基于粗糙集改进的疗法型元宇宙辅助系统
Rough Set improved Therapy-Based Metaverse Assisting System
AI总结：
本文提出一种融合粗糙集优化EMG/IMU数据与认知行为疗法的慢性颈肩痛辅助系统，并探索其在元宇宙中的沉浸式个性化治疗应用。
摘要：
慢性颈肩痛（CNSP）是一个重大的全球公共卫生问题。物理治疗和康复等传统治疗方法存在成本高、精度低和用户不适等缺点。本文提出了一种基于认知疗法理论（CBT）的交互式系统，用于慢性颈肩痛治疗。该系统包括一个疼痛检测模块，利用肌电图（EMG）和惯性测量单元（IMU）监测疼痛，并通过粗糙集理论优化数据；以及一个认知治疗模块，进一步处理这些数据以实施基于CBT的干预措施，包括按摩和热疗。文中概述了一项实验计划，以评估该系统的有效性和性能。其目标是创建一种可用于慢性颈肩痛治疗的易获取设备。此外，本文还探讨了该系统在元宇宙环境中的应用，以增强治疗的沉浸感和个性化。该元宇宙平台可模拟治疗环境，并对实时患者数据做出响应，从而支持对治疗方案的持续监测和调整。
英文摘要：
Chronic neck and shoulder pain (CNSP) is a major global public health issue. Traditional treatments like physiotherapy and rehabilitation have drawbacks, including high costs, low precision, and user discomfort. This paper presents an interactive system based on Cognitive Therapy Theory (CBT) for CNSP treatment. The system includes a pain detection module using EMG and IMU to monitor pain and optimize data with Rough Set theory, and a cognitive therapy module that processes this data further for CBT-based interventions, including massage and heating therapy. An experimental plan is outlined to evaluate the system's effectiveness and performance. The goal is to create an accessible device for CNSP therapy. Additionally, the paper explores the system's application in a metaverse environment, enhancing treatment immersion and personalization. The metaverse platform simulates treatment environments and responds to real-time patient data, allowing for continuous monitoring and adjustment of treatment plans.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
