{"doi":"10.21923/jesd.745275","title":"SAMPLE ENTROPY ANALYSIS OF HEART RATE VARIABILITY IN RR INTERVAL DETECTION","abstract":"<jats:p xml:lang=\"en\">Entropy is a robust method that is able to measure irregularities or the general behavior of the complex time series which could be continuously interact with many different and independent factors in time. This study aimed to investigate the sample entropy measurement of heart rate variability (HRV) for evaluating of 50Hz interference and baseline wander (BW) noise effects on RR interval. Three different synthetic electrocardiogram (ECG) signals were recorded using the simulator device. Sample Entropy (SampEn) values of full length and windowed length of data were calculated to track and identify RR intervals.  It was found that adult normal sinus rhythm (NSR) signal without noise had the most regular and consistent results while adult ECG signal with BW noisy had the most irregular and inconsistent results. Furthermore, the BW noisy had more effect on irregularity ECG signal than 50 Hz interference. Consequently, the SampEn provided the measurement of irregularity and randomness of ECG data. However, it was found that the determination of RR intervals for classification and decision support systems was not practical in real-time analysis of HRV from raw ECG recordings because of noisy affect.</jats:p>","journal":"Mühendislik Bilimleri ve Tasarım Dergisi","year":2020,"id":655919,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1712204,"name":"Veysel ALCAN","orcid":"0000-0002-7786-8591","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"SAMPLE ENTROPY ANALYSIS OF HEART RATE VARIABILITY IN RR INTERVAL DETECTION","abstract":"<jats:p xml:lang=\"en\">Entropy is a robust method that is able to measure irregularities or the general behavior of the complex time series which could be continuously interact with many different and independent factors in time. This study aimed to investigate the sample entropy measurement of heart rate variability (HRV) for evaluating of 50Hz interference and baseline wander (BW) noise effects on RR interval. Three different synthetic electrocardiogram (ECG) signals were recorded using the simulator device. Sample Entropy (SampEn) values of full length and windowed length of data were calculated to track and identify RR intervals.  It was found that adult normal sinus rhythm (NSR) signal without noise had the most regular and consistent results while adult ECG signal with BW noisy had the most irregular and inconsistent results. Furthermore, the BW noisy had more effect on irregularity ECG signal than 50 Hz interference. Consequently, the SampEn provided the measurement of irregularity and randomness of ECG data. However, it was found that the determination of RR intervals for classification and decision support systems was not practical in real-time analysis of HRV from raw ECG recordings because of noisy affect.</jats:p>","is_dataset_classified":null,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":null,"pmcid":null,"openalex_id":"https://openalex.org/W3088843374","authors":[],"funders":[],"total_grants":0,"fwci":0.0,"citation_percentile":0.17344655,"influential_citations":0,"citation_trend":[{"year":2024,"count":1},{"year":2025,"count":1}],"oa_status":"gold","license":null,"oa_locations":[{"url":"https://dergipark.org.tr/en/download/article-file/1126143","host_type":"journal"},{"url":"https://dergipark.org.tr/en/download/article-file/1126143","host_type":"publisher"},{"url":"https://doi.org/10.21923/jesd.745275","host_type":"journal"},{"url":"https://dergipark.org.tr/tr/pub/jesd/issue/56892/745275","host_type":""}],"fields_of_study":["Heart Rate Variability and Autonomic Control","Non-Invasive Vital Sign Monitoring","EEG and Brain-Computer Interfaces"],"mesh_terms":[],"keywords":["Sample entropy","RR interval","Heart rate variability","Approximate entropy","Normal Sinus Rhythm","Pattern recognition (psychology)","Randomness","Mathematics","Entropy (arrow of time)","Statistics","Rhythm","Detrended fluctuation analysis","Computer science","Heart rate","Artificial intelligence","Speech recognition","Medicine","Cardiology","Internal medicine","Physics"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Peace, Justice and strong institutions"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-11T19:21:06.450119Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}