination) and convulsion, characterised by abnormal muscle contractions, usually bilateral (Fisher et al., 2005).



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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 <t>ECG</t> 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.
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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