{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T16:13:19Z","timestamp":1787242399380,"version":"build-2736575974"},"reference-count":64,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Deaf individuals often face communication challenges when interacting with those who can hear. Within health care settings, these challenges may pose risks to their safety, potentially resulting in misdiagnoses, treatment errors, and decreased quality of care.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study aims to systematically review the evidence on communication systems reported in the literature that use human-computer interaction techniques to support communication between deaf individuals who use sign language and hearing health professionals in health care settings. The review focuses on systems that are either currently in use or proposed for use in health care and that have been tested using human participants or videos of human users.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A comprehensive search was performed via MEDLINE, Web of Science, ACM, IEEE Xplore, Scopus, and Google Scholar in March 2025. The inclusion criteria comprised studies developing a sign language recognition system within a health care context and testing with human users. Eligible studies underwent screening by 2 independent investigators (LRV and LMMSR or LFRdO and GTdSS), with any disagreements resolved by a senior researcher (MSM).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The search retrieved 21,778 publications, and screening of reference lists identified 2 additional studies, resulting in a total of 23 studies meeting the eligibility criteria. Most systems (15\/23, 65.2%) were image-based, while 34.8% (8\/23) relied on sensors (glove-based or depth-sensing). Applications varied across health care settings, including general hospital care (10\/23, 43.5%), emergencies (8\/23, 34.8%), and primary care (4\/23, 17.4%). All systems were in the development and testing stage, with no data on security and psychological impacts. Accuracy ranged from 25% to 100% for image-based and 72% to 99.7% for sensor-based systems. Bidirectionality and facial expression recognition, crucial for effective communication, were largely overlooked.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Image-based systems were more common than sensor-based ones, though both showed wide variability in accuracy in recognizing and interpreting signs. Most systems failed to address critical aspects such as bidirectional communication and the recognition of facial expressions, essential for effective communication. None fully addresses the requirements for integration into health care settings. These findings highlight the need for further research on implementation, usability, and impact on the quality of care for deaf patients.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/70417","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T19:54:39Z","timestamp":1775764479000},"page":"e70417-e70417","source":"Crossref","is-referenced-by-count":3,"title":["Innovations in Deaf Health Care Communication: Systematic Review of Sign Language Recognition Systems"],"prefix":"10.2196","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4278-3771","authenticated-orcid":false,"given":"Milena Soriano","family":"Marcolino","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2248-1218","authenticated-orcid":false,"given":"Lucca Fagundes Ramos de","family":"Oliveira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0676-8657","authenticated-orcid":false,"given":"Lucas Rocha","family":"Valle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4741-4871","authenticated-orcid":false,"given":"Luiza Marinho Motta Santa","family":"Rosa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8878-7925","authenticated-orcid":false,"given":"Gabriela Teodora de Souza","family":"Sanches","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6037-1378","authenticated-orcid":false,"given":"Natalia Sales","family":"Santos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4990-0627","authenticated-orcid":false,"given":"Michelle Ralil da","family":"Costa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3718-9631","authenticated-orcid":false,"given":"Elidea Lucia Almeida","family":"Bernardino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5588-6023","authenticated-orcid":false,"given":"Raniere Alislan Almeida","family":"Cordeiro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7128-4974","authenticated-orcid":false,"given":"Raquel Oliveira","family":"Prates","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6374-9295","authenticated-orcid":false,"given":"Zilma