# Using Smartwatches in Stress Management, Mental Health, and Well-Being: A Systematic Review
## 3 Smartwatches as Stress Assessment Tools
### Stress Management  
This aspect was examined by [PERSON] et al. (2018), who conducted a study focused on the ability of smartwatches to detect and predict stress levels using machine learning techniques. The aim of their research was to compare different stress prediction models using both objective indicators (predefined stress-inducing stimuli) and subjective participant self-reports. To achieve this, they supervised a controlled experiment with 32 healthy volunteers, each performing a series of stress-inducing tasks--social, cognitive, and physical tasks--while wearing a commercially available smartwatch equipped with appropriate sensors. Throughout the tasks, the watch continuously recorded physiological signals (e.g., heart rate) while the participants wore a commercially available smartwatch equipped with appropriate sensors. The watch continuously recorded physiological signals (e.g., heart rate). Figure 3 illustrates the mechanism by which these signals were acquired, particularly through the use of photoplethysmography (PPG) sensors and optical components embedded in the smartwatch. Participants were periodically asked to report their perceived stress levels. Furthermore, according to the study by [PERSON] et al. (2019), the research focuses on technological innovation through the development of an integrated smartwatch that incorporates sensors for detecting mental stress. In this study, the researchers adopt an approach that combines biochemical measurements (via a cortisol sensor that detects sweat) and physiological parameters (via heart rate variability--HRV). The method involves detailed experimental procedures, such as theoretical calculations (DFT) to estimate the electrostatic potential between the polymer monomer and cortisol, and the design of a sensor based on organic electrochemical transistors (OECTs). This process demonstrates that the sensor offers high sensitivity and reusability, with the ability to convert small changes in cortisol levels into corresponding changes in electric current, enabling the direct and non-invasive monitoring of mental stress ([PERSON] et al., 2019). The detailed analyses of the sensor's various parameters,such as the role of Prussian Blue in enhancing conductivity, exemplify the integration of theoretical and practical approaches in achieving a comprehensive solution. From a broader perspective, these studies present complementary approaches to the evaluation and implementation of smartwatches in healthcare. While [PERSON]'s [12] study offers a theoretical and psychologically oriented analysis of the process leading to continued usage intention, the work of [PERSON] et al. [19] contributes technical innovation, focusing on the development and optimization of an integrated mental stress detection system. Conversely, the systematic review by [PERSON] et al. [20] synthesizes data from various interventions, highlighting both positive outcomes and practical challenges associated with smartwatch use in real-world clinical settings. The combined approach emerging from these studies emphasizes the necessity for interdisciplinary research, where the integration of theoretical models, technical optimization, and the critical evaluation of the existing literature is essential for the effective exploitation of smartwatch capabilities in digital health. This integrative perspective suggests that psychological processes, technological innovations, and practical applications must all be taken into account in order to achieve a comprehensive solution that improves not only health monitoring but also users' quality of life [12; 19; 20]. According to the study by [PERSON], [PERSON], and [PERSON] [21], their research provides an extensive overview of efforts to detect stress in daily life through the use of smartphones and wearable devices.