International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Mental Health Detection Using NLP from Journal Entries |
|---|---|
| ABSTRACT | This paper presents Mental Health Detection using NLP from Journal Entries, a web-based system designed for real-time emotion and mental health analysis. The platform processes user- provided journal text and voice inputs through voice-to-text transcription and applies Natural Language Processing (NLP) techniques for analysis. The system follows a rule-based approach that combines keyword detection and basic text processing to identify emotional patterns. It classifies various emotional states and detects key mental health indicators such as stress, anxiety, and depression. The system also integrates user authentication and secure data handling to ensure privacy and reliability. The processed results are presented through an interactive interface, allowing users to understand their emotional state effectively. The system demonstrates efficient performance in analyzing textual data and identifying emotional trends with consistent accuracy based on predefined rules. This approach makes the system lightweight, fast, and easy to implement without requiring complex machine learning models. The proposed system can be used as a supportive tool for mental health awareness, enabling early identification of emotional changes and encouraging timely intervention. However, it is intended only as an assistive system and not as a replacement for professional medical diagnosis. |
| AUTHOR | A.VAMSI KIRAN, G.V.S.BHARGAV, V.ARUN KUMAR, K.HEMANTH, S.HEMANTH, Y. VEERABABU Students, Department of CSE (AI&ML), NSRIT, Visakhapatnam, India Asst. Professor, Department of CSE (AI&ML), NSRIT, Visakhapatnam, India |
| VOLUME | 182 |
| DOI | DOI: 10.15680/IJIRCCE. 2026.1403103 |
| pdf/103_Mental Health Detection Using NLP from Journal Entries.pdf | |
| KEYWORDS | |
| References | [1] A. A. Favour, “Real-Time Emotion Detection from Speech Using NLP and Acoustic Signal Processing,” ResearchGate, Federal University of Technology, May 2025. [2] “Emotional Detection from Text Using NLP with Prediction Probability,” ResearchGate, 2024. [3] “Application of NLP and Machine Learning for Mental Health Detection,” Zenodo, 2022. [4] “MoodyAI: Text-Based Mood Detection Using NLP and LSTM,” ScienceDirect, 2025. [5] “Emotion Fusion for Mental Illness Detection from Social Media,” ScienceDirect, 2023. [6] “A Review on Emotion Detection Using Deep Learning Techniques,” Springer, 2024. [7] “Attention-Based Fully Convolutional Network for Speech Emotion Recognition,” arXiv, Jun. 2018. [8] “AVEC 2019: Detecting Depression with AI and Affect Recognition,” arXiv, Jul. 2019. [9] “Towards Robust Deep Neural Networks for Affect and Depression Recognition,” arXiv, Nov. 2019. [10] “Emotion Recognition in Conversation: Research Challenges and Advances,” IEEE Xplore, 2019. |
