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Single-lead electrocardiography (ECG) technologies and photoplethysmography (PPG) deriving smartphone apps are gaining interest in the heart rhythm detection space since these apps have the potential to capture and assess heart rhythms. Proprietary arrhythmia detection algorithms are proven to be reliable and accurate. However, insights into the readability of PPG waveforms by human reviewers remain limited. To the investigators' knowledge, there are no publications available regarding the readability of PPG waveforms by human reviewers. The objective of the study was to assess the readability of PPG and single-lead ECG analysis by medical professionals, with respect to the gold-standard 12-lead ECG diagnosis, and investigate whether additional information positively impacts PPG analysis.
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During the study, the readability of PPG and single-lead ECG waveform analysis will be investigated. The objective of the study is to determine the readability of PPG and single-lead ECG measurements, with respect to the gold-standard 12-lead ECG, and investigate whether additional information positively impacts the readability of PPG. Medical professionals (cardiologists and cardiology residents), blinded for the patients' characteristics and history, are instructed to separately analyse the following signals, obtained from 30 patients.
Participants report the results of the qualitative analysis via a digital questionnaire with multiple-choice questions. Medical professionals classify each rhythm trace as regular rhythm, one or more ectopic/missed heartbeats, atrial flutter, atrial fibrillation, unreadable, or other. The tachogram, Poincaré, and the algorithm interpretation are subsequently added to investigate whether the additional information improves the readability of PPG. Based on the provided answers, the study team will determine the readability of PPG and single-lead ECG analysis interpretation, with respect to the gold-standard 12-lead ECG diagnosis.
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Inclusion Criteria:
76 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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