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- W4386870679 abstract "In current scenario, mental stress has detrimental impacts on one’s health. To mitigate detrimental ramifications, high-level stress must be detected early on. Following the introduction of wearable devices that could become a part of our daily lives, according to study, researchers have started detecting extreme stress in people who used them during their daily routines. An automatic stress detection system is developed by incorporating physiological signals obtained from unobtrusive clever, smart portable wearable devices that can be carried during individuals’ daily life routines. Using various approaches of machine learning, successfully differentiated contest stress, relatively higher cognitive load (lecture), and relaxed time activities using heart activity, skin conductance and accelerometer signals, and skin temperature. Main objective is to develop a wrist band which identifies whether the student is under stress or not based on various parameters like heartrate and temperature of human body. This information can be obtained by employing various sensors such as an electrocardiogram (ECG), galvanic skin response (GSR)." @default.
- W4386870679 created "2023-09-20" @default.
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- W4386870679 date "2023-01-01" @default.
- W4386870679 modified "2023-09-27" @default.
- W4386870679 title "Stress Detection in Classroom Environment Using Physiological Data" @default.
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- W4386870679 doi "https://doi.org/10.1007/978-981-99-1588-0_15" @default.
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