Cardiotocograph (CTG) is widely used in everyday clinical practice for fetal surveillance, where it is used to record fetal heart rate (FHR) and uterine activity (UA). These two biosignals can be used for antepartum and intrapartum fetal monitoring and are, in fact, nonlinear and non-stationary. CTG recordings are often corrupted by artifacts such as missing beats in FHR, high-frequency noise in FHR and UA signals. In this paper, an empirical mode decomposition (EMD) method is applied on CTG signals. A recursive algorithm is first utilized to eliminate missing beats. High-frequency noise is reduced using EMD followed by the partial reconstruction (PAR) method, where the noise order is identified by a statistical method. The obtained signal enhancement from the proposed method is validated by comparing the resulting traces with the output obtained by applying classical signal processing methods such as Butterworth low-pass filtering, linear interpolation and a moving average filter on 12 CTG signals. Three obstetricians evaluated all 12 sets of traces and rated the proposed method, on average, 3.8 out of 5 on a scale of 1(lowest) to 5 (highest).
In this report, a facile and label-free electrochemical RNA biosensor is developed by exploiting methylene blue (MB) as an electroactive positive ligand of G-quadruplex. The electrochemical response mechanism of the nucleic acid assay was based on the change in differential pulse voltammetry (DPV) signal of adsorbed MB on the immobilized human telomeric G-quadruplex DNA with a loop that is complementary to the target RNA. Hybridization between synthetic positive control RNA and G-quadruplex DNA probe on the transducer platform rendered a conformational change of G-quadruplex to double-stranded DNA (dsDNA), and increased the redox current of cationic MB π planar ligand at the sensing interface, thereby the electrochemical signal of the MB-adsorbed duplex is proportional to the concentration of target RNA, with SARS-CoV-2 (COVID-19) RNA as the model. Under optimal conditions, the target RNA can be detected in a linear range from 1 zM to 1 μM with a limit of detection (LOD) obtained at 0.59 zM for synthetic target RNA and as low as 1.4 copy number for positive control plasmid. This genosensor exhibited high selectivity towards SARS-CoV-2 RNA over other RNA nucleotides, such as SARS-CoV and MERS-CoV. The electrochemical RNA biosensor showed DPV signal, which was proportional to the 2019-nCoV_N_positive control plasmid from 2 to 200000 copies (R2 = 0.978). A good correlation between the genosensor and qRT-PCR gold standard was attained for the detection of SARS-CoV-2 RNA in terms of viral copy number in clinical samples from upper respiratory specimens.