Silveira Nogueira","family":"Reis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8336-9190","authenticated-orcid":false,"given":"Mario Fernando Montenegro","family":"Campos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,4,9]]},"reference":[{"key":"R1","doi-asserted-by":"crossref","unstructured":"Bragg D Koller O Bellard M et al. Sign language recognition, generation, and translation: an interdisciplinary perspective. Presented at: Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility; Oct 28-30, 2019; Pittsburgh, PA, United States. [doi: 10.1145\/3308561.3353774]","DOI":"10.1145\/3308561.3353774"},{"key":"R2","doi-asserted-by":"crossref","unstructured":"Kendon A . Gesture Visible Action as Utterance. Cambridge University Press; 2004. ISBN: 0521542936","DOI":"10.1017\/CBO9780511807572"},{"key":"R3","unstructured":"Deafness and hearing loss. World Health Organization. 2023. URL: https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/deafness-and-hearing-loss [Accessed 14-11-2024]"},{"key":"R4","unstructured":"World Federation of the Deaf. URL: https:\/\/wfdeaf.org [Accessed 05-12-2025]"},{"issue":"4","key":"R5","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1046\/j.1365-2524.2002.00365.x","article-title":"Inequalities in access to healthcare faced by women who are deaf","volume":"10","author":"Ubido","journal-title":"Health Soc Care Community"},{"issue":"1","key":"R6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/deafed\/env042","article-title":"Health care access among deaf people","volume":"21","author":"Kuenburg","journal-title":"J Deaf Stud Deaf Educ"},{"issue":"15-16","key":"R7","doi-asserted-by":"publisher","first-page":"4454","DOI":"10.1111\/jocn.16572","article-title":"Individuals with hearing impairment\/deafness during the COVID-19 pandemic: a rapid review on communication challenges and strategies","volume":"32","author":"Mansutti","journal-title":"J Clin Nurs"},{"issue":"1","key":"R8","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-023-16924-w","article-title":"Deaf and hard-of-hearing patients are unsatisfied with and avoid German health care: results from an online survey in German Sign Language","volume":"23","author":"Rannefeld","journal-title":"BMC Public Health"},{"key":"R9","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113794","article-title":"Sign language recognition: a deep survey","volume":"164","author":"Rastgoo","journal-title":"Expert Syst Appl"},{"issue":"17","key":"R10","doi-asserted-by":"publisher","DOI":"10.3390\/s21175843","article-title":"Artificial intelligence technologies for sign language","volume":"21","author":"Papastratis","journal-title":"Sensors (Basel)"},{"issue":"1","key":"R11","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1093\/deafed\/enj003","article-title":"Sign language recognition and translation: a multidisciplined approach from the field of artificial intelligence","volume":"11","author":"Parton","journal-title":"J Deaf Stud Deaf Educ"},{"key":"R12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3226696","article-title":"A prototype for Mexican Sign Language recognition and synthesis in support of a primary care physician","volume":"10","author":"Sosa-Jim\u00e9nez","journal-title":"IEEE Access"},{"issue":"23","key":"R13","doi-asserted-by":"publisher","DOI":"10.3390\/s22239107","article-title":"A sign language recognition system applied to deaf-mute medical consultation","volume":"22","author":"Xia","journal-title":"Sensors (Basel)"},{"issue":"7","key":"R14","doi-asserted-by":"publisher","DOI":"10.3390\/s22072656","article-title":"Context-aware automatic sign language video transcription in psychiatric interviews","volume":"22","author":"Pikoulis","journal-title":"Sensors (Basel)"},{"issue":"7","key":"R15","doi-asserted-by":"publisher","first-page":"19767","DOI":"10.1007\/s11042-023-16332-7","article-title":"A multiple stream architecture for the recognition of signs in Brazilian sign language in the context of health","volume":"83","author":"da Silva","journal-title":"Multimed Tools Appl"},{"key":"R16","doi-asserted-by":"crossref","unstructured":"S Kumar S Wangyal T Saboo V Srinath R . Time series neural networks for real time sign language translation. Presented at: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA); Dec 17-20, 2018; Orlando, FL, United States. [doi: 10.1109\/ICMLA.2018.00043]","DOI":"10.1109\/ICMLA.2018.00043"},{"key":"R17","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2023.100504","article-title":"A survey on sign language literature","volume":"14","author":"Alaghband","journal-title":"Mach Learn Appl"},{"key":"R18","unstructured":"Sign language recognition system for deaf patients: a systematic review. Open Science Framework. 