Discovery of Single Independent Latent Variable

Shaham, Uri; Svirsky, Jonathan; Katz, Ori; Talmon, Ronen

doi:10.48550/arxiv.2110.05887

Cited by 1 publication

(1 citation statement)

References 41 publications

(51 reference statements)

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“…+/-10 beats/minute corresponds to an RR interval range far greater than the RR interval differences described in the present work, making a comparison very difficult. Shaham et al [13] applied a source separation method to the NInFEA dataset but did not provide detail QRS or RR interval statistics.…”

Section: Discussionmentioning

confidence: 99%

Fetal QRS Detection by Multiple Channel Temporal Pattern Search Applied to the NInFEA Database

Hopenfeld¹

2022

Preprint

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Background: In some cases, the fetal electrocardiogram (ECG) has a relatively low signal to noise ratio. Much of the literature pertaining to fetal ECG processing focuses on methods for separating the fetal ECG from the maternal ECG rather than detecting the fetal QRS in high noise conditions. This paper describes the application of a previously described pattern search methodology (TEPS) for detecting the fetal QRS in noisy ECGs. Algorithm Summary: Signals are processed in non-overlapping 5 s segments. The maternal QRS peaks are detected in a segment from a reliable lead. Next, for each of a potentially large number of leads, after removing the maternal QRS peaks from the set of searchable peaks, single channel TEPS is applied to search for provisional fetal peak sequences. The provisional sequences are scored according to previously described single channel TEPS quality measures: temporal regularity, peak pair amplitude ratios, and number of skips. The provisional sequences across all leads are aggregated according to their average RR intervals and scores. The most likely average RR interval for the segment is estimated from this aggregation by forming a score weighted average of the RR intervals. Sequences with RR intervals close to the chosen RR interval are selected to form a set of high quality sequences. To account for the possibility of peak time offsets between different channels, these sequences are time aligned by time lagged cross correlation. An optimal sequence is formed from these time aligned sequences, with optimality criteria based on peak timing coherence, temporal regularity, and skips. Data: The above procedure was applied to 60 ECG signals (avg. duration approximately 31 s) from the Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research (NInFEA). The NInFEA dataset also includes ultrasound recordings from which RR intervals may be extracted. Results: Out of 59 records, RR intervals were well tracked in 57 records. (One of the 60 NInFEA records was excluded due to the inability to obtain a sinus rhythm peak sequence from the ultrasound recording). For these 57 records, 84% and 95% of the ECG RR intervals were within 5 ms and 10 ms, respectively, of the ultrasound derived RR intervals. The mean and median average absolute value RR interval difference (between ECG and ultrasound) over 5 second segments were 3.2 ms and 2.4 ms respectively, with 93% of segments having a mean average absolute value RR interval difference less than 7ms. Conclusion: The TEPS methodology shows promise for ECG based fetal sinus rhythm monitoring.

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Section: Discussionmentioning

confidence: 99%

Fetal QRS Detection by Multiple Channel Temporal Pattern Search Applied to the NInFEA Database

Hopenfeld¹

2022

Preprint

View full text Add to dashboard Cite

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Discovery of Single Independent Latent Variable

Cited by 1 publication

References 41 publications

Fetal QRS Detection by Multiple Channel Temporal Pattern Search Applied to the NInFEA Database

Fetal QRS Detection by Multiple Channel Temporal Pattern Search Applied to the NInFEA Database

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