{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T14:14:08Z","timestamp":1780496048242,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,10,5]],"date-time":"2024-10-05T00:00:00Z","timestamp":1728086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,10,5]]},"DOI":"10.1145\/3675094.3678494","type":"proceedings-article","created":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:31:48Z","timestamp":1726965108000},"page":"412-417","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":26,"title":["Exploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1315-8969","authenticated-orcid":false,"given":"Yongquan","family":"Hu","sequence":"first","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4145-117X","authenticated-orcid":false,"given":"Shuning","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3806-1493","authenticated-orcid":false,"given":"Ting","family":"Dang","sequence":"additional","affiliation":[{"name":"University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6047-4158","authenticated-orcid":false,"given":"Hong","family":"Jia","sequence":"additional","affiliation":[{"name":"University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1237-1664","authenticated-orcid":false,"given":"Flora D.","family":"Salim","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4076-1811","authenticated-orcid":false,"given":"Wen","family":"Hu","sequence":"additional","affiliation":[{"name":"UNSW, Syndey, New South Wales, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5274-6889","authenticated-orcid":false,"given":"Aaron J.","family":"Quigley","sequence":"additional","affiliation":[{"name":"CSIRO's Data61, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,10,5]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3029154"},{"key":"e_1_3_2_1_2_1","volume-title":"Proceedings of demo session of the 3rd international workshop on smart appliances, ICDCS03","author":"Arshad Usman","year":"2003","unstructured":"Usman Arshad, Cecilia Mascolo, and Marcus Mellor. 2003. Exploiting mobile computing in health-care. In Proceedings of demo session of the 3rd international workshop on smart appliances, ICDCS03. Citeseer."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3534642"},{"key":"e_1_3_2_1_4_1","volume-title":"Irene Maga na, and Rodrigo Rojas","author":"Cabrera Johana","year":"2023","unstructured":"Johana Cabrera, M Soledad Loyola, Irene Maga na, and Rodrigo Rojas. 2023. Ethical dilemmas, mental health, artificial intelligence, and llm-based chatbots. In International Work-Conference on Bioinformatics and Biomedical Engineering. Springer, 313--326."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-022-01211-x"},{"key":"e_1_3_2_1_6_1","volume-title":"30th USENIX Security Symposium (USENIX Security 21)","author":"Carlini Nicholas","year":"2021","unstructured":"Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al. 2021. Extracting training data from large language models. In 30th USENIX Security Symposium (USENIX Security 21). 2633--2650."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3146729"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/S2215-0366(16)30024-4"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3023871"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1098\/rsos.230806"},{"key":"e_1_3_2_1_11_1","volume-title":"Critiquing Self-report Practices for Human Mental and Wellbeing Computing at Ubicomp. arXiv preprint arXiv:2311.15496","author":"Gao Nan","year":"2023","unstructured":"Nan Gao, Soundariya Ananthan, Chun Yu, Yuntao Wang, and Flora D Salim. 2023. Critiquing Self-report Practices for Human Mental and Wellbeing Computing at Ubicomp. arXiv preprint arXiv:2311.15496 (2023)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/PuneCon46936.2019.9105749"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2021.612750"},{"key":"e_1_3_2_1_14_1","volume-title":"Advances in Electrodermal activity processing with applications for mental health","author":"Greco Alberto","unstructured":"Alberto Greco, Gaetano Valenza, and Enzo Pasquale Scilingo. 2016. Advances in Electrodermal activity processing with applications for mental health. Springer."},{"key":"e_1_3_2_1_15_1","volume-title":"A wearable EEG-HEG-HRV multimodal system with simultaneous monitoring of tES for mental health management","author":"Ha Unsoo","year":"2015","unstructured":"Unsoo Ha, Yongsu Lee, Hyunki Kim, Taehwan Roh, Joonsung Bae, Changhyeon Kim, and Hoi-Jun Yoo. 2015. A wearable EEG-HEG-HRV multimodal system with simultaneous monitoring of tES for mental health management. IEEE transactions on biomedical circuits and systems, Vol. 9, 6 (2015), 758--766."