2023. URL: https:\/\/osf.io\/fpemr\/overview [Accessed 28-01-2026]"},{"issue":"1","key":"R19","doi-asserted-by":"publisher","DOI":"10.2196\/55427","article-title":"Sign language recognition system for deaf patients: protocol for a systematic review","volume":"14","author":"Marcolino","journal-title":"JMIR Res Protoc"},{"key":"R20","unstructured":"Higgins JPT . Cochrane Handbook for Systematic Reviews of Interventions Version 65 (Updated August 2024). Cochrane; 2024."},{"key":"R21","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.n71","article-title":"The PRISMA 2020 statement: an updated guideline for reporting systematic reviews","volume":"372","author":"Page","journal-title":"BMJ"},{"key":"R22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3142918","article-title":"Helping hearing-impaired in emergency situations: a deep learning-based approach","volume":"10","author":"Areeb","journal-title":"IEEE Access"},{"key":"R23","doi-asserted-by":"crossref","unstructured":"Areeb QM Nadeem M . Deep learning based hand gesture recognition for emergency situation: a study on Indian Sign Language. Presented at: 2021 International Conference on Data Analytics for Business and Industry (ICDABI); Oct 25-26, 2021; Sakheer, Bahrain. [doi: 10.1109\/ICDABI53623.2021.9655842]","DOI":"10.1109\/ICDABI53623.2021.9655842"},{"key":"R24","doi-asserted-by":"crossref","unstructured":"da Silva DRB Araujo TMU R\u00eago T do Brand\u00e3o MAC . A two-stream model based on 3D convolutional neural networks for the recognition of brazilian sign language in the health context. Presented at: WebMedia \u201920: Proceedings of the Brazilian Symposium on Multimedia and the Web; Nov 30 to Dec 4, 2020; S\u00e3o Lu\u00eds, Brazil. [doi: 10.1145\/3428658.3430980]","DOI":"10.1145\/3428658.3430980"},{"key":"R25","doi-asserted-by":"crossref","unstructured":"Das S Biswas SK Purkayastha B . Indian Sign Language recognition system for emergency words by using shape and deep features. Presented at: 2023 11th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks (IEMECON); Feb 10-11, 2023; Jaipur, India. [doi: 10.1109\/IEMECON56962.2023.10092312]","DOI":"10.1109\/IEMECON56962.2023.10092312"},{"issue":"13","key":"R26","doi-asserted-by":"publisher","first-page":"2683","DOI":"10.3390\/app9132683","article-title":"Neural sign language translation based on human keypoint estimation","volume":"9","author":"Ko","journal-title":"Appl Sci (Basel)"},{"key":"R27","doi-asserted-by":"crossref","unstructured":"Barrientos-Villalta GF Quiroz P Ugarte W . Peruvian Sign Language recognition using recurrent neural networks. Presented at: International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability; Sep 12-15, 2022; Santiago de Compostela, Spain. [doi: 10.1007\/978-3-031-20319-0_34]","DOI":"10.1007\/978-3-031-20319-0_34"},{"key":"R28","doi-asserted-by":"crossref","unstructured":"Ram\u00edrez S\u00e1nchez JE Rodr\u00edguez AA Mendoza MG . Real-time Mexican Sign Language interpretation using CNN and HMM. Presented at: Mexican International Conference on Artificial Intelligence; Oct 25-30, 2021; Mexico City, Mexico. [doi: 10.1007\/978-3-030-89817-5_4]","DOI":"10.1007\/978-3-030-89817-5_4"},{"issue":"7","key":"R29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42452-019-0771-2","article-title":"Supervised learning classifiers for Arabic gestures recognition using Kinect V2","volume":"1","author":"Hisham","journal-title":"SN Appl Sci"},{"key":"R30","doi-asserted-by":"crossref","unstructured":"Gandhi J Gandhi P Gosar A Chaudhari S . Video recognition techniques for Indian Sign Language in healthcare domain. Presented at: 2021 2nd International Conference for Emerging Technology (INCET); May 21-23, 2021; Belagavi, India. [doi: 10.1109\/INCET51464.2021.9456116]","DOI":"10.1109\/INCET51464.2021.9456116"},{"key":"R31","doi-asserted-by":"crossref","unstructured":"Uchil AP Jha S Sudha BG . Vision-based deep learning approach for dynamic Indian Sign Language recognition in healthcare. Presented at: Computational Vision and Bio-Inspired Computing: ICCVBIC 2019; Sep 25-26, 2019; Coimbatore, India. [doi: 10.1007\/978-3-030-37218-7_43]","DOI":"10.1007\/978-3-030-37218-7_43"},{"key":"R32","doi-asserted-by":"crossref","unstructured":"Deji Dere M Dere RO Adesina A Yauri AR . SmartCall: a real-time, sign language medical emergency communicator. Presented at: 2022 5th Information Technology for Education and Development (ITED); Nov 1-3, 2022; Abuja, Nigeria. [doi: 10.1109\/ITED56637.2022.10051420]","DOI":"10.1109\/ITED56637.2022.10051420"},{"key":"R33","doi-asserted-by":"crossref","unstructured":"Sarhan