This paper presents an interactive system for the treatment of chronic neck and shoulder pain (CNSP) based on Cognitive Therapy Theory (CBT). The system integrates pain detection using EMG and IMU sensors with Rough Set theory to optimize data and enhance precision. It also includes a cognitive therapy module that provides interventions such as massage and heating. The system is designed to be accessible and user-friendly, with the potential for integration into a metaverse environment to improve treatment immersion and personalization. The metaverse platform simulates treatment environments and responds to real-time patient data, enabling continuous monitoring and adjustment of treatment plans. The system's effectiveness is evaluated through an experimental plan involving quantitative and qualitative methods. The paper also explores the application of Rough Set theory in data screening and analysis, enhancing the accuracy of EMG signal processing. The system aims to provide a more effective and personalized treatment for CNSP by combining physiological and psychological approaches. The study highlights the importance of integrating cognitive therapy techniques with technological advancements to address the limitations of traditional treatments. The proposed system is expected to improve the accuracy of pain detection and provide more effective therapeutic interventions for CNSP patients.This paper presents an interactive system for the treatment of chronic neck and shoulder pain (CNSP) based on Cognitive Therapy Theory (CBT). The system integrates pain detection using EMG and IMU sensors with Rough Set theory to optimize data and enhance precision. It also includes a cognitive therapy module that provides interventions such as massage and heating. The system is designed to be accessible and user-friendly, with the potential for integration into a metaverse environment to improve treatment immersion and personalization. The metaverse platform simulates treatment environments and responds to real-time patient data, enabling continuous monitoring and adjustment of treatment plans. The system's effectiveness is evaluated through an experimental plan involving quantitative and qualitative methods. The paper also explores the application of Rough Set theory in data screening and analysis, enhancing the accuracy of EMG signal processing. The system aims to provide a more effective and personalized treatment for CNSP by combining physiological and psychological approaches. The study highlights the importance of integrating cognitive therapy techniques with technological advancements to address the limitations of traditional treatments. The proposed system is expected to improve the accuracy of pain detection and provide more effective therapeutic interventions for CNSP patients.