Autonomous driving paper index
AI-Enabled Musical Communication Therapy: Enhancing Overall Well-Being of Patients in Select Hospitals in Akwa Ibom
One-line summary
Artificial intelligence (AI)-enabled music therapy offers emerging possibilities for enhancing patient well-being through personalized musical communication; however, its application within Nigerian healthcare settings remains insufficiently examined.
Engineering notes
Key topics: autonomous driving, perception. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Artificial intelligence (AI)-enabled music therapy offers emerging possibilities for enhancing patient well-being through personalized musical communication; however, its application within Nigerian healthcare settings remains insufficiently examined. This study investigates the effectiveness of AI-enhanced music therapy programmes in promoting patients’ general well-being, assesses the influence of musical communication on patients’ emotional well-being during treatment, and explores how AI-based technologies can personalize music therapy according to individual patient needs in selected hospitals in Akwa Ibom State, Nigeria. A mixed-methods research design was employed with 120 patients recruited through convenience sampling from hospitals purposively selected across the state’s three senatorial districts, with an average of two hospitals representing each district. Participants completed a three-week AI-enabled music therapy programme, and their well-being was assessed before and after the intervention. Qualitative data were also collected to examine participants’ experiences and perceptions of the therapy and were integrated with the well-being assessments during analysis. The findings indicate that AI-enabled music therapy, facilitated through musical communication, has the potential to improve patients’ general and emotional well-being and support the personalization of therapeutic programmes. Nevertheless, its implementation presents challenges related to privacy, data protection, and cultural sensitivity. The study concludes that AI-enabled music therapy represents a promising complementary approach to patient care, provided that its implementation is supported by continuous evaluation, responsible data-governance practices, cultural responsiveness, and multidisciplinary collaboration among relevant healthcare, technological, and creative-sector stakeholders.
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