| dc.description.abstract | Depression is a common mental health issue that
affects many people, often making them feel persistently sad
or lose interest in activities. Despite its global impact, with
246 million people affected worldwide, access to professional
help remains limited due to cost, stigma, and accessibility
issues. Existing mobile personal chatbots primarily offer
generic responses without personalized context, lacking deep
personalization that adapts to user history, preferences, and
specific mental health needs, thereby reducing their
effectiveness. Additionally, they have limited integration with
established mental health tools, inadequate emotion
recognition through multimodal inputs, insufficient
mechanisms for long-term engagement, and often lack robust
privacy and security measures, compromising user trust and
reliability in tracking and assessing mental health conditions.
This review explores how AI-powered chatbots, especially
those integrated with emotion recognition, might offer
personalized and empathetic support to people dealing with
depression. The study explores the effectiveness, feasibility,
and ethical considerations of implementing AI in mental
health applications, aiming to fill gaps in current care
methods and enhance patient support and engagement.
Future work will focus on refining the system, expanding its
capabilities, and ensuring it meets diverse user needs while
adhering to ethical considerations and data privacy. | en_US |
