Rihab A Ghanma, Rania Al-Asa'd, Abeer Mohammad, Mohannad Al Qararah, Abdullah Bani Issa
Factors Affecting the Awareness of Diabetic Retinopathy: An Observational Cross-Sectional Study
Cureus
hearts study holds paramount importance human physiology driving valuable research cardiovascular health however assessing electrocardiogram ecg analysis techniques poses challenges due noise artifacts authentic recordings advent machine learning systems automated diagnosis heightened demand extensive data yet accessing medical data hindered privacy concerns consequently generating artificial ecg signals faithful real ones formidable task biomedical signal processing paper introduces method ecg signal modeling using parametric quartic splines generating new dataset based modeled signals additionally explores ecg classification using three machine learning techniques facilitated orange software addressing normal abnormal sinus rhythms classification enables early detection prediction heartrelated ailments facilitating timely clinical interventions improving patient outcomes assessment synthetic signal quality conducted power spectrum analysis crosscorrelation analysis power spectrum analysis real synthetic ecg waves provides quantitative assessment frequency content aiding validation evaluation synthetic ecg signal generation techniques crosscorrelation analysis revealing robust correlation coefficient 0974 precise alignment negligible time lag 0000 synthetic real ecg signals overall adoption quartic spline interpolation ecg modeling enhances precision smoothness fidelity signal representation thereby improving effectiveness diagnostic analytical tasks cardiology three prominent machine learning algorithms namely decision tree logistic regression gradient boosting effectively classify modeled ecg signals classification accuracies 098620 098965 099137 respectively notably models exhibit robust performance characterized high auc values classification accuracy gradient boosting logistic regression demonstrate marginally superior performance compared decision tree model across metrics models showcase commendable efficacy ecg signal classification study underscores significance accurate ecg modeling health sciences biomedical technology offering enhanced accuracy flexibility improved cardiovascular health understanding diagnostic tools