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MindCare - AI Based Mental Wellness Voice Based Companion

Author

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  • Rohan Tirkhunde

    (Department of Computer Engineering, K J College of Engineering & Management Research Pune, India)

  • Vaishnavi Patole

    (Department of Computer Engineering, K J College of Engineering & Management Research Pune, India)

  • Sneha Yamgar

    (Department of Computer Engineering, K J College of Engineering & Management Research Pune, India)

  • Nayana S. Thombare

    (Department of Computer Engineering, K J College of Engineering & Management Research Pune, India)

  • Nikita Shinde

    (Department of Computer Engineering, K J College of Engineering & Management Research Pune, India)

Abstract

Mental health disorders such as stress, anxiety, and depression are increasing rapidly across all age groups. Many individuals do not receive timely support due to limited access to professional mental healthcare services. Artificial intelligence–based voice assistants provide a new opportunity to offer emotional support and continuous mental health monitoring. This paper surveys voice-based artificial intelligence mental health companions integrated with emotion tracking systems. The study reviews existing technologies, emotion detection techniques, system architectures, and practical applications. It also discusses major challenges including privacy, ethical responsibility, and emotional accuracy. The survey highlights that combining voice interaction with emotion tracking can significantly improve accessibility and user engagement in mental healthcare systems. This paper aims to provide a comprehensive overview for researchers and developers working in the field of intelligent mental health support systems.

Suggested Citation

  • Rohan Tirkhunde & Vaishnavi Patole & Sneha Yamgar & Nayana S. Thombare & Nikita Shinde, 2026. "MindCare - AI Based Mental Wellness Voice Based Companion," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(6), pages 462-467, July.
    • Handle: RePEc:bjf:ijltem:v:15:y:2026:i:6:a:35
    DOI: 10.51583/IJLTEMAS.2026.150600035
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