Author
Listed:
- Gulnur Tyulepberdinova
- Zhanar Oralbekova
- Murat Kunelbayev
- Gulshat Amirkhanova
- Sulu Issabayeva
Abstract
Modern challenges require effective methods for stress monitoring and management, which drive the implementation of innovative solutions. This article presents the development of a wearable device integrated with Internet of Things (IoT) technology, capable of detecting and quantitatively assessing stress levels in real-time. This technology enhances the accuracy of stress evaluation, enabling quick responses and the development of personalized stress management strategies. The device uses a Field-Programmable Gate Array (FPGA) as the main controller and includes nine sensors: Photo plethysmography (MAX30102), electroencephalography (EEG), electrocardiography (ECG), glucose level (GS), electromyography (EMG), temperature (TS), pressure (PS), heart rate (HRS), pulse (PS), and galvanic skin response (GSR). These sensors measure physiological parameters such as heart rate, skin conductance, and breathing rate, which are associated with stress. The collected data is transmitted via Wi-Fi to the Firebase platform. The article also discusses the benefits of IoT-enabled wearable devices, their versatility for use in various environments such as offices, educational institutions, and healthcare settings, where stress management plays a critical role. Continuous monitoring allows users to track stress levels and take timely actions to improve their well-being. Experimental data shows that the device achieves 85% accuracy in measuring heart rate and breathing. This device can be valuable in both everyday life and professional fields, including medicine, education, and work environments, where stress control is crucial for health and productivity).
Suggested Citation
Gulnur Tyulepberdinova & Zhanar Oralbekova & Murat Kunelbayev & Gulshat Amirkhanova & Sulu Issabayeva, 2025.
"Design of an IoT-enabled wearable device for stress level monitoring,"
International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(1), pages 599-612.
Handle:
RePEc:aac:ijirss:v:8:y:2025:i:1:p:599-612:id:4406
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