Abstract

The article presents a methodology to support the process of correct cardiodiagnostics based on cardio signals recorded with modern optical photoplethysmographic (PPG) sensor devices. An algorithm for preprocessing registered PPG signals and the formation of a time series for the analysis of heart rate variability is presented, which is an important information indicator in the diagnosis of cardiovascular diseases. In order to validate the proposed algorithm, an experimental scheme for synchronous recordings of PPG and electrocardiographic (ECG) signals and the study of the accuracy of the registered signals was created. The obtained results show high accuracy of the studied signals in terms of the following parameters: number of QRS complexes/pulse waves and mean RR intervals/PP intervals and the finding that the proposed algorithm is suitable for preprocessing PPG signals, as well as the possibility of interchangeable use of PPG and ECG. The results of the mathematical analysis of heart rate variability by applying linear methods (Time-Domain and Frequency-Domain) to two groups of people are presented: healthy controls and patients with cardiovascular disease (syncope). After determining the values of the parameters of the methods used, in order to distinguish healthy subjects from sick ones, statistical analysis was applied using t-test and Receiver Operating Characteristics (ROC) analysis. The obtained results show that the linear methods used are suitable for analysing the dynamics of PP interval series and for distinguishing healthy subjects from those with pathological diseases. The presented research and analyses can find applications in guaranteeing correctness and accuracy of conducting cardiodiagnostics in clinical practice.

Highlights

  • Diagnosis of cardiovascular disease can be assisted by mathematical methods for heart rate variability (HRV) [1,2] analysis based on the study of dynamic changes in cardiac activity

  • The comparative analysis of the registered ECG and PPG signals with the presented experimental scheme was performed concerning parameter accuracy by determining the root mean square error and the relative error on the following two groups of people: Healthy individuals; Patients diagnosed with syncope

  • The determined relative error in determining the same parameters in patients with syncope is greater than 15%, which indicates impaired synchronization between ECG and PPG signals during their recording

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Summary

Introduction

Diagnosis of cardiovascular disease can be assisted by mathematical methods for heart rate variability (HRV) [1,2] analysis based on the study of dynamic changes in cardiac activity. There has been an increase in the use of HRV assessment due to the non-invasive nature of cardio signals, the clinical significance of the method, and the possibility of using it to study cardiovascular activity and many other diseases (diabetes and psychopathological disorders) [7,8] and others. Remote patient follow-up [9,10] and the use of portable medical devices have gained popularity for monitoring heart rate, which does not require complex analyses of cardiac waveforms (ECG and PPG). Research shows two things: the ability to obtain information by using PPG sensors, and it shows the need to improve this process

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