Driven gamification by AI in a time series healthcare case study: Statistical intervention analysis

Abstract

With artificial intelligence (AI), gamification has emerged as a promising strategy for improving patient engagement and rehabilitation outcomes. This study investigates the impact of AI models. (GRU, TCN, and ARIMA models ) Driven gamification on stroke rehabilitation by analyzing engagement metrics, functional independence improvement, and motivation scores. A simulated 180-day recovery dataset. SHAP analysis and performance comparisons provide insights into model interpretability and the influence of interventions performed using R. Results indicate that AI-driven gamification significantly enhances patient engagement, improving rehabilitation outcomes. The study provides a data-driven foundation for integrating AI-driven gamification in healthcare interventions. Also, this research simulates the application of a game-based cognitive therapy on day 91 and studies its effects using AI models for intervention analysis on simulated stroke recovery data with time series modeling as a forecasting model.