{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:24:36Z","timestamp":1767338676881,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2023,7,28]],"date-time":"2023-07-28T00:00:00Z","timestamp":1690502400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"German Federal Ministry of Education and Research (BMBF)","doi-asserted-by":"publisher","award":["13N15189"],"award-info":[{"award-number":["13N15189"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Good feature engineering is a prerequisite for accurate classification, especially in challenging scenarios such as detecting the breathing of living persons trapped under building rubble using bioradar. Unlike monitoring patients\u2019 breathing through the air, the measuring conditions of a rescue bioradar are very complex. The ultimate goal of search and rescue is to determine the presence of a living person, which requires extracting representative features that can distinguish measurements with the presence of a person and without. To address this challenge, we conducted a bioradar test scenario under laboratory conditions and decomposed the radar signal into different range intervals to derive multiple virtual scenes from the real one. We then extracted physical and statistical quantitative features that represent a measurement, aiming to find those features that are robust to the complexity of rescue-radar measuring conditions, including different rubble sites, breathing rates, signal strengths, and short-duration disturbances. To this end, we utilized two methods, Analysis of Variance (ANOVA), and Minimum Redundancy Maximum Relevance (MRMR), to analyze the significance of the extracted features. We then trained the classification model using a linear kernel support vector machine (SVM). As the main result of this work, we identified an optimal feature set of four features based on the feature ranking and the improvement in the classification accuracy of the SVM model. These four features are related to four different physical quantities and independent from different rubble sites.<\/jats:p>","DOI":"10.3390\/s23156771","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T02:13:32Z","timestamp":1690769612000},"page":"6771","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Automatic Life Detection Based on Efficient Features of Ground-Penetrating Rescue Radar Signals"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3987-6731","authenticated-orcid":false,"given":"Di","family":"Shi","sequence":"first","affiliation":[{"name":"Laboratory for Electrical Instrumentation and Embedded Systems, Department of Microsystems Engineering\u2014IMTEK, University of Freiburg, Georges-K\u00f6hler-Allee 106, 79110 Freiburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0114-9056","authenticated-orcid":false,"given":"Gunnar","family":"Gidion","sequence":"additional","affiliation":[{"name":"Laboratory for Electrical Instrumentation and Embedded Systems, Department of Microsystems Engineering\u2014IMTEK, University of Freiburg, Georges-K\u00f6hler-Allee 106, 79110 Freiburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5068-8929","authenticated-orcid":false,"given":"Leonhard M.","family":"Reindl","sequence":"additional","affiliation":[{"name":"Laboratory for Electrical Instrumentation and Embedded Systems, Department of Microsystems Engineering\u2014IMTEK, University of Freiburg, Georges-K\u00f6hler-Allee 106, 79110 Freiburg, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4806-9838","authenticated-orcid":false,"given":"Stefan J.","family":"Rupitsch","sequence":"additional","affiliation":[{"name":"Laboratory for Electrical Instrumentation and Embedded Systems, Department of Microsystems Engineering\u2014IMTEK, University of Freiburg, Georges-K\u00f6hler-Allee 106, 79110 Freiburg, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,28]]},"reference":[{"key":"ref_1","unstructured":"SIFO (2023, March 10). FOUNT\u00b2: Fliegendes Lokalisierungssystem f\u00fcr die Rettung und Bergung von Versch\u00fctteten. Available online: https:\/\/www.sifo.de\/sifo\/de\/projekte\/schutz-und-rettung-von-menschen\/innovative-rettungs-und-sicherheitssysteme\/fount2\/fount2_node.html."},{"key":"ref_2","unstructured":"SIFO (2023, March 10). SORTIE: Sensor-Systeme zur Lokalisierung von Versch\u00fctteten Personen in Eingest\u00fcrzten Geb\u00e4uden. Available online: https:\/\/www.sifo.de\/sifo\/de\/projekte\/schutz-und-rettung-von-menschen\/internationales-katastrophen-und-risikomanagement\/sortie-sensor-systeme-zur-loka-en-in-eingestuerzten-gebaeuden\/sortie-sensor-systeme-zur-loka-en-in-eingestuerzten-gebaeuden.html."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Shi, D., Aftab, T., Gidion, G., Sayed, F., and Reindl, L.M. (2021). A novel electrically small ground-penetrating radar patch antenna with a parasitic ring for respiration detection. 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