## 2 Materials and Methods
### Physical and Psychological Well-Being Tracking Component  
The first component of the analysis focuses on utilizing a custom wearable device (CWD) designed to monitor various physiological parameters contributing to employee well-being. This component provides the parameters needed to track health metrics to promote a holistic understanding of an individual's physical and overall wellness. The CWD is equipped with several hardware features:  
1. The device features an optical heart rate sensor that continuously monitors the user's heart rate. This feature provides real-time data on both resting and active heart rates, allowing users to track their cardiovascular health. 2. The three-axis accelerometer tracks movement and activity levels, including steps taken, distance traveled, and active minutes. This sensor quantifies physical activity and encourages employees to maintain an active lifestyle through an hourly movement alert. 3. A display that gives users easy access to health metrics, notifications, and fitness data. This display facilitates user interaction with the device. 4. An advanced algorithm to analyze sleep patterns, measuring deep sleep, light sleep, and wake times. This feature helps users understand their sleep quality and duration. 5. A battery life of up to 10 days on a single charge for continuous monitoring without frequent interruptions for charging. 6. A synchronization app that saves the collected data into a custom database. Users can track trends over time and set personalized health goals. The wearable data this research uses include parameters captured through commercially available fitness trackers. For heart rate, both resting and active states are recorded to assess the heart rate coefficient against daily norms. Segmented into active and passive intervals, step counts inform the physical activity coefficient. Sleep data include total sleep duration and the breakdown of deep versus light sleep phases, contributing to the sleep quality coefficient. These granular data from wearables are then paired with sentiment analysis, capturing the psychological dimension of well-being. Together, these data sources enable a comprehensive assessment of both physical and emotional states. The analysis covers 605 days of monitoring data, collected from 1 January 2023 to 18 October 2024, with some days missing due to equipment being discharged. During this period, the data provide health metrics of employees, with 51 cumulative days where monitoring did not occur. The 605 days cover physical and psychological well-being assessments through various health parameters gathered from the CWD. The SQL Server database contains the following parameters:  
* date: The monitored stats date. * avgRate, minRate, and maxRate represent the average heart rate of the day, minimum heart rate, and maximum heart rate, helping to assess cardiovascular health and stress levels. * noSteps is the total number of steps taken. This measure tracks physical activity, reflecting a healthy lifestyle, especially in sedentary work environments. distanceM is the total distance covered in meters. By calculating the distance covered, organizations encourage movement throughout the day, combating the adverse effects of prolonged sitting. * intensActDistance is the distance covered explicitly while running. This parameter emphasizes active engagement in physical exercise, which is an important parameter for physical and mental well-being. * burnCalories represents the total calories burned. Monitoring calories burned helps employees make informed decisions about their physical health and activity levels. * deepSleep, shallowSleep, and wakeTime are the duration of deep sleep (in minutes), duration of shallow sleep (in minutes), and total wake time during the night (in minutes). These metrics help evaluate the quality of sleep, which is a component of overall health and cognitive function.