智能枕头:考虑睡眠习惯的基于物联网的压力检测设备

Laavanya Rachakonda, S. Mohanty, E. Kougianos, Kalyani B. Karunakaran, M. Ganapathiraju
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引用次数: 9

摘要

晚上的睡眠质量反映了白天的工作效率。为了充分利用一天,了解压力等影响睡眠的因素是很重要的。技术的进步可以帮助一个人自我分析这种情况。为此,我们提出了一个基于睡眠习惯的系统来帮助人们缓解压力。在睡眠的非快速眼动(NREM)和快速眼动(REM)阶段,体温、血压、呼吸速率和心率等生理参数往往会发生变化。非生理参数,如睡眠小时数、打鼾的范围、睡眠姿势和环境条件也会影响睡眠质量。为了分析睡眠习惯,这里考虑了这些因素。定义了一个系统,它可以预测应力水平高达五种状态:高、中高、中、中低和低应力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart-Pillow: An IoT Based Device for Stress Detection Considering Sleeping Habits
The quality of sleep during the night reflects on productivity during the day. To make the most out of a day, it is important to understanding the factors such as stress which impair sleep. Advances in technologies may aid a person to self-analyze such situations. For this, we propose a system which helps in stressfulness of a person based on sleeping habits. Physiological parameters such as temperature, blood pressure, respiration rate, and heart rate tend to vary during the NREM (Non Rapid Eye Movement) and REM (Rapid Eye Movement) stages of sleep. Non-physiological parameters such as the number of sleeping hours, the range of snoring, the sleeping position, and environmental conditions can also affect the quality of sleep. These factors are considered here in order to analyze sleeping habits. A system is defined which can predict stress levels up to five states: High, Medium-High, Medium, Medium-Low and Low stress.
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