Multimodal mental state analysis

Abbaschian, B.J., Sierra-Sosa, D., Elmaghraby, A.: Deep learning techniques for speech emotion recognition, from databases to models. Sensors 21(4), 1249 (2021). https://doi.org/10.3390/s21041249

Article  PubMed  PubMed Central  Google Scholar 

Alanazi, S.A., et al.: Public’s mental health monitoring via sentimental analysis of financial text using machine learning techniques. Int. J. Environ. Res.s Public Health 19, 15 (2022). https://doi.org/10.3390/ijerph19159695

Article  Google Scholar 

Babu, N.V., Kanaga, E.G.: Sentiment analysis in social media data for depression detection using artificial intelligence: a review. SN Comput. Sci. 3(1), 74 (2022). https://doi.org/10.1007/s42979-021-00958-1

Article  PubMed  Google Scholar 

Bota, P.J., Wang, C., Fred, A.L., Da Silva, H.P.: A review, current challenges, and future possibilities on emotion recognition using machine learning and physiological signals. IEEE Access 26(7), 140990–141020 (2019)

Article  Google Scholar 

Campbell, F., Blank, L., Cantrell, A., Baxter, S., Blackmore, C., Dixon, J., Goyder, E.: Factors that influence mental health of university and college students in the UK: a systematic review. BMC Public Health 22(1), 1778 (2022). https://doi.org/10.1186/s12889-022-13943-x

Article  PubMed  PubMed Central  Google Scholar 

Chung, J., Teo, J.: Mental Health prediction using machine learning: taxonomy, applications, and challenges. Appl. Comput. Intell. Soft Comput. 5(2022), 1–9 (2022). https://doi.org/10.1155/2022/9970363

Article  Google Scholar 

Ehiabhi, J., Wang, H.: A systematic review of machine learning models in mental health analysis based on multi-channel multi-modal biometric signals. BioMedInformatics 3(1), 193–219 (2023). https://doi.org/10.3390/biomedinformatics3010014

Article  Google Scholar 

Garcia-Ceja, E., Riegler, M., Nordgreen, T., Jakobsen, P., Oedegaard, K.J., Tørresen, J.: Mental health monitoring with multimodal sensing and machine learning: a survey. Pervasive Mobile Comput. 1(51), 1–26 (2018). https://doi.org/10.1016/j.pmcj.2018.09.003

Article  Google Scholar 

Hernández-Torrano, D., Ibrayeva, L., Sparks, J., Lim, N., Clementi, A., Almukhambetova, A., Nurtayev, Y., Muratkyzy, A.: Mental health and well-being of university students: a bibliometric mapping of the literature. Front. Psychol. 9(11), 540000 (2020). https://doi.org/10.3389/fpsyg.2020.01226

Article  Google Scholar 

Kazemitabar, M., Lajoie, S.P., Doleck, T.: Analysis of emotion regulation using posture, voice, and attention: a qualitative case study. Comput. Education Open 2, 100030 (2021). https://doi.org/10.1016/j.caeo.2021.100030

Article  Google Scholar 

Khalil, R.A., Jones, E., Babar, M.I., Jan, T., Zafar, M.H., Alhussain, T.: Speech emotion recognition using deep learning techniques: a review. IEEE Access 7, 117327–117345 (2019). https://doi.org/10.1109/ACCESS.2019.2936124

Article  Google Scholar 

Lin, L., Chen, X., Shen, Y., Zhang, L.: Towards automatic depression detection: a bilstm/1d cnn-based model. Appl. Sci. (switzerland) 10(23), 1–20 (2020). https://doi.org/10.3390/app10238701

Article  CAS  Google Scholar 

Nandwani, P., Verma, R.: A review on sentiment analysis and emotion detection from text. Soc. Netw. Anal. Mining 11(1), 81 (2021). https://doi.org/10.1007/s13278-021-00776-6

Article  Google Scholar 

Rahman, R.A., Omar, K., Noah, S.A.M., Danuri, M.S.N.M., Al-Garadi, M.A.: Application of machine learning methods in mental health detection: a systematic review. IEEE Access 8, 183952–183964 (2020). https://doi.org/10.1109/ACCESS.2020.3029154

Article  Google Scholar 

Rai, B.K.: BBTCD: blockchain based traceability of counterfeited drugs. Health Serv Outcomes Res Methodol 23(3), 337–353 (2023)

Article  Google Scholar 

Rai, B.K., Fatima, S., Satyarth, K.: Patient-centric multichain healthcare record. Int. J.E-Health Med. Commun. (IJEHMC) 13(4), 1–4 (2022). https://doi.org/10.4018/IJEHMC.309439

Article  CAS  Google Scholar 

Rai, B. K., Kumar, G., and Balyan, V. Eds., “AI and Blockchain in Healthcare,” 2023, doi: https://doi.org/10.1007/978-981-99-0377-1.

Shatte, A.B., Hutchinson, D.M., Teague, S.J.: Machine learning in mental health: a scoping review of methods and applications. Psychol. Med. 49(9), 1426–1448 (2019)

Article  PubMed  Google Scholar 

Tavabi, L.: “Multimodal machine learning for interactive mental health therapy,” In: ICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction, Association for Computing Machinery, Inc, Oct. 2019, pp. 453–456. doi: https://doi.org/10.1145/3340555.3356095.

Thieme, A., Belgrave, D., Doherty, G.: Machine learning in mental health: a systematic review of the HCI literature to support the development of effective and implementable ML systems. ACM Transact. Comput.-Human Interact. (TOCHI) 27(5), 1–53 (2020)

Article  Google Scholar 

Xie, W.  et al., “Interpreting Depression from Question-wise Long-term Video Recording of SDS Evaluation,” Jun. 2021. http://arxiv.org/abs/2106.13393

留言 (0)

沒有登入
gif