## 6 Novel mHealth Predictive Outbreak for COVID-19 (mPOC) Algorithm and IoMT Protocol
### Simulation Environment and Parameter Setup  
The mPOC system has been tested and simulated using the LabVIEW Community Edition [45], which is a powerful and versatile platform for data acquisition, analysis, and control. This subsection outlines the simulation environment setup and the related parameter configuration within the LabVIEW system.  
1. LabVIEW Simulation Environment: The LabVIEW Community Edition provides an ideal simulation environment for testing the mPOC system's functionalities in a controlled and repeatable manner. The LabVIEW graphical programming interface allows for easy integration of various components, making it suitable for simulating the complex interactions between wearable IoMT device emulation, data processing algorithms, and outbreak prediction models.  
2. Wearable IoMT Device Emulation: To mimic real-world data acquisition from wearable IoMT devices, LabVIEW incorporates virtual instrumentation for emulating physiological signals, including EMG, EEG, ECG, and breathing patterns. This emulation allows for comprehensive testing of the mPOC system's data collection capabilities under different outbreak scenarios.
3. Data Processing Algorithms: LabVIEW's extensive library of built-in functions and tools is leveraged to develop and integrate data processing algorithms into the simulation environment. These algorithms simulate the real-time processing and analysis of user-centric physiological parameters, such as calculating Predictive Exposure Index (PEI) and Deterioration Risk Index (DRI) based on EMG, EEG, ECG, and breathing pattern data.
4. Outbreak Prediction Models: Within LabVIEW, sophisticated machine learning and artificial intelligence (AI) models are incorporated to predict outbreak trends and patterns based on the processed physiological data. These models take into account both bottom-up user-centric data and top-down public health information to make accurate outbreak predictions.
5. Parameter Setup: The LabVIEW simulation environment allows for flexible parameter configuration to test various outbreak scenarios and system responses. Key parameters include: - Outbreak Scenarios--Different outbreak scenarios--including varying disease transmission rates and geographic spread--can be simulated to assess the mPOC system's predictive capabilities under diverse conditions. - Physiological Signal Variability--LabVIEW allows for the introduction of signal noise and variability to emulate real-world fluctuations in physiological signals, enabling robustness testing of the system. - Network Latency--Parameters related to network connectivity and latency are adjustable to evaluate the system's performance in handling real-time data transmission from wearable IoMT devices to the central system. - Predictive Thresholds--The LabVIEW simulation environment facilitates the dynamic adjustment of predictive thresholds for PEI and DRI, enabling fine-tuning of the system's sensitivity and specificity in issuing outbreak warnings.  
The accuracy and responsiveness of the mPOC system during various scenarios were tested, which are presented in Figure 4 and explained in detail in Section 7.2.  
Figure 4: The performance measure (accuracy versus movement) of the mPOC system.