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Fig 1.

MITDB heartbeat annotations (dots) not located on R-peaks (record 107) and jitter between annotations.

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Fig 1 Expand

Fig 2.

Examples of ECG detection errors using a fixed temporal window.

d0…4 are sample numbers of detected QRS complexes. a0…4 are sample numbers of the annotated QRS complex (ground truth). w is the temporal window used for the classical performance measures sensitivity, positive predictivity, false positive rate and overall accuracy.

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Fig 3.

Experimental setup and example ECG traces.

A: Wiring of the two wireless biosignal amplifiers (Attys). The first amplifier records V1V2 with a chest strap and the second amplifier Einthoven II & III with standard Ag/AgCl electrodes. B: Photo of the chest strap and the biosignal amplifier mounted on it. Signal comparison between C: chest strap and D: Einthoven II recording while the subject was jogging.

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Fig 4.

Graphical illustration of the JF algorithm.

A: Time stamps al of the QRS annotations versus the time stamps of the actual QRS detections dk. pl links the index numbers of the annotations l = 0, 1, 2, 3 to the index numbers k of the detections dk. B: Mapping function Eq 11 which maps the average jitter to a score between zero and one which reaches 0.5 at a jitter of 12 ms.

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Fig 5.

Classical sensitivity values.

A: Einthoven, B: Chest strap. Significantly above 90% indicated with an asterisk.

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Fig 6.

JF values.

A: Einthoven, B: Chest strap. Significantly above 90% indicated with a “*”.

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Fig 7.

Comparing detector performance against increasing signal to noise ratios.

The JF benchmark value was calculated for the different activities of sitting, doing a maths test, walking, operating a hand-bike and jogging. The 4 detectors EngZee, Elgendi, WQRS and Pan& Tompkins have been benchmarked. If a JF value is significantly above 90% it is indicated with an asterisk.

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Table 1.

Original cited sensitivities from the literature, in comparison to the new overall JF benchmark scores for each detector using GUDB.

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Table 1 Expand