A Human Trial Study on Overcoming Linguistic and Stress-Related Barriers in Chronic Disease Management

The study addresses language and stress barriers in chronic disease management among Sinhala-speaking patients, using an Augmented Reality (AR) embedded platform combined with an Artificial Intelligence (AI) chatbot. Rasa is integrated into the AI chatbot using Bidirectional Encoder Representations from Transformer (BERT)-Sinhala embeddings to deliver culturally tailored, real-time health recommendations. An AR module on AR.js and Three.js implements personalized stress-reduction interventions. The chatbot achieves an F1 score of 91% and a word error rate (WER) of 8.5%, while the AR system reduces systolic blood pressure by 8.96% (p = 0.002). The combined platform attains 88% scenario accuracy with a mean response time of 1.2 seconds. These findings support the system’s potential to improve healthcare access and reduce stress markers among Sinhala-speaking chronic patients, offering a low-resource, scalable, and culturally appropriate model for healthcare environments.