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21103461"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2015.540"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581641.3584069"},{"key":"e_1_3_2_1_19_1","first-page":"1","article-title":"Microcam: Leveraging smartphone microscope camera for context-aware contact surface sensing","volume":"7","author":"Hu Yongquan","year":"2023","unstructured":"Yongquan Hu, Hui-Shyong Yeo, Mingyue Yuan, Haoran Fan, Don Samitha Elvitigala, Wen Hu, and Aaron Quigley. 2023. Microcam: Leveraging smartphone microscope camera for context-aware contact surface sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 7, 3 (2023), 1--28.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_1_20_1","volume-title":"Twelve tips to leverage AI for efficient and effective medical question generation: a guide for educators using Chat GPT. Medical Teacher","author":"Indran Inthrani Raja","year":"2024","unstructured":"Inthrani Raja Indran, Priya Paranthaman, Neelima Gupta, and Nurulhuda Mustafa. 2024. Twelve tips to leverage AI for efficient and effective medical question generation: a guide for educators using Chat GPT. Medical Teacher (2024), 1--6."},{"key":"e_1_3_2_1_21_1","volume-title":"EEG-GPT: Exploring Capabilities of Large Language Models for EEG Classification and Interpretation. arXiv preprint arXiv:2401.18006","author":"Kim Jonathan W","year":"2024","unstructured":"Jonathan W Kim, Ahmed Alaa, and Danilo Bernardo. 2024. EEG-GPT: Exploring Capabilities of Large Language Models for EEG Classification and Interpretation. arXiv preprint arXiv:2401.18006 (2024)."},{"key":"e_1_3_2_1_22_1","volume-title":"The benefits, risks and bounds of personalizing the alignment of large language models to individuals. Nature Machine Intelligence","author":"Kirk Hannah Rose","year":"2024","unstructured":"Hannah Rose Kirk, Bertie Vidgen, Paul R\u00f6ttger, and Scott A Hale. 2024. The benefits, risks and bounds of personalizing the alignment of large language models to individuals. Nature Machine Intelligence (2024), 1--10."},{"key":"e_1_3_2_1_23_1","volume-title":"Psy-llm: Scaling up global mental health psychological services with ai-based large language models. arXiv preprint arXiv:2307.11991","author":"Lai Tin","year":"2023","unstructured":"Tin Lai, Yukun Shi, Zicong Du, Jiajie Wu, Ken Fu, Yichao Dou, and Ziqi Wang. 2023. Psy-llm: Scaling up global mental health psychological services with ai-based large language models. arXiv preprint arXiv:2307.11991 (2023)."},{"key":"e_1_3_2_1_24_1","volume-title":"Evaluation of chatgpt for nlp-based mental health applications. arXiv preprint arXiv:2303.15727","author":"Lamichhane Bishal","year":"2023","unstructured":"Bishal Lamichhane. 2023. Evaluation of chatgpt for nlp-based mental health applications. arXiv preprint arXiv:2303.15727 (2023)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642068"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9533663"},{"key":"e_1_3_2_1_27_1","volume-title":"A multi-modal extraction integrated model for neuropsychiatric disorders classification. Pattern Recognition","author":"Liu Liangliang","year":"2024","unstructured":"Liangliang Liu, Zhihong Liu, Jing Chang, and Xue Xu. 2024. A multi-modal extraction integrated model for neuropsychiatric disorders classification. Pattern Recognition (2024), 110646."},{"key":"e_1_3_2_1_28_1","volume-title":"Automated assessment of psychiatric disorders using speech: A systematic review. Laryngoscope investigative otolaryngology","author":"Low Daniel M","year":"2020","unstructured":"Daniel M Low, Kate H Bentley, and Satrajit S Ghosh. 2020. Automated assessment of psychiatric disorders using speech: A systematic review. Laryngoscope investigative otolaryngology, Vol. 5, 1 (2020), 96--116."},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies","volume":"6","author":"Meegahapola Lakmal","year":"2023","unstructured":"Lakmal Meegahapola, William Droz, Peter Kun, Amalia De G\u00f6tzen, Chaitanya Nutakki, Shyam Diwakar, Salvador Ruiz Correa, Donglei Song, Hao Xu, Miriam Bidoglia, et al. 2023. Generalization and personalization of mobile sensing-based mood inference models: an analysis of college students in eight countries. Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, Vol. 6, 4 (2023), 1--32."},{"key":"e_1_3_2_1_30_1","unstructured":"OpenAI. 2024. Hello GPT-4o. https:\/\/openai.com\/index\/hello-gpt-4o\/ [Accessed:June 2024]."},{"key":"e_1_3_2_1_31_1","unstructured":"World Health Organization et al. 2022. World mental health report: Transforming mental health for all. (2022)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2021.12.010"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3575792"},{"key":"e_1_3_2_1_34_1","volume-title":"Working with environmental noise and noise-cancelation: a workload assessment with EEG and subjective measures. Frontiers in neuroscience","author":"Pieper Kerstin","year":"2021","unstructured":"Kerstin Pieper, Robert P Spang, Pablo Prietz, Sebastian M\u00f6ller, Erkki Paajanen, Markus Vaalgamaa, and Jan-Niklas Voigt-Antons. 2021. Working with environmental noise and noise-cancelation: a workload assessment with EEG and subjective measures. Frontiers in neuroscience, Vol. 15 (2021), 771533."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3329189.3329213"},{"key":"e_1_3_2_1_36_1","volume-title":"ICLR 2024 Workshop on Reliable and Responsible Foundation Models.","author":"Staab Robin","year":"2024","unstructured":"Robin Staab, Mark Vero, Mislav Balunovic, and Martin Vechev. 2024. Large Language Models are Anonymizers. In ICLR 2024 Workshop on Reliable and Responsible Foundation Models."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41398-020-0780-3"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.3390\/s21144764"},{"key":"e_1_3_2_1_39_1","volume-title":"Timothy R McIntosh, and Surangika Ranathunga.","author":"Susnjak Teo","year":"2024","unstructured":"Teo Susnjak, Peter Hwang, Napoleon H Reyes, Andre LC Barczak, Timothy R McIntosh, and Surangika Ranathunga. 2024. Automating research synthesis with domain-specific large language model fine-tuning. arXiv preprint arXiv:2404.08680 (2024)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3610916"},{"key":"e_1_3_2_1_41_1","volume-title":"Denny Zhou, et al.","author":"Wei Jason","year":"2022","unstructured":"Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022. Chain-of-thought prompting elicits reasoning in large language models. Advances in neural information processing systems, Vol. 35 (2022), 24824--24837."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3613904.3642790"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3569485"},{"key":"e_1_3_2_1_44_1","first-page":"1","article-title":"Mental-llm: Leveraging large language models for mental health prediction via online text data","volume":"8","author":"Xu Xuhai","year":"2024","unstructured":"Xuhai Xu, Bingsheng Yao, Yuanzhe Dong, Saadia Gabriel, Hong Yu, James Hendler, Marzyeh Ghassemi, Anind K Dey, and Dakuo Wang. 2024. Mental-llm: Leveraging large language models for mental health prediction via online text data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 8, 1 (2024), 1--32.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_3_2_1_45_1","volume-title":"Promptcast: A new prompt-based learning paradigm for time series forecasting","author":"Xue Hao","year":"2023","unstructured":"Hao Xue and Flora D Salim. 2023. Promptcast: A new prompt-based learning paradigm for time series forecasting. IEEE Transactions on Knowledge and Data Engineering (2023)."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/S2589-7500(23)00225-X"}],"event":{"name":"UbiComp '24: The 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing","location":"Melbourne VIC Australia","acronym":"UbiComp '24","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGSPATIAL ACM Special Interest Group on Spatial Information"]},"container-title":["Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3675094.3678494","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3675094.3678494","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:10:14Z","timestamp":1755839414000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3675094.3678494"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,5]]},"references-count":46,"alternative-id":["10.1145\/3675094.3678494","10.1145\/3675094"],"URL":"https:\/\/doi.org\/10.1145\/3675094.3678494","relation":{},"subject":[],"published":{"date-parts":[[2024,10,5]]},"assertion":[{"value":"2024-10-05","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}