In today’s fast-paced society, loneliness, stress, and depression are prevalent issues, particularly among young adults. Despite their prevalence, individuals often refrain from seeking help due to stigma, lack of awareness, and financial constraints. This research aims to address these challenges by exploring the potential of technology, specifically humanoid companions, to revolutionise mental health interventions. Through interviews, surveys, journey map-ping, task analysis, and prototyping, the study aims to develop user-centred solutions tailored to the target audience’s needs. By gathering insights from qualitative and quantitative data, the research identifies key challenges and opportunities in mental health support. The proposed solutions leverage advanced emotional recognition and user-friendly interfaces to provide accessible, personalised, and empathetic mental health support. Through iterative design and usability testing, the research refines these solutions to enhance user engagement and well-being. Future directions include expanding research methodologies, tailoring solutions to cultural differences, and prioritising accessibility to advance mental health care. By emphasising technology’s role in addressing mental health challenges, the research contributes to promoting holistic well-being in society.

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AI Companion: Revolutionising Mental Well-Being Through Conversational UX

  • N. P. Soundarya,
  • Sura Bhoomika,
  • Vaishali Ashok,
  • Harshit Kumar Gupta

摘要

In today’s fast-paced society, loneliness, stress, and depression are prevalent issues, particularly among young adults. Despite their prevalence, individuals often refrain from seeking help due to stigma, lack of awareness, and financial constraints. This research aims to address these challenges by exploring the potential of technology, specifically humanoid companions, to revolutionise mental health interventions. Through interviews, surveys, journey map-ping, task analysis, and prototyping, the study aims to develop user-centred solutions tailored to the target audience’s needs. By gathering insights from qualitative and quantitative data, the research identifies key challenges and opportunities in mental health support. The proposed solutions leverage advanced emotional recognition and user-friendly interfaces to provide accessible, personalised, and empathetic mental health support. Through iterative design and usability testing, the research refines these solutions to enhance user engagement and well-being. Future directions include expanding research methodologies, tailoring solutions to cultural differences, and prioritising accessibility to advance mental health care. By emphasising technology’s role in addressing mental health challenges, the research contributes to promoting holistic well-being in society.