{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T22:25:14Z","timestamp":1777415114446,"version":"3.51.4"},"reference-count":26,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T00:00:00Z","timestamp":1653955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"FCT\/MCTES","award":["UIDB\/50008\/2020"],"award-info":[{"award-number":["UIDB\/50008\/2020"]}]},{"name":"EU","award":["UIDB\/50008\/2020"],"award-info":[{"award-number":["UIDB\/50008\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This article proposes a new method of identity recognition in sanitary facilities based on electrocardiography (ECG) signals. Our team previously proposed a novel approach of invisible ECG at the thighs using polymeric electrodes, leading to the creation of a proof-of-concept system integrated into a toilet seat. In this work, a biometrics pipeline was devised, which tested four different classifiers, varying the population from 2 to 17 subjects and simulating a residential environment. However, for this approach to be industrially viable, further optimization is required, particularly regarding electrode materials that are compatible with industrial processes. As such, we also explore the use of a conductive silicone material as electrodes, aiming at the industrial-scale production of a toilet seat capable of recording ECG data, without the need for body-worn devices. A desirable aspect when using such a system is matching the recorded data with the monitored user, ideally using a minimal sensor set, further reinforcing the relevance of user identification through ECG signals collected at the thighs. Our approach was evaluated against a reference device for a population of 17 healthy and pathological individuals, covering a wide age range (24\u201370 years). With the silicone composite, we were able to acquire signals in 100% of the sessions, with a mean heart rate deviation between a reference system and our experimental device of 2.82 \u00b1 1.99 beats per minute (BPM). In terms of ECG waveform morphology, the best cases showed a Pearson correlation coefficient of 0.91 \u00b1 0.06. For biometric detection, the best classifier was the Binary Convolutional Neural Network (BCNN), with an accuracy of 100% for a population of up to four individuals.<\/jats:p>","DOI":"10.3390\/s22114201","type":"journal-article","created":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T21:43:42Z","timestamp":1654119822000},"page":"4201","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Identity Recognition in Sanitary Facilities Using Invisible Electrocardiography"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7588-1349","authenticated-orcid":false,"given":"Aline Santos","family":"Silva","sequence":"first","affiliation":[{"name":"FEUP\u2014Faculdade de Engenharia da Universidade do Porto, 4200-465 Porto, Portugal"},{"name":"IT\u2014Instituto de Telecomunica\u00e7\u00f5es, 1049-001 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6065-9358","authenticated-orcid":false,"given":"Miguel Velhote","family":"Correia","sequence":"additional","affiliation":[{"name":"FEUP\u2014Faculdade de Engenharia da Universidade do Porto, 4200-465 Porto, Portugal"},{"name":"INESC TEC\u2014Institute for Systems and Computer Engineering, Technology and Science, 4200-365 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1919-4661","authenticated-orcid":false,"given":"Francisco","family":"de Melo","sequence":"additional","affiliation":[{"name":"IT\u2014Instituto de Telecomunica\u00e7\u00f5es, 1049-001 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6764-8432","authenticated-orcid":false,"given":"Hugo Pl\u00e1cido","family":"da Silva","sequence":"additional","affiliation":[{"name":"IT\u2014Instituto de Telecomunica\u00e7\u00f5es, 1049-001 Lisboa, Portugal"},{"name":"Department of Bioengineering, Instituto Superior T\u00e9cnico, 1049-001 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1007\/s11760-008-0073-4","article-title":"ECG biometric analysis in cardiac irregularity conditions","volume":"3","author":"Agrafioti","year":"2009","journal-title":"Signal Image Video Process."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1812","DOI":"10.1109\/TIFS.2012.2215324","article-title":"ECG Biometric Recognition: A Comparative Analysis","volume":"7","author":"Odinaka","year":"2012","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.patrec.2018.03.028","article-title":"Deep-ECG: Convolutional neural networks for ECG biometric recognition","volume":"126","author":"Labati","year":"2019","journal-title":"Pattern Recognit. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1109\/TIFS.2020.3006384","article-title":"Learning Joint and specific patterns: A unified sparse representation for off-the-person ECG biometric recognition","volume":"16","author":"Huang","year":"2020","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"6222","DOI":"10.1038\/s41598-021-85697-2","article-title":"Design and evaluation of a novel approach to invisible electrocardiography (ECG) in sanitary facilities using polymeric electrodes","volume":"11","author":"Almeida","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ghosh, D., Giri, D., Mohapatra, R., Savas, E., Sakurai, K., and Singh, L. (2018, January 9\u201311). ECG Biometric Recognition. Proceedings of the International Conference on Mathematics and Computing, Varanasi, India.","DOI":"10.1007\/978-981-13-2095-8"},{"key":"ref_7","unstructured":"Foshan, E.T. (2017). Human Body Impedance Measuring Toilet Seat and Closestool. (Application No. CN201720475328.8U), International Patent, Available online: https:\/\/patents.google.com\/patent\/CN207870820U\/en?oq=CN207870820+."