2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2018
DOI: 10.1109/embc.2018.8513614
|View full text |Cite
|
Sign up to set email alerts
|

Signal Separation for Transabdominal Non-invasive Fetal Pulse Oximetry using Comb Filters

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2020
2020
2022
2022

Publication Types

Select...
2
2

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(4 citation statements)
references
References 12 publications
0
4
0
Order By: Relevance
“…This work demonstrates an extended signal processing strategy for the extraction of the fetal pulse wave from mixed signals measured with transabdominal fetal pulse oximetry. The core of the strategy is an ANC and a comb filter, realized with algorithms presented in our former works [8], [7]. The application of a synchronous averaging procedure enhances the strategy to get a reliable information about the shape of the fetal pulse wave.…”
Section: Discussionmentioning
confidence: 99%
See 3 more Smart Citations
“…This work demonstrates an extended signal processing strategy for the extraction of the fetal pulse wave from mixed signals measured with transabdominal fetal pulse oximetry. The core of the strategy is an ANC and a comb filter, realized with algorithms presented in our former works [8], [7]. The application of a synchronous averaging procedure enhances the strategy to get a reliable information about the shape of the fetal pulse wave.…”
Section: Discussionmentioning
confidence: 99%
“…It can be seen that the signals in Setup 1 are disturbed by cross terms, represented by small peaks between the fetal and maternal component. They are analyzed more in detail in our former works in [10], [8]. Due to the heart rate variability, the maternal and fetal component are not separable in the overall frequency spectrum of the artificial signal (upper left plot of Fig.…”
Section: B Synthetic Datasetsmentioning
confidence: 99%
See 2 more Smart Citations