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Rough Set improved Therapy-Based Metaverse Assisting System

Jin Cao, Yanhui Jiang, Chang Yu, Feiwei Qin, Zekun Jiang

TL;DR

The paper tackles CNSP by proposing a CBT-based interactive system that fuses sensor-driven data with Rough Set theory to enhance pain detection and tailor cognitive-behavioral interventions. It presents two core computational pipelines: EMG processing on Arduino hardware and Rough Set–based data screening to identify meaningful features, implemented via Algorithms 1 and 2. A two-module system combines objective pain detection (EMG/IMU) with CBT-enabled therapies (massage and heating) and envisions metaverse immersion to boost treatment immersion and personalization. An outlined evaluation plan combines qualitative interviews and quantitative measures to assess effectiveness, with an emphasis on accessibility and real-time adaptation in a metaverse-enabled care continuum.

Abstract

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.

Rough Set improved Therapy-Based Metaverse Assisting System

TL;DR

The paper tackles CNSP by proposing a CBT-based interactive system that fuses sensor-driven data with Rough Set theory to enhance pain detection and tailor cognitive-behavioral interventions. It presents two core computational pipelines: EMG processing on Arduino hardware and Rough Set–based data screening to identify meaningful features, implemented via Algorithms 1 and 2. A two-module system combines objective pain detection (EMG/IMU) with CBT-enabled therapies (massage and heating) and envisions metaverse immersion to boost treatment immersion and personalization. An outlined evaluation plan combines qualitative interviews and quantitative measures to assess effectiveness, with an emphasis on accessibility and real-time adaptation in a metaverse-enabled care continuum.

Abstract

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.
Paper Structure (34 sections, 8 equations, 5 figures)

This paper contains 34 sections, 8 equations, 5 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Therapeutic Interventions for CNSP
  4. Cognitive Behavioural Therapy
  5. EQUATIONS AND ALGORITHM
  6. Equations 1: EMG Processing with Arduino
  7. Initialize Arduino System
  8. Data Collection
  9. Data Processing
  10. Data Logging and Monitoring
  11. Filtering and Amplification
  12. Feature Extraction
  13. Analysis and Feedback
  14. Equations 2: Screening Meaningful Data Using Rough Set Theory and Importance
  15. Data Processing and Normalization
  16. ...and 19 more sections

Figures (5)

  • Figure 1: A novel interactive system for the treatment of CNSP. It is divided into two interactive steps. Step 1 is pain collection and recognition. Step 2 is CBT adjunctive treatment.
  • Figure 2: Pain detection Arduino sensor wiring logic diagram.
  • Figure 3: Equipment diagrams to assist in the treatment of CNSP. (A) Exploded view of equipment and location of sensors. (B) Panoramic view of head and neck apparatus. (C) Simulation of figure wearing.
  • Figure 4: EMG Module and Electrical Nerve Stimulation Module: perform muscle testing to detect tense (painful) muscles and relaxed (pain-free) powers to detect values and capture pain intervals.
  • Figure 5: Add on quantitative data collection method, directly by user's input for pain sensation