Machine learning and electrocardiography signal-based minimum calculation time detection for blood pressure detection
Yükleniyor...
Dosyalar
Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Hindawi Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Objective. Measurement and monitoring of blood pressure are of great importance for preventing diseases such as cardiovascular and stroke caused by hypertension. Therefore, there is a need for advanced artificial intelligence-based systolic and diastolic blood pressure systems with a new technological infrastructure with a noninvasive process. The study is aimed at determining the minimum ECG time required for calculating systolic and diastolic blood pressure based on the Electrocardiography (ECG) signal. Methodology. The study includes ECG recordings of five individuals taken from the IEEE database, measured during daily activity. For the study, each signal was divided into epochs of 2-4-6-8-10-12-14-16-18-20 seconds. Twenty-five features were extracted from each epoched signal. The dimension of the dataset was reduced by using Spearman's feature selection algorithm. Analysis based on metrics was carried out by applying machine learning algorithms to the obtained dataset. Gaussian process regression exponential (GPR) machine learning algorithm was preferred because it is easy to integrate into embedded systems. Results. The MAPE estimation performance values for diastolic and systolic blood pressure values for 16-second epochs were 2.44 mmHg and 1.92 mmHg, respectively. Conclusion. According to the study results, it is evaluated that systolic and diastolic blood pressure values can be calculated with a high-performance ratio with 16-second ECG signals.
Açıklama
Anahtar Kelimeler
Pulse Transit-Time, Measuring Devices, Hypertension, Prevention, Adults, Photoplethysmography
Kaynak
Computational and Mathematical Methods in Medicine
WoS Q Değeri
N/A
Scopus Q Değeri
Q2
Cilt
2022
Sayı
Künye
Nour, M., Kandaz, D., Ucar, M. K., Polat, K., & Alhudhaif, A. (2022). Machine Learning and Electrocardiography Signal-Based Minimum Calculation Time Detection for Blood Pressure Detection. Computational and Mathematical Methods in Medicine, 2022.
