Assessment of ECG Signal Quality Index Algorithms Using Synthetic ECG Data

dc.contributor.authorSyversen, Aron B.
dc.contributor.authorZhang, Zhiqiang
dc.contributor.authorBatty, Jonathan A.
dc.contributor.authorKaisti, Matti
dc.contributor.authorJayne, David
dc.contributor.authorWong, David C.
dc.contributor.organizationfi=terveysteknologia|en=Health Technology|
dc.contributor.organization-code1.2.246.10.2458963.20.28696315432
dc.converis.publication-id484547883
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/484547883
dc.date.accessioned2025-08-28T00:48:49Z
dc.date.available2025-08-28T00:48:49Z
dc.description.abstract<p>This study evaluated the performance of several publicly available signal quality indices (SQI) in assessing the quality of synthetic electrocardiogram (ECG) signals with varying categories and levels of noise. We used an existing framework to generate realistic ECG signals with controlled increases in heart rate, power line interference, white noise, and motion artifacts. ECG signals were generated at the threshold of acceptable and unacceptable outputs from each SQI across four categories of noise. The 16 signals were then evaluated by a cardiologist based on four specific criteria and these responses were compared against the SQI outputs. Results showed that the four SQI’s were inconsistent with each other; they also frequently disagreed with the cardiologist assessment. When assessing whether the ECG could be used to ’estimate a plausible heart rate’, the cardiologist assessment agreed with the SQI outputs in between 9/16 and 15/16 cases. When asked whether the ECG was ’clinically useful’, the cardiologist assessment only agreed with SQI’s in between 4/16 and 10/16 cases. The findings from this study underscore the importance of users critically analysing the outputs of SQI’s as their suitability may be limited to only basic heart rate extraction from ECG signals, rather than more comprehensive clinical applications.</p>
dc.identifier.issn2325-8861
dc.identifier.jour-issn2325-8861
dc.identifier.olddbid206462
dc.identifier.oldhandle10024/189489
dc.identifier.urihttps://www.utupub.fi/handle/11111/46212
dc.identifier.urlhttps://doi.org/10.22489/CinC.2024.270
dc.identifier.urnURN:NBN:fi-fe2025082791266
dc.language.isoen
dc.okm.affiliatedauthorKaisti, Matti
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline217 Medical engineeringen_GB
dc.okm.discipline3121 Internal medicineen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline217 Lääketieteen tekniikkafi_FI
dc.okm.discipline3121 Sisätauditfi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.conferenceComputing in cardiology conference
dc.relation.doi10.22489/CinC.2024.270
dc.relation.ispartofjournalComputing in Cardiology
dc.relation.volume51
dc.source.identifierhttps://www.utupub.fi/handle/10024/189489
dc.titleAssessment of ECG Signal Quality Index Algorithms Using Synthetic ECG Data
dc.title.bookComputing in Cardiology 2024
dc.year.issued2024

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