{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,3]],"date-time":"2026-01-03T06:46:00Z","timestamp":1767422760084,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,11,26]],"date-time":"2018-11-26T00:00:00Z","timestamp":1543190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Electrocardiograph (ECG) technology is vital for biometric security, and blood oxygen is essential for human survival. In this study, ECG signals and blood oxygen levels are combined to increase the accuracy and efficiency of human identification and verification. The proposed scheme maps the combined biometric information to a matrix and quantifies it as a sparse matrix for reorganizational purposes. Experimental results confirm a much better identification rate than in other ECG-related identification studies. The literature shows no research in human identification using the quantization sparse matrix method with ECG and blood oxygen data combined. We propose a multi-dimensional approach that can improve the accuracy and reduce the complexity of the recognition algorithm.<\/jats:p>","DOI":"10.3390\/s18124138","type":"journal-article","created":{"date-parts":[[2018,11,27]],"date-time":"2018-11-27T03:31:33Z","timestamp":1543289493000},"page":"4138","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Electrocardiograph Identification Using Hybrid Quantization Sparse Matrix and Multi-Dimensional Approaches"],"prefix":"10.3390","volume":"18","author":[{"given":"Kuo-Kun","family":"Tseng","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen 518055, China"}]},{"given":"Jiao","family":"Lo","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen 518055, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8723-6152","authenticated-orcid":false,"given":"Chih-Cheng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Jimei University, Xiamen 361021, China"}]},{"given":"Shu-Yi","family":"Tu","sequence":"additional","affiliation":[{"name":"Mathematics Department, University of Michigan, Flint, Ann Arbor, MI 48502, USA"}]},{"given":"Cheng-Fu","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Chemical and Materials Eng., N.U.K., Kaohsiung 81148, Taiwan"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1172","DOI":"10.1016\/j.patrec.2007.01.014","article-title":"Verification of humans using the electrocardiogram","volume":"28","author":"Stavridis","year":"2007","journal-title":"Pattern Recognit. 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