NA El-Sonbaty Y Youssef SM . HMM-based Arabic Sign Language recognition using Kinect. Presented at: 2015 Tenth International Conference on Digital Information Management (ICDIM); Dec 23-24, 2015; Jeju Island, South Korea. [doi: 10.1109\/ICDIM.2015.7381873]","DOI":"10.1109\/ICDIM.2015.7381873"},{"key":"R34","doi-asserted-by":"crossref","unstructured":"Guo Y Zhao J Ding B et al. Sign-to-911: emergency call service for sign language users with assistive AR glasses. Presented at: ACM MobiCom \u201923: Proceedings of the 29th Annual International Conference on Mobile Computing and Networking; Oct 2-5, 2023; Madrid, Spain. [doi: 10.1145\/3570361.3613260]","DOI":"10.1145\/3570361.3613260"},{"issue":"3","key":"R35","first-page":"75","volume":"11","author":"S\u00fczg\u00fcn","journal-title":"J Naval Sci Eng"},{"key":"R36","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2020.106016","article-title":"Hand gestures for emergency situations: a video dataset based on words from Indian Sign Language","volume":"31","author":"Adithya","journal-title":"Data Brief"},{"key":"R37","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3370684","article-title":"MediSign: an attention-based CNN-BiLSTM approach of classifying word level signs for patient-doctor interaction in hearing impaired community","volume":"12","author":"Ihsan","journal-title":"IEEE Access"},{"issue":"5","key":"R38","doi-asserted-by":"publisher","first-page":"13543","DOI":"10.1007\/s11042-023-15214-2","article-title":"Transforming consulting atmosphere with Indian Sign Language translation","volume":"83","author":"Das","journal-title":"Multimed Tools Appl"},{"key":"R39","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3337514","article-title":"Enabling two-way communication of deaf using Saudi Sign Language","volume":"11","author":"Faisal","journal-title":"IEEE Access"},{"issue":"4","key":"R40","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1007\/s10209-019-00695-6","article-title":"A machine translation system from Arabic Sign Language to Arabic","volume":"19","author":"Luqman","journal-title":"Univ Access Inf Soc"},{"key":"R41","doi-asserted-by":"crossref","unstructured":"Dewasurendra D Kumar A Perera I Jayasena D Thelijjagoda S . Emergency communication application for speech and hearing-impaired citizens. Presented at: 2020 From Innovation to Impact (FITI); Dec 15-15, 2020; Colombo, Sri Lanka. [doi: 10.1109\/FITI52050.2020.9424899]","DOI":"10.1109\/FITI52050.2020.9424899"},{"key":"R42","doi-asserted-by":"crossref","unstructured":"Bellil L Ghiri MG Boulesnane A . Empowering deaf community in healthcare communication: 1D-CNN-based Algerian Sign Language recognition system. Presented at: 2024 6th International Conference on Pattern Analysis and Intelligent Systems (PAIS); Apr 24-25, 2024; El Oued, Algeria. [doi: 10.1109\/PAIS62114.2024.10541233]","DOI":"10.1109\/PAIS62114.2024.10541233"},{"key":"R43","unstructured":"Vosk: speech recognition toolkit. Alphacephei. URL: https:\/\/alphacephei.com\/vosk\/ [Accessed 24-03-2026]"},{"key":"R44","unstructured":"Arabic language disambiguation for natural language processing applications. Columbia University. URL: https:\/\/inventions.techventures.columbia.edu\/technologies\/arabic-language-disambiguation--cu14012 [Accessed 24-03-2026]"},{"key":"R45","doi-asserted-by":"crossref","unstructured":"Shotton J Fitzgibbon A Cook M et al. Real-time human pose recognition in parts from single depth images. Presented at: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR); Jun 20-25, 2011; Colorado Springs, CO, United States. [doi: 10.1109\/CVPR.2011.5995316]","DOI":"10.1109\/CVPR.2011.5995316"},{"issue":"1","key":"R46","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1007\/s11042-010-0529-8","article-title":"Improving multimodal web accessibility for deaf people: sign language interpreter module","volume":"54","author":"Debevc","journal-title":"Multimed Tools Appl"},{"key":"R47","unstructured":"Madhiarasan M Roy PP . A comprehensive review of sign language recognition: different types, modalities, and datasets. arXiv. Preprint posted online on Apr 7, 2022. [doi: 10.48550\/arXiv.2204.03328]"},{"issue":"13","key":"R48","doi-asserted-by":"publisher","first-page":"7433","DOI":"10.3390\/app13137433","article-title":"Vision-based hand detection and tracking using fusion of kernelized correlation filter and single-shot detection","volume":"13","author":"Haji Mohd","journal-title":"Appl Sci (Basel)"},{"key":"R49","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3110912","article-title":"Deep learning for sign language recognition: current techniques, benchmarks, and open