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Non-invasive monitoring of fetal electrocardiogram (fECG) plays an important role in detecting and diagnosing fetal diseases. This study aimed to develop a multi-step method for locating both maternal and fetal QRS complexes from abdominal ECG (aECG) recordings. The proposed method included four major steps: abdominal ECG pre-processing, maternal QRS complex locating, maternal ECG cancellation and fetal QRS complex locating. Signal quality assessment (SQA) and fine-tuning for maternal ECG (FTM) were implemented in the first and third steps, respectively. The method was then evaluated using 75 non-invasive 4-channel aECG recordings provided by the PhysioNet/Computing in Cardiology Challenge 2013. The F1 measure, which is a new index introduced by Behar et al (2013 Proc. Comput. Cardiol. 40 297-300), was used to assess the locating accuracy. The other two indices, mean squared error of heart rate (MSE_HR) between the fetal HR signals estimated from the reference and our method (MSE_HR in bpm(2)) and root mean squared difference between the corresponding fetal RR intervals (MSE_RR in ms) were also used to assess the locating accuracy. Overall, for the maternal QRS complex, the F1 measure was 98.4% from the method without the implementation of SQA, and it was improved to 99.8% with SQA. For the fetal QRS complex, the F1 measure, MSE_HR and MSE_RR were 84.9%, 185.6 bpm(2) and 19.4 ms for the method without both SQA and FTM procedures. They were improved to 93.9%, 47.5 bpm(2) and 7.6 ms with both SQA and FTM procedures. These improvements were observed from each individual subject. It can be concluded that implementing both SQA and FTM procedures could achieve better performance for locating both maternal and fetal QRS complexes.

This study presents a systematic comparison of different approaches to the automated selection of the principal components (PC) which optimise the detection of maternal and fetal heart beats from non-invasive maternal abdominal recordings.A public database of 75 4-channel non-invasive maternal abdominal recordings was used for training the algorithm. Four methods were developed and assessed to determine the optimal PC: (1) power spectral distribution, (2) root mean square, (3) sample entropy, and (4) QRS template. The sensitivity of the performance of the algorithm to large-amplitude noise removal (by wavelet de-noising) and maternal beat cancellation methods were also assessed. The accuracy of maternal and fetal beat detection was assessed against reference annotations and quantified using the detection accuracy score F1 [2*PPV*Se / (PPV + Se)], sensitivity (Se), and positive predictive value (PPV). The best performing implementation was assessed on a test dataset of 100 recordings and the agreement between the computed and the reference fetal heart rate (fHR) and fetal RR (fRR) time series quantified.The best performance for detecting maternal beats (F1 99.3%, Se 99.0%, PPV 99.7%) was obtained when using the QRS template method to select the optimal maternal PC and applying wavelet de-noising. The best performance for detecting fetal beats (F1 89.8%, Se 89.3%, PPV 90.5%) was obtained when the optimal fetal PC was selected using the sample entropy method and utilising a fixed-length time window for the cancellation of the maternal beats. The performance on the test dataset was 142.7 beats(2)/min(2) for fHR and 19.9 ms for fRR, ranking respectively 14 and 17 (out of 29) when compared to the other algorithms presented at the Physionet Challenge 2013.

Objective. Multisite photoplethysmography (PPG) cardiovascular assessments can evaluate endothelial, peripheral autonomic and arterial dysfunction. The aim of this pilot study was to investigate the potential clinical utility of the technology in assessing patients with SSc and primary RP (PRP).Methods. Multisite PPG pulse measurements, a reference ankle brachial pressure index (ABPI) and a full clinical assessment were undertaken for three subject groups: SSc, PRP and controls. Endothelial and autonomic function and arterial disease measures were obtained using pulse wave analysis.Results. Nineteen SSc, 19 PRP and 23 control subjects were assessed and compared. Endothelial function was significantly impaired in SSc (P < 0.02), but with no difference between controls and PRP. Receiver operating characteristic–based classification accuracy was 81% (sensitivity 90%, specificity 74%) for separating SSc from controls and 82% (sensitivity 84%, specificity 79%) for separating SSc from PRP. SSc patients with digital ulcers had significantly lower endothelial function compared with those without ulcers (P < 0.05). Autonomic dysfunction was suggested in both SSc and PRP and was most exaggerated in patients with diffuse SSc. All groups had overall normal ABPI and arterial stiffness timing measures. Bilateral timing differences at the toes, which represents peripheral occlusive arterial disease, did show increased asymmetry in SSc (P < 0.02).Conclusion. Multisite PPG pulse technology showed potential diagnostic ability. By using measures of endothelial function, it differentiated SSc from control and PRP subjects with an accuracy of at least 81%. Objective pulse-derived measures of autonomic function and arterial disease in SSc have also been reported in this pilot study. [ABSTRACT FROM PUBLISHER]