A Multisensor System Embedded in a Computer Mouse for Occupational Stress Detection.

Area of Science:

• Biomedical Engineering
• Occupational Health
• Human-Computer Interaction

Background:

• Occupational stress presents significant health and economic challenges in modern workplaces.
• Automatic stress detection is crucial for effective management, particularly in evolving post-COVID work environments.
• Existing methods for stress monitoring may lack unobtrusiveness in typical office settings.

Purpose of the Study:

• To design, develop, and validate a multisensor system integrated into a computer mouse for detecting office work stress.
• To assess the system's ability to identify physiological markers of stress during simulated work tasks.
• To evaluate the impact of work-related stressors on physiological responses and cognitive performance.

Main Methods:

• Development of a computer mouse incorporating photoplethysmography (PPG) and galvanic skin response (GSR) sensors.
• Acquisition of PPG and GSR signals from 32 participants during stress-inducing office-based tasks.
• Application of Kalman and moving average filters for signal processing, followed by feature extraction of pulse rate and skin conductance.

Main Results:

• Stressful task periods significantly increased participants' self-reported stress levels and negatively impacted cognitive performance.
• Statistically significant differences were observed in measured physiological parameters (pulse rate, skin conductance) during periods with and without stressors.
• The developed system demonstrated the capability to detect stress through physiological signal changes.

Conclusions:

• The proposed multisensor computer mouse system is effective for unobtrusively monitoring and detecting occupational stress in office workers.
• Physiological responses captured by the device correlate with experimentally induced stress.
• This technology offers a potential tool for proactive stress management in the workplace.