{"doi":"10.1126/sciadv.adi6492","title":"3D-printed epifluidic electronic skin for machine learning–powered multimodal health surveillance","abstract":"The amalgamation of wearable technologies with physiochemical sensing capabilities promises to create powerful interpretive and predictive platforms for real-time health surveillance. However, the construction of such multimodal devices is difficult to be implemented wholly by traditional manufacturing techniques for at-home personalized applications. Here, we present a universal semisolid extrusion–based three-dimensional printing technology to fabricate an epifluidic elastic electronic skin (e 3 -skin) with high-performance multimodal physiochemical sensing capabilities. We demonstrate that the e 3 -skin can serve as a sustainable surveillance platform to capture the real-time physiological state of individuals during regular daily activities. We also show that by coupling the information collected from the e 3 -skin with machine learning, we were able to predict an individual’s degree of behavior impairments (i.e., reaction time and inhibitory control) after alcohol consumption. The e 3 -skin paves the path for future autonomous manufacturing of customizable wearable systems that will enable widespread utility for regular health monitoring and clinical applications.","journal":"Science Advances","year":2023,"id":315214,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":199,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9472,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1014070,"name":"Roland Yingjie Tay","orcid":"0000-0002-3341-0984","position":1,"is_corresponding":false},{"id":1014071,"name":"Jiahong Li","orcid":"0000-0001-7938-9589","position":2,"is_corresponding":false},{"id":109863,"name":"Changhao Xu","orcid":"0000-0002-6817-3341","position":3,"is_corresponding":false},{"id":109864,"name":"Jihong Min","orcid":"0000-0002-5788-1473","position":4,"is_corresponding":false},{"id":255575,"name":"Ehsan Shirzaei Sani","orcid":"0000-0002-4609-1505","position":5,"is_corresponding":false},{"id":1016082,"name":"Gwangmook Kim","orcid":"0000-0002-7469-408X","position":6,"is_corresponding":false},{"id":615627,"name":"Wenzheng Heng","orcid":"0009-0009-5278-0727","position":7,"is_corresponding":false},{"id":1016083,"name":"In Ho Kim","orcid":"0000-0002-5751-7241","position":8,"is_corresponding":false},{"id":109872,"name":"Wei Gao","orcid":"0000-0002-8503-4562","position":9,"is_corresponding":false},{"id":109869,"name":"Yu Song","orcid":"0000-0002-4185-2256","position":0,"is_corresponding":true}],"reference_count":59,"raw_metadata":null,"created_at":"2026-07-19T01:06:25.560098Z","pmid":"37703361","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}