Improving Mental Health Diagnosis in mHealth Systems Using Facial and Text-Based Sentiment Analysis

Authors

  • Prof. Robert Johnson Author

Abstract

 This study introduces a machine learning framework for improving mental health diagnosis in mHealth systems using facial emotion recognition and text-based sentiment analysis. The system enhances the accuracy of emotional health assessments by integrating visual and textual data sources.

Downloads

Download data is not yet available.

References

Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161-1178. https://doi.org/10.1037/h0077714

Scherer, K. R., Bänziger, T., & Roesch, E. B. (2010). A blueprint for affective computing: A sourcebook and manual. Oxford University Press.

Shen, L., Wang, M., & Shen, Y. (2011). Sentiment classification of online reviews to travel destinations by supervised machine learning approaches. Expert Systems with Applications, 38(10), 14059-14065. https://doi.org/10.1016/j.eswa.2011.04.066

Tkalčič, M., De Carolis, B., De Gemmis, M., Odić, A., & Košir, A. (2016). Emotions and personality in personalized services. Springer.

Wöllmer, M., Eyben, F., Schuller, B., & Rigoll, G. (2010). A multi-modal LSTM–MRF model for robust facial expression recognition. 2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3642-3645. https://doi.org/10.1109/ICASSP.2010.5495407

Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009). A survey of affect recognition methods: Audio, visual, and spontaneous expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(1), 39-58. https://doi.org/10.1109/TPAMI.2008.52

Pillai, S. E. V. S., & Hu, W. C. (2023, May). Misinformation detection using an ensemble method with emphasis on sentiment and emotional analyses. In 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA) (pp. 295-300). IEEE.

Kalla, D., Smith, N., Samaah, F., & Polimetla, K. (2022). Enhancing Early Diagnosis: Machine Learning Applications in Diabetes Prediction. Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-205. DOI: doi. org/10.47363/JAICC/2022 (1), 191, 2-7.

Published

2023-10-13

Issue

Section

Articles

How to Cite

Improving Mental Health Diagnosis in mHealth Systems Using Facial and Text-Based Sentiment Analysis. (2023). International Numeric Journal of Machine Learning and Robots, 7(7). https://injmr.com/index.php/fewfewf/article/view/123