{"doi":"10.1002/advs.202101020","title":"Bionic Ultra‐Sensitive Self‐Powered Electromechanical Sensor for Muscle‐Triggered Communication Application","abstract":"<jats:title>Abstract</jats:title><jats:p>The past few decades have witnessed the tremendous progress of human–machine interface (HMI) in communication, education, and manufacturing fields. However, due to signal acquisition devices’ limitations, the research on HMI related to communication aid applications for the disabled is progressing slowly. Here, inspired by frogs’ croaking behavior, a bionic triboelectric nanogenerator (TENG)‐based ultra‐sensitive self‐powered electromechanical sensor for muscle‐triggered communication HMI application is developed. The sensor possesses a high sensitivity (54.6 mV mm<jats:sup>−1</jats:sup>), a high‐intensity signal (± 700 mV), and a wide sensing range (0–5 mm). The signal intensity is 206 times higher than that of traditional biopotential electromyography methods. By leveraging machine learning algorithms and Morse code, the safe, accurate (96.3%), and stable communication aid HMI applications are achieved. The authors' bionic TENG‐based electromechanical sensor provides a valuable toolkit for HMI applications of the disabled, and it brings new insights into the interdisciplinary cross‐integration between TENG technology and bionics.</jats:p>","journal":"Advanced Science","year":2021,"id":620352,"datarank":0.6515708132780527,"base_score":4.343805421853684,"endowment":4.343805421853684,"self_citation_contribution":0.6515708132780527,"citation_network_contribution":0.0,"self_endowment_contribution":0.6515708132780527,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":76,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1601426,"name":"Dongxiao Li","orcid":null,"position":1,"is_corresponding":false},{"id":1601429,"name":"Xianming He","orcid":null,"position":2,"is_corresponding":false},{"id":1601432,"name":"Xindan Hui","orcid":null,"position":3,"is_corresponding":false},{"id":313546,"name":"Hengyu Guo","orcid":"0000-0001-7133-4823","position":4,"is_corresponding":false},{"id":1601435,"name":"Chenguo Hu","orcid":null,"position":5,"is_corresponding":false},{"id":1601437,"name":"Xiaojing Mu","orcid":null,"position":6,"is_corresponding":false},{"id":65744,"name":"Zhong Lin Wang","orcid":"0000-0002-5530-0380","position":7,"is_corresponding":false},{"id":863185,"name":"Hong Zhou","orcid":"0000-0003-0120-3347","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Bionic Ultra‐Sensitive Self‐Powered Electromechanical Sensor for Muscle‐Triggered Communication Application","abstract":"<jats:title>Abstract</jats:title><jats:p>The past few decades have witnessed the tremendous progress of human–machine interface (HMI) in communication, education, and manufacturing fields. However, due to signal acquisition devices’ limitations, the research on HMI related to communication aid applications for the disabled is progressing slowly. Here, inspired by frogs’ croaking behavior, a bionic triboelectric nanogenerator (TENG)‐based ultra‐sensitive self‐powered electromechanical sensor for muscle‐triggered communication HMI application is developed. The sensor possesses a high sensitivity (54.6 mV mm<jats:sup>−1</jats:sup>), a high‐intensity signal (± 700 mV), and a wide sensing range (0–5 mm). The signal intensity is 206 times higher than that of traditional biopotential electromyography methods. By leveraging machine learning algorithms and Morse code, the safe, accurate (96.3%), and stable communication aid HMI applications are achieved. The authors' bionic TENG‐based electromechanical sensor provides a valuable toolkit for HMI applications of the disabled, and it brings new insights into the interdisciplinary cross‐integration between TENG technology and bionics.</jats:p>","is_dataset_classified":null,"base_score":4.343805421853684,"endowment":4.343805421853684,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"34081406","pmcid":"PMC8336610","openalex_id":"https://openalex.org/W3165411860","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"52075061","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"52005064","title":null},{"funder_name":"National Key Research and Development Program of China","grant_id":"2019YFB2004800","title":null},{"funder_name":"National Key Research and Development Program of China","grant_id":"2019YFB2004803","title":null},{"funder_name":"China Postdoctoral Science Foundation","grant_id":"2020M673129","title":null},{"funder_name":"Fundamental Research Funds for the Central Universities","grant_id":"2019CDCGGD320","title":null}],"total_grants":6,"fwci":3.9947,"citation_percentile":0.95030895,"influential_citations":0,"citation_trend":[{"year":2021,"count":7},{"year":2022,"count":19},{"year":2023,"count":16},{"year":2024,"count":13},{"year":2025,"count":18},{"year":2026,"count":3}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.1002/advs.202101020","host_type":"journal"},{"url":"https://doi.org/10.1002/advs.202101020","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/advs.202101020","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/full-xml/10.1002/advs.202101020","host_type":"publisher"},{"url":"https://advanced.onlinelibrary.wiley.com/doi/pdf/10.1002/advs.202101020","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/34081406","host_type":"repository"},{"url":"https://doaj.org/article/17533d1066e44287a1823054f35dc56a","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8336610","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC8336610","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC8336610?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Advanced Sensor and Energy Harvesting Materials","Conducting polymers and applications","Muscle activation and electromyography studies","Bionics","Biosensing Techniques","Electric Power Supplies","Equipment Design","Muscles","Nanotechnology","Wearable Electronic Devices"],"mesh_terms":["Wearable Electronic Devices","Bionics","Equipment Design","Muscles","Electric Power Supplies","Biosensing Techniques","Nanotechnology"],"keywords":["Bionics","Triboelectric effect","Nanogenerator","SIGNAL (programming language)","Computer science","Interface (matter)","Sensitivity (control systems)","Electrical engineering","Embedded system","Electronic engineering","Materials science","Engineering","Piezoelectricity","Artificial intelligence","Machine Learning","Morse Code","Human-machine Interfaces","Triboelectric Nanogenerators"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Quality Education"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-03T10:48:24.129482Z","pmid":null,"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":[]}