Theory informed framework for integrating environmental and physiologic data in applications targeting productivity and well-being in workplace

We propose a framework targeting mental health in workplace by tracking the environmental and physiological variables. Environmental variables (noise, air quality, light intensity, etc.) will be collected by sensor nodes installed for each variable and physiological changes are measured by recording Electrocardiogram (ECG) signal, providing information about heart activity. ECG data is used to get Heart Rate Variability (HRV) values, indicating the physiological state based on Polyvagal Theory. Data analysis from these two sources (environment and physiology) together helps to generate a system alert suggesting ways (short walk, listening to music) to manage the mental health without aggravating it, throughout the day. This framework creates awareness about the mental state of an individual, giving them opportunity to restore their mental state and protect it from getting worse. Mental health affects the productivity of a person. Targeting mental health improves productivity in a workplace. This paper proposes the framework and suggests future steps in deployment. The framework improves upon existing methods by considering dependence of environmental factors on individual autonomic state.