Wearable Healthcare Devices for Monitoring Stress and Attention Level in Workplace Environments

TL;DR

This survey analyzes wearable healthcare devices for monitoring stress and attention in workplace environments, comparing head-worn, wrist-worn, finger-worn, and chest-worn modalities. It details sensor configurations (EEG, HRV, PPG, accelerometers) and links them to applications such as stress and attention detection, early warning scoring, and mental-health monitoring, highlighting algorithmic approaches and practical deployment constraints. The work surveys a broad set of studies, reporting performance ranges, data-access limitations, and the benefits of multimodal fusion, while identifying persistent challenges posed by uncontrolled environments and privacy concerns. It emphasizes the need for robust denoising, missing-data handling, and energy-aware, user-friendly systems to enable reliable, real-world monitoring of workers’ stress and attention. The findings advocate for integrated, non-intrusive wearable solutions that balance data quality with comfort and privacy to positively impact workplace health and productivity.

Abstract

Wearable devices have revolutionized healthcare monitoring, allowing us to track physiological conditions without disrupting daily routines. Whereas monitoring physical health and physical activities have been widely studied, their application and impact on mental health are significantly understudied. This work reviews the state-of-the-art, focusing on stress and concentration levels. These two can play an important role in workplace humanization. For instance, they can guide breaks in high-pressure workplaces, indicating when and how long to take. Those are important to avoid overwork and burn-out, harming employees and employers. To this end, it is necessary to study which sensors can accurately determine stress and attention levels, considering that they should not interfere with their activities and be comfortable to wear. From the software point of view, it is helpful to know the capabilities and performance of various algorithms, especially for uncontrolled workplace environments. This work aims to research, review, and compare commercially available non-intrusive measurement devices, which can be worn during the day and possibly integrated with healthcare systems for stress and concentration assessment. We analyze the performance of various algorithms used for stress and concentration level assessment and discuss future paths for reliable detection of these two parameters.

Figures (3)

• Figure 1: Embedded sensors in wearable devices (PO: Pulse Oximeter, TM: Thermometer, BT: Bluetooth, ST: Skin Temperature, AM: Altimeter, Acc: Accelerometer, Gyro: Gyroscope, GPS: Global Positioning System)
• Figure 2: A Subject wearing different wearable healthcare devices including Empatica E4 and Polar M430 smartwatches, BrainLink headband, Polar chestband, and Oura Ring while performing a stress detection activity e4_specifications_websitePolar_Watch_M430polar_h10_specifications_websitemacrotellect_specifications_websiteoura_ring_website.
• Figure 3: Overview of biosensor usage in stress and attention detection research (SKT: Skin temperature, EOG: Electrooculography)