single lead body surface ecg signals (ADInstruments)
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single lead body surface ecg signals
Single Lead Body Surface Ecg Signals, supplied by ADInstruments, used in various techniques. Bioz Stars score: 99/100, based on 8090 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/lead+surface+ecg/PowerLab/pmc10762020-207-0-18
Average 99 stars, based on 8090 article reviews
Single Lead Body Surface Ecg Signals, supplied by ADInstruments, used in various techniques. Bioz Stars score: 99/100, based on 8090 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/lead+surface+ecg/PowerLab/pmc10762020-207-0-18
Average 99 stars, based on 8090 article reviews
single lead body surface ecg signals - by Bioz Stars,
2026-10
99/100 stars
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1) Product Images from "Open-source software for respiratory rate estimation using single-lead electrocardiograms"
Article Title: Open-source software for respiratory rate estimation using single-lead electrocardiograms
Journal: Scientific Reports
doi: 10.1038/s41598-023-50470-0
Figure Legend 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.
Techniques Used: Comparison
Figure Legend 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.
Techniques Used: Blocking Assay, Generated
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