issues","volume":"9","author":"Al-Qurishi","journal-title":"IEEE Access"},{"issue":"3","key":"R50","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1109\/TPAMI.2009.26","article-title":"Handling movement epenthesis and hand segmentation ambiguities in continuous sign language recognition using nested dynamic programming","volume":"32","author":"Yang","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"R51","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging8040098","article-title":"A comparative review on applications of different sensors for sign language recognition","volume":"8","author":"Amin","journal-title":"J Imaging"},{"issue":"2","key":"R52","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1080\/15398285.2023.2204717","article-title":"Deafness and other communication disorders","volume":"27","author":"Figg","journal-title":"J Consum Health Internet"},{"issue":"5","key":"R53","doi-asserted-by":"publisher","first-page":"10","DOI":"10.20431\/2347-3134.1005002","article-title":"Significance of globalisation and English language","volume":"10","author":"Bihari Dash","journal-title":"Int J Stud Engl Lang Lit"},{"key":"R54","doi-asserted-by":"crossref","unstructured":"Nye B Jessy Li J Patel R et al. A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature. Presented at: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers); Jul 15-20, 2018; Melbourne, Australia. [doi: 10.18653\/v1\/P18-1019]","DOI":"10.18653\/v1\/P18-1019"},{"key":"R55","doi-asserted-by":"crossref","unstructured":"Zheng L Liang B Jiang A . Recent advances of deep learning for sign language recognition. Presented at: 2017 International Conference on Digital Image Computing; Nov 29 to Dec 1, 2017; Sydney, NSW. [doi: 10.1109\/DICTA.2017.8227483]","DOI":"10.1109\/DICTA.2017.8227483"},{"issue":"14","key":"R56","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph18147259","article-title":"Psychosocial impact of assistive devices and other technologies on deaf and hard of hearing people","volume":"18","author":"Jim\u00e9nez-Arberas","journal-title":"Int J Environ Res Public Health"},{"key":"R57","doi-asserted-by":"publisher","DOI":"10.1016\/j.iswa.2021.200056","article-title":"Machine learning methods for sign language recognition: a critical review and analysis","volume":"12","author":"Adeyanju","journal-title":"Intell Syst Appl"},{"key":"R58","unstructured":"Ergonomics of human-system interaction: Part 210: Human-centered design for interactive systems. International Organization for Standardization. URL: https:\/\/www.iso.org\/obp\/ui\/#iso:std:iso:9241:-210:ed-1:v1:en [Accessed 13-04-2025]"},{"key":"R59","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3219430","article-title":"A systematic review on systems-based sensory gloves for sign language pattern recognition: an update from 2017 to 2022","volume":"10","author":"Saeed","journal-title":"IEEE Access"},{"issue":"4","key":"R60","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1007\/s10209-014-0354-3","article-title":"Enhancing universal access: deaf and hard of hearing people on social networking sites","volume":"14","author":"Ko\u017euh","journal-title":"Univ Access Inf Soc"},{"issue":"1","key":"R61","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/IJSSCI.311448","article-title":"Sign language translation systems","volume":"14","author":"Boggaram","journal-title":"Int J Softw Sci Comput Intell"},{"issue":"6","key":"R62","doi-asserted-by":"publisher","first-page":"1789","DOI":"10.1007\/s40031-024-01118-8","article-title":"Techniques for generating sign language a comprehensive review","volume":"105","author":"Waghmare","journal-title":"J Inst Eng India Ser B"},{"issue":"4","key":"R63","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1515\/applirev-2020-0144","article-title":"Accent or not? Language attitudes towards regional variation in British Sign Language","volume":"14","author":"Rowley","journal-title":"Appl Linguist Rev"},{"key":"R64","unstructured":"Preece J Rogers Y Sharp H . Interaction Design: Beyond Human-Computer Interaction. 6th ed. John Wiley & Sons; 2023. ISBN: 978-1-119-90109-9"}],"container-title":["Journal of Medical Internet Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jmir.org\/2026\/1\/e70417","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T17:59:07Z","timestamp":1782842347000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jmir.org\/2026\/1\/e70417"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,9]]},"references-count":64,"URL":"https:\/\/doi.org\/10.2196\/70417","relation":{},"ISSN":["1438-8871"],"issn-type":[{"value":"1438-8871","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,9]]},"article-number":"v28i4e70417"}}