},{"key":"ref_8","unstructured":"Guangzhou, Y.F. (2017). A Kind of Multi-Function Water Closet Cover Plate. (Application No. CN201721109114.5U), International Patent, Available online: https:\/\/patents.google.com\/patent\/CN208551795U\/en?oq=CN208551795."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1038\/s41551-020-0534-9","article-title":"A mountable toilet system for personalized health monitoring via the analysis of excreta","volume":"4","author":"Park","year":"2020","journal-title":"Nat. Biomed. Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"106517","DOI":"10.1016\/j.nanoen.2021.106517","article-title":"Artificial intelligence of toilet (AI-Toilet) for an integrated health monitoring system (IHMS) using smart triboelectric pressure sensors and image sensor","volume":"90","author":"Zhang","year":"2021","journal-title":"Nano Energy"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Kurahashi, M., Murao, K., Terada, T., and Tsukamoto, M. (2017, January 13\u201317). Personal identification system based on rotation of toilet paper rolls. Proceedings of the 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Kona, HI, USA.","DOI":"10.1109\/PERCOMW.2017.7917617"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Hong, P., Hsiao, J., Chung, C., Feng, Y., and Wu, S. (2019, January 23\u201327). ECG biometric recognition: Template-free approaches based on deep learning. Proceedings of the 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany.","DOI":"10.1109\/EMBC.2019.8856916"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1109\/JIOT.2020.3004362","article-title":"ECG Biometric Recognition: Unlinkability, Irreversibility, and Security","volume":"8","author":"Wu","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_14","unstructured":"Protoplant, I. (2018). Technical Data Sheet: Proto-Pasta, Protoplant Inc.. Available online: https:\/\/cdn.shopify.com\/s\/files\/1\/0717\/9095\/files\/CDP1xxxx_SDS.pdf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1109\/MPRV.2014.61","article-title":"Biosignals for Everyone","volume":"13","author":"Silva","year":"2014","journal-title":"IEEE Pervasive Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1109\/TBME.2019.2913913","article-title":"Design and Evaluation of a Diaphragm for Electrocardiography in Electronic Stethoscopes","volume":"67","author":"Martins","year":"2020","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Louren\u00e7o, A., Silva, H., and Carreiras, C. (2013, January 26\u201328). Outlier detection in non-intrusive ECG biometric system. In image analysis and recognition. Proceedings of the 10th International Conference, ICIAR, Aveiro, Portugal.","DOI":"10.1007\/978-3-642-39094-4_6"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1016\/j.procs.2015.03.201","article-title":"Na\u00efve Bayes Classifier for ECG Abnormalities Using Multivariate Maximal Time Series Motif","volume":"47","author":"Padmavathi","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Belo, D., Bento, N., Silva, H., Fred, A., and Gamboa, H. (2020). ECG Biometrics Using Deep Learning and Relative Score Threshold Classification. Sensors, 20.","DOI":"10.3390\/s20154078"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kim, J., Yang, G., Kim, J., Lee, S., Kim, K.K., and Park, C. (2021). Efficiently Updating ECG-Based Biometric Authentication Based on Incremental Learning. Sensors, 21.","DOI":"10.3390\/s21051568"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"De Melo, F., Neto, H.C., and da Silva, H.P. (2022). System on Chip (SoC) for Invisible Electrocardiography (ECG) Biometrics. Sensors, 22.","DOI":"10.3390\/s22010348"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1109\/72.991427","article-title":"A comparison of methods for multiclass support vector machines","volume":"13","author":"Hsu","year":"2002","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ghofrani, N., and Boostani, R. (2010, January 3\u20134). Reliable features for an ECG-based biometric system. Proceedings of the 2010 17th Iranian Conference of Biomedical Engineering (ICBME), Isfahan, Iran.","DOI":"10.1109\/ICBME.2010.5704918"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"012019","DOI":"10.1088\/1742-6596\/1900\/1\/012019","article-title":"Review on Data Acquisition of Electrocardiogram Biometric Recognition in Wearable Smart Textile Shirts","volume":"1900","author":"Nawawi","year":"2021","journal-title":"J. Physics Conf. Ser."},{"key":"ref_25","first-page":"29","article-title":"SUS: A Retrospective","volume":"8","author":"Brooke","year":"2013","journal-title":"J. Usability Stud."},{"key":"ref_26","unstructured":"Dos Santos Silva, A., and da Silva, H.P. (2022, January 24). Electrocardiografia Invis\u00edvel (ECG) em Instala\u00e7\u00f5es Sanit\u00e1rias Usando Eletrodos Polim\u00e9ricos. T\u00e9cnica, Available online: https:\/\/www.nature.com\/articles\/s41598-021-85697-2."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/11\/4201\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:22:52Z","timestamp":1760138572000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/11\/4201"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,31]]},"references-count":26,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2022,6]]}},"alternative-id":["s22114201"],"URL":"https:\/\/doi.org\/10.3390\/s22114201","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,31]]}}}