使用红外热成像识别床铺系统覆盖率的研究
Haonan Ma1, Guodan Liu2, Yulei Lin1
1School of Environmental and Municipal Engineering, Qingdao University of Technology, No. 777 Jialingjiang Road, Huangdao District, Qingdao, 266520, Shandong province, China.
Journal of thermal biology
|May 27, 2025
概括
本研究引入了一种非接触式方法,使用红外热成像来实时识别床铺系统覆盖率 (BSCR). K-means集群实现了高准确度,女性比男性显示更高的BSCR,为睡眠热舒适模型提供了洞察力.
科学领域:
- 热舒适性研究热舒适性研究
- 睡眠科学 睡眠科学
- 图像处理 图像处理
背景情况:
- 准确评估床铺系统覆盖率 (BSCR) 对于了解睡眠热舒适度至关重要.
- 现有的BSCR评估方法通常是基于接触的,缺乏实时功能.
- 开发一种非接触式的实时方法对于客观的睡眠分析至关重要.
研究的目的:
- 开发和验证一种非接触式方法,用于实时识别床铺系统覆盖率 (BSCR).
- 评估拍摄角度和环境温度对BSCR识别精度的影响.
- 为了将BSCR与主观的热感知和客观的睡眠质量相关联.
主要方法:
- 红外热成像与图像细分算法相结合 (K-means集群测试).
- 在不同的拍摄角度 (45°,60°,90°) 和环境温度 (23°C,26°C,29°C) 下从30名受试者收集数据.
- 在夏季实时识别BSCR,同时收集热感觉,热舒适度投票和睡眠质量数据.
主要成果:
- 在BSCR识别方面,K-means集群显示出高准确度 (MAE: 3.70,RMSE: 4.67,R2: 0.901).
- 为红外摄像头确定了60°的最佳拍摄角度.
- 测试范围内的环境温度 (23°C-29°C) 并没有显著影响识别准确度.
- 在舒适的睡眠期间,平均BSCR为76.6%.
- 与男性相比,女性的BSCR显著更高 (8.9%) (p < 0.01).
结论:
- 拟议的非接触式方法有效地实时识别BSCR.
- 这些发现为开发非接触式睡眠热舒适度预测模型提供了有价值的数据.
- 在BSCR中性别差异凸显了个性化睡眠环境评估的必要性.
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