Classification of Cervical Dilation Stages through Combined EHG and Clinical Features: A Genetic Algorithm-Optimized Approach
Classification of Cervical Dilation Stages through Combined EHG and Clinical Features: A Genetic Algorithm-Optimized Approach
| dc.audience | students | |
| dc.audience | researchers | |
| dc.audience | teachers | |
| dc.audience | generalPublic | |
| dc.contributor.author | Otniel Portillo-Rodriguez, 0000-0002-2198-477X | |
| dc.contributor.author | OSCAR OSVALDO SANDOVAL_GONZALEZ, 0000-0002-0309-5231 | |
| dc.contributor.author | Eric Alonso Abarca-Castro, 0000-0002-2029-3790 | |
| dc.contributor.author | Juan C. Echeverría Arjonilla, 0009-0004-5625-1949 | |
| dc.contributor.author | José Javier Reyes-Lagos, 0000-0001-5361-5007 | |
| dc.contributor.author | Hugo Mendieta Zeron, 0000-0003-3492-8950 | |
| dc.contributor.other | Escalante Gaytán, Jorge | |
| dc.contributor.other | Romina Soria, Paula | |
| dc.coverage | México | |
| dc.date.accessioned | 2025-07-24T23:47:03Z | |
| dc.date.available | 2025-07-24T23:47:03Z | |
| dc.date.issued | 2025 | |
| dc.description | This open dataset contains feature vectors derived from abdominal electrohysterogram (EHG) recordings collected between 2017 and 2019 from seventy-three healthy parturient women, aged eighteen to thirty-four years and bearing pregnancies of 30.5 to 41.2 weeks’ gestation. Recordings were made at the Maternal and Childhood Research Center (CIMIGen) in Mexico City and at the Maternal-Perinatal Hospital “Mónica Pretelini-Sáenz” in Toluca, Mexico, using the Monica AN24 portable maternal–fetal monitor. Raw signals were acquired at 900 Hz, automatically resampled to 20 Hz and band-limited to 0.2 – 1 Hz before export. To preserve temporal information while enlarging the training set, every ten-minute trace was sliced into overlapping 120-second windows that slide forward in 60-second steps. This sliding-window strategy yielded 648 partially repeated samples. Each window was then split into three frequency bands: the complete 0.2 – 1 Hz band (B1), a high sub-band that emphasises the fast-wave-high component 0.34 – 1 Hz (B2) and a lower sub-band that emphasises the fast-wave-low component 0.2 – 0.34 Hz (B3). Seven signal descriptors were calculated in every band, giving twenty-one EHG features per window. Acronyms follow the pattern “metric plus band index”. • RMS1, RMS2, RMS3: Root Mean Square amplitude in B1, B2 and B3. • AUC1, AUC2, AUC3: Area Under the rectified Curve in B1, B2 and B3. • SampEn1, SampEn2, SampEn3: Sample Entropy, a measure of complexity, for each band. • MNF1, MNF2, MNF3: Mean (spectral) Frequency in each band. • MDF1, MDF2, MDF3: Median Frequency that splits spectral power in half for each band. • ZCR1, ZCR2, ZCR3: Zero-Crossing Rate, the number of sign changes per second, for each band. • BubbEn1, BubbEn2, BubbEn3: Bubble Entropy, another complexity metric, for each band. Four additional columns provide clinical context and are independent of any band-pass filtering. • MA: Maternal Age in years. • GA: Gestational Age in weeks. • LC: Low-amplitude uterine Contractions counted within the 120-second window. • HC: High-amplitude uterine Contractions counted in the same window. Two label fields complete every record. • Dilation: cervical dilation measured clinically in centimetres. • Dilation Class: labour stage derived from Dilation, coded as Low for 1–4 cm, Moderate for 5–6 cm and Advanced for 7–10 cm. Each row in the CSV file therefore contains twenty-seven columns: twenty-one band-specific EHG features, four clinical descriptors and the two dilation labels. The file, named ehg_cervical_dilation_features.csv, is encoded in UTF-8 and is distributed through the Universidad Autónoma Metropolitana institutional repository under a Creative Commons Attribution 4.0 International licence. The raw EHG recordings can be downloaded from: https://xogi.ler.uam.mx/items/c142016c-87bd-4f71-8315-459e41e42418 | |
| dc.format | text/csv | |
| dc.identificador.materia | 3 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12222/438 | |
| dc.language | eng | |
| dc.publisher | Universidad Autónoma Metropolitana. Unidad Lerma | |
| dc.rights.license | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | MEDICINA Y CIENCIAS DE LA SALUD | |
| dc.subject.keywords | EHG | |
| dc.subject.keywords | Classification | |
| dc.subject.keywords | Machine Learning | |
| dc.subject.keywords | Labor | |
| dc.subject.keywords | Physiological signals | |
| dc.title | Classification of Cervical Dilation Stages through Combined EHG and Clinical Features: A Genetic Algorithm-Optimized Approach | |
| dc.type | technicalDocumentation | |
| dc.type.version | info:eu-repo/semantics/submittedVersion |
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