Detection of Fetal ECG R Wave From Single-Lead Abdominal ECG Using a Combination of RR Time-Series Smoothing and Template-Matching Approach

• Main Authors: He Liu, Deyun Chen, Guanghao Sun
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Fetal ECG; <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k</italic>-means; singular value decomposition; template matching; RR time-series smoothing
• Online Access: https://ieeexplore.ieee.org/document/8718289/

Fetal electrocardiograph (fECG) R-wave detection from maternal abdominal ECGs (aECGs) is challenging as it is easily distorted and often overwhelmed by a variety of unavoidable interference signals. In this study, we combined RR time-series smoothing with a template-matching (TM) approach to detect fECG R waves from a single-lead aECG. According to the quasi-periodicity of the R wave, we analyzed the cases of misaligned and missed R wave detection in the RR time series and developed an amendment algorithm to distinguish and correct them. The fECG R wave detection consists of two stages. First, an fECG R wave, which did not overlap with the maternal ECG QRS complex (mQRS), was detected. Subsequently, the amendment algorithm corrected the misaligned and missed R waves and predicted the approximate region of the fECG R wave that overlapped with the mQRS. A TM algorithm was implemented to detect the fECG R wave that overlapped with the mQRS in the approximate region. The fECG QRS complex (fQRS) and mQRS templates were built from the detected fQRS and mQRS that did not overlap with the fQRS, respectively, using singular value decomposition. The TM algorithm then determined the accurate location when the most optimal correlation occurred between the actual mQRS and the superposition of the mQRS and fQRS templates in the approximate region. The performance of the proposed method was assessed using F1 measure and Bland-Altman analysis. High accuracy values were obtained corresponding to 95% and -0.04&#x00B1;9.00 ms, respectively. The proposed method was therefore considered to enhance accurate extraction of the fECG R wave in both the clinical and